Journal of Intelligent & Fuzzy Systems - Volume Pre-press, issue Pre-press

Authors: Ma, Weimin | Lei, Wenjing | Sun, Bingzhen

Article Type: Research Article

Abstract:  Three-way decisions, deduced from decision-theoretic rough set (DTRS), provide useful approaches for uncertain decision-making problems from a new perspective. Considering situations where decision-makers hesitate among several evaluation values, the hesitant fuzzy set, an innovative extension of fuzzy set, is introduced into multigranulation DTRS under multi-criteria group decision-making (MCGDM) environment. More specifically, we incorporate DTRS with hesitant fuzzy information into MCGDM in this paper, and explore the related decision-making mechanism. Firstly, the variable precision multigranulation hesitant fuzzy DTRS over two universes is defined by utilizing hesitant relation and conditional probability of a hesitant fuzzy event, and the associated decision rules and …properties are derived and carefully investigated. Accordingly, as two special types, optimistic and pessimistic multigranulation hesitant fuzzy DTRS over two universes are constructed similarly at the same time. Then, different from loss functions with fixed values in most of the existing DTRS models, the loss function is not given directly but calculated from evaluation values expressed by hesitant fuzzy elements. With the aid of the distance measure of hesitant fuzzy elements, the calculation of loss functions is presented. Furthermore, the three-way group decision-making model based on multigranulation hesitant fuzzy DTRS over two universes is established to address MCGDM problems, and key steps of this model are designed. Finally, we elaborate the application of the model by an example of green supplier selection problem. Show more

Keywords: Three-way decisions, rough set over two universes, hesitant fuzzy rough set, multigranulation, multi-criteria group decision-making, green supplier selection

DOI: 10.3233/JIFS-190970

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-15, 2019

Authors: Khan, Vakeel A. | Fatima, Hira | Ahmad, Ayaz | Idrisi, Mohd Imran

Article Type: Research Article

Abstract:  The concept of fuzzy sets was introduced by Zadeh as a means of representing data that was not precise but rather fuzzy. Recently, Ko c ˇ inac [12 ] studied some topological properties of fuzzy antinormed linear spaces. This has motivated us to introduce and study the fuzzy antinormed double sequence spaces with respect to ideal by using a compact linear operator and prove some theorems, in particular convergence and completeness theorems on these new double sequence spaces.

Keywords: Ideal, filter, I-convergence, fuzzy antinormed space

DOI: 10.3233/JIFS-182575

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-6, 2019

Authors: Visalakshi, P. | Prabakaran, S.

Article Type: Research Article

Abstract: The nature of mobile nodes are affects the performance of MANET. The main requirement of secured MANET is use of secure protocols which ensure the network integrity, confidentiality, availability and authenticity. Recently, the secure protocols have been used to resists such attacks in MANET. Spoofing attack is one of them, which affects network by an attacker program successfully acts on another node behalf by impersonating data. In this paper, we investigate the spoofing attack problems in MANET and propose an optimal intrusion detection system (OIDS) using hybrid optimization algorithm (HOA) named as OIDS-HOA. Here, we propose an improved whale optimization …(IWO) algorithm for efficient cluster formation and a cluster chain weight metrics approach (CCWW) for trust degree computation of each mobile node. Moreover, the intrusion detection system (IDS) is done by the condition check algorithm and the intrusion response action (IRA) is performed by average route trust with three different responses are: No Punishment (NP), Route Change (RC) and Route Isolate (RI). The simulation results show that the effectiveness of proposed OIDS-HOA scheme in terms of packet delivery fraction, end-end-delay, energy consumption, overhead and packet drop ratio. Show more

Keywords: Mobile ad hoc network (MANETs), optimal intrusion detection system (OIDS), hybrid optimization algorithm (HOA), improved whale optimization (IWO), intrusion detection system (IDS), spoofing attack, trust degree

DOI: 10.3233/JIFS-182881

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-14, 2019

Authors: Shah, Nasir | Ali, Muhammad Irfan | Shabir, Muhammad | Ali, Abbas | Rehman, Noor

Article Type: Research Article

Abstract:  Z-soft rough covering models introduced by zhan et al are important generalizations of classical rough set theory to deal with more complex problems of real world. So far, the existing studies mainly focus on constructing various forms of approximation operators and their related properties by means of neighborhoods. In this paper, we introduce different kinds of uncertainty measures related to Z-soft rough covering sets and discuss their limitations. An axiomatic definition of knowledge granulation for soft covering approximations space is introduced. Some main theoretical results are obtained and investigated with the help of examples. Finally, a fully developed example describing …the application of the proposed theory in multicriteria decision making is constructed. Show more

Keywords: Z-soft rough covering sets, uncertainty, knowledge granulation, axiomation, decision making

DOI: 10.3233/JIFS-182708

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-11, 2019

Authors: Alsager, K.M. | Alshehri, N.O.

Article Type: Research Article

Abstract:  In this paper, we present a novel hybrid model called multi Q -dual hesitant fuzzy soft (Mk QDHFS) rough set model, by the combination of rough sets and Mk QDHFS sets. We investigate some fundamental properties of Mk QDHFS rough set model. Further, we develop Mk QDHFS rough approximation operators with the help of Mk QDHFS relations. We discuss some useful properties of lower and upper Mk QDHFS rough approximation operators. Furthermore, we present a novel framework for handling vagueness in decision-making problems based on Mk QDHFS rough sets. Finally, we give an …application to analyze the failure detection in unmanned aircraft systems (UAS) to show the validity of the proposed decision-making method. Show more

Keywords: Q-dual hesitant fuzzy soft set, MkQDHFS rough set, UAS failure detection approach, decision-making method

DOI: 10.3233/JIFS-182624

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-13, 2019

Authors: Mohagheghi, Vahid | Mousavi, S. Meysam | Mojtahedi, Mohammad

Article Type: Research Article

Abstract: Project portfolio selection (PSP) problems have been explored for more than two decades. As a result, in the last two decades, the literature of PSP has experienced a sharp increase. Despite this increase, the literature has not been thoroughly reviewed. The main goal of this paper is to investigate and explain the features, state of the art, research direction, and real-world applications of PSP. To pursue this goal, the paper investigates PSP form aspects of PPS criteria, uncertainty modelling tools, selection and optimization methods, and application areas. More than 105 journal papers have been reviewed. The review has resulted in …the categorization of applied tools in PPS in addition to the presentation of new research directions. Show more

Keywords: Project portfolio selection problem, real-world applications, uncertainty, project decision making

DOI: 10.3233/JIFS-182847

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-15, 2019

Authors: Guevara, Edgar | Flores-Castro, Jorge-Arturo | Peng, Ke | Nguyen, Dang Khoa | Lesage, Frédéric | Pouliot, Philippe | Rosas-Romero, Roberto

Article Type: Research Article

Abstract: Research to predict epileptic seizures has been mainly focused on the analysis of electroencephalography (EEG) signals; however, recent research efforts have encouraged the use of a relatively new optical signal modality, called functional Near-Infrared Spectroscopy (fNIRS). In fNIRS, near-infrared light is injected into the scalp and the intensity of the reflected light is registered in optodes. Light absorption in hemoglobin depends on the level of blood oxygenation, which is related to brain activity. In this technique, two parameters are measured at each optode, the relative level of oxygenated hemoglobin (HbO) and the relative level of deoxygenated …hemoglobin (HbR). In this work we investigated the feasibility of predicting epileptic seizures, using either fNIRS, EEG, or a combination of both signals. In one set of experiments, different implementations for epileptic seizure prediction are tested by using (1) different combinations of electrical and optical signals (EEG, HbO, HbR, EEG+HbO, EEG+HbR, HbO+HbR, EEG+HbO+HbR) and (2) two different classifiers, (Support Vector Machine - SVM and Multi-Layer Perceptron - MLP). In the second set of experiments, seizures are predicted within a five-minute window that is moved up to 15 minutes before the start of the epileptic seizure. By computing the@@ Positive Predictive Value (PPV) and the accuracy , it is demonstrated that fNIRS-based epileptic prediction outperforms EEG-based epileptic prediction. By using optical signals and the SVM classifier, a PPV greater than 99% and an accuracy of 100% were obtained. PPV values of 100% are also obtained when seizures are predicted up to 15 minutes in advance. Furthermore, Kernel Discriminant Analysis (KDA) is used to demonstrate that the highest separability among the classes, corresponding to different epileptic signal phases (pre-ictal , ictal , and inter-ictal ), is achieved when fNIRS recordings are used as features for prediction. Finally, fNIRS-based epileptic seizure prediction is tested with Random Chance classifiers. In this study, we showed that fNIRS signals are an effective tool to predict epileptic seizures, even without the use of EEG signals, which are the current standard for seizure prediction. Show more

Keywords: epileptic seizure, seizure prediction, functional near infra red spectroscopy (fNIRS), electroencephalogram (EEG), multi-layer perceptron (MLP), support vector machine (SVM)

DOI: 10.3233/JIFS-190738

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-14, 2019

Authors: Henselmeyer, Sylwia | Grzegorzek, Marchin

Article Type: Research Article

Abstract: The paper presents a novel approach for hourly short term forecast of load active power using discrete state Hidden Markov Models. The load data used belongs to the New York Independent System Operator (NYISO) and has been recorded in the years 2014-2017. In the first step, features the best explaining load power changes from the set of weather data, market data (price for load, losses or congestion) and calendar data (day type, day of week, season) are defined. Due to strong seasonality in the data, also a filtering step is included. Finally, the forecast itself is executed with 24 discrete …state Hidden Markov Models with a high number of states. Besides the direct comparison with the forecast results obtained by NYISO, the approach is evaluated using an additional benchmark method. Show more

Keywords: Short term load forecast, discrete state Hidden Markov Model, gaussian mixture model, multivariate gauss distribution, clustering, filtering, euclidean distance

DOI: 10.3233/JIFS-191036

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-12, 2019

Authors: Lin, Yang | Wang, Ying-Ming | Yan, Longzhong

Article Type: Research Article

Abstract: The theory of hesitant fuzzy set is powerful in capturing fuzziness when a decision maker hesitates among some possible values in assessment. In this paper, a novel method is developed for weight determination based on the hesitant fuzzy cosine similarity. This method fully considers the impact of each criterion as well as their mutual relationship on decision analysis. Additionally, we extend this cosine similarity-based method for deriving priorities from a hesitant multiplicative preference relation. This method has a clearer modeling mechanism that the priority vector derived from a hesitant multiplicative preference relation should be as highly cosine-similarity correlated with its …column vectors as possible. Then an optimization model can be sequentially established. After that, the proposed methods are demonstrated with two numerical examples and compared with other similar approaches to show the validity and superiority. Show more

Keywords: Hesitant fuzzy set, hesitant multiplicative preference relation, cosine similarity, weights determination, multi-criteria decision making

DOI: 10.3233/JIFS-191034

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-11, 2019

Authors: Wang, Huan-Huan | Tian, Sheng-Wei | Yu, Long | Wang, Xian-Xian | Qi, Qing-Shan | Chen, Ji-Hong

Article Type: Research Article

Abstract: A convolutional neural network combined with attention mechanism and a parallel joint algorithm model (CATTB) of bidirectional independent recurrent neural network are proposed. The algorithm extracts the relocation feature and the “texture fingerprint” feature for expressing the similarity of the URL (Uniform Resource Locator) binary file content of the malicious web page, and uses the word vector tool word2vec to train the URL word vector feature and extract the URL static vocabulary feature. CNN (Convolutional Neural Network) is used to extract deep local features. Secondly, Attention mechanism adjusts weight and BiIndRNN (Bidirectional Independently Recurrent Neural Network) to extract global features. …Finally, softmax is used for classification. This paper extracts more comprehensive features from different angles and using different methods. The experimental results show that the test results are higher than other researchers, and compared with other algorithms, the proposed CATTB algorithm improves the accuracy of malicious web page detection. Show more

Keywords: Malicious webpages, convolutional neural network, attention mechanism, bidirectional independently recurrent neural network

DOI: 10.3233/JIFS-190455

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-12, 2019

Authors: Lu, Haishu | Li, Rong | Zhang, Kai

Article Type: Research Article

Abstract: This paper introduces new concepts of fuzzy generalized quasi-weak transfer continuity and fuzzy generalized pseudo quasi-weak transfer continuity for fuzzy generalized discontinuous games with infinite players. Furthermore, by using a collectively maximal element theorem, we obtain some new existence results of Nash equilibria in fuzzy generalized discontinuous games with infinite players. Finally, as applications, some existence results of Nash equilibria in generalized discontinuous games are given in crisp senses. The results presented in this paper improve and generalize some known results in the literature.

Keywords: Fuzzy generalized discontinuous game, Nash equilibrium, maximal element, transfer continuity

DOI: 10.3233/JIFS-182954

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-16, 2019

Authors: Yasrebi, Mohammad | Rafe, Vahid | parvin, Hamid | Nejatian, Samad

Article Type: Research Article

Abstract: Since complexity of computer systems is growing increasingly, assuring flawless operation of these systems has become more difficult. Therefore, it is important that these systems whether software or hardware are executed as expected. Consequently, verifying system before implementation at model level is necessary. Model checking is a formal technique for validating the system automatically which decides whether the finite state system satisfies temporal property by scanning the whole state space or not. One of the most important problems in model checking is state space explosion of models which results in memory shortage in generation of all states. Therefore, this paper …presents a method which employs machine learning techniques without exploring the whole state space to predict temporal properties of trajectories in systems based on graph transmission system. the proposed method is implemented in Groove; results indicate desirable accuracy and speed of this method compared to other methods. Show more

DOI: 10.3233/JIFS-190023

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-13, 2019

Authors: Abulaish, Muhammad | Bhat, Ishfaq Majid | Bhat, Sajid Yousuf

Article Type: Research Article

Abstract:  Community detection from networks is one of the long standing and challenging tasks in the field of complex network research. Detection of communities poses numerous challenges in terms of their overlapping and hierarchical nature, dynamics of networks and underlying communities, scalability of detection algorithms on large scale networks to mention a few. Traditional community detection methods are not readily scalable to large networks mainly due to the computation of global network metrics. This paper presents a novel scalable overlapping community detection approach for large scale networks by presenting a MapReduce framework based implementation of a density-based local community detection …method. The method is divided in two stages where the first stage uses a MapReduce approach to identify a mutual-core connected subgraph of the underlying network. The second stage uses an existing connected component detection method, implemented via MapReduce , to identify connected components in the mutual-core connected subgraph generated in the first stage. A community is then taken as the union of the core-nodes in a connected component and the respective density-based neighborhood of each core-node in the connected component. The resulting approach is among the first scalable overlapping community detection methods proposed in literature. Show more

Keywords: Community detection, overlapping community, connected components, mapreduce, large-scale networks

DOI: 10.3233/JIFS-182765

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-12, 2019

Authors: Wu, Jian-Zhang | Xi, Rui-Jie | Zhu, Ye

Article Type: Research Article

Abstract:  The Choquet capacity and integral is an efficient tool to flexibly show the decision maker’s correlative preference information on multiple decision criteria as well as decision alternatives. In this paper, we enrich the capacity and Choquet integral based decision making scheme from two aspects. The first aspect is to introduce the multiple goals linear programming to aid the decision maker to find out and adjust the inconsistency among the correlative preference information, which needs little prior knowledge of field but can identify the inconsistent constraints efficiently and give the adjust suggestions flexibly. The second aspect is to propose a random …simulation based comprehensive decision aid algorithm to show the dominance relationships between all decision alternatives and then unify them into the most creditable ranking order of alternatives, which is quite different to the thought of unique representative ranking order accomplished by the optimization model of some existing methods. An illustrative example is given to show that the enriched decision making scheme is robust to deal with the inconsistent correlative preference information and also practicable to obtain the comprehensive dominance relationship of multiple decision alternatives. Show more

Keywords: Decision preference information, capacity, inconsistency check and adjustment, multiple goals linear programming, comprehensive dominance relationship

DOI: 10.3233/JIFS-190652

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-11, 2019

Authors: Algarni, M. | Al-Ghamdi, H. | Abdel-Khalek, S.

Article Type: Research Article

Abstract: Quantum information technology depends on an invaluable and tenuous resource, named quantum correlation, that shows strong significant manifestation of the coherent overlap of states of a combined quantum systems. So the quantifier of this resource under factual conditions that is, whereas corrupted via generalized optical radiation field states is still limited, and common statements on entanglement dynamics. In this article, we describe quantitatively the nonlocal correlation between a two-qubit and squeezed thermal field. Especially, considering the effect thermal photons and number of photons transition between the two qubits and squeezed thermal field. Also, the Mandel parameter, entanglement and atomic Fisher …information over the time evolution as a function of implicated parameters in the system are investigated. We have shown that the squeeze parameter and thermal photons have a potential effect of the dynamical properties of the atomic Fisher information, Mandel parameter and entanglement. Also, the AFI is very sensitive to the field parameters rather than the number of photons transition. Furthermore, the results interpreted in the case of thermal environment considering the effect of thermal photons and squeeze parameter on the evolution of the system under consideration. Show more

Keywords: Atomic Fisher information, entanglement, squeezed thermal field, concurrence, Mandel parameter.

DOI: 10.3233/JIFS-179532

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-7, 2019

Authors: Tang, Ziyuan | Srivastava, Gautam | Liu, Shuai

Article Type: Research Article

Abstract: Current accounting methods for small and medium-sized enterprises (SMEs) have long running times and low user satisfaction. Therefore, a method for the selection of accounting models for SME s based on accounting market big data (AMBD ) is proposed in this paper. Firstly, some indicators such as the current ratio, quick ratio, asset-liability ratio, accounts receivable turnover rate, and other indicators taken from the solvency, operating capacity, profitability, and growth capacity of a company are selected to set up an AMBD constraint system. Then, the principal component analysis method is used to achieve the classification of the constraints of …the AMBD . Finally, by combining particle swarm optimization with ant colony optimization, the optimal accounting model is obtained through iteration. Experimental results show that the proposed method has high efficiency and user satisfaction, and achieves a high coefficient of rationality. Furthermore, the method incorporates the constraints found in the AMBD , and meets the selection requirements of the SME accounting model. Show more

Keywords: Ant colony optimization, swarm intelligence, accounting, big data, market constraints, accounting models, choice

DOI: 10.3233/JIFS-179530

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-9, 2019

Authors: Boulaaras, Salah | Allahem, Ali

Article Type: Research Article

Abstract: Motivated by our recent publication in ([9 ]), which was supported during the academic year 2016/1437 by the Deanship of Scientific Research in Project 1175, we will develop the previous mathematical model into a two-dimensional model of the transition equations of some pollutants and their rapid spread in a particular liquid, taking into account the given stability analysis of the numerical method which based on finite difference time scheme combined with Galerkin special approximation. This method has been given by our published work in ([12 ]).

Keywords: Mathematical model, transport propagation equations, pollution, finite elements, finite differences timescheme

DOI: 10.3233/JIFS-179534

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-11, 2019

Authors: Wu, Xia | Zhang, Jialu | Zhong, Jiaming

Article Type: Research Article

Abstract: In this paper, information entropy about logarithmic form is used to measure uncertainty of knowledge, and the correlation connection between information entropy, conditional information entropy, joint information entropy and mutual information entropy are analyzed. Correlation coefficient ρ  (B , C ) between two attribute subsets in random information systems and ρ  (C /  - B ) for a conditional attributes set B relative to another condition attributes set C w.r.t. the decision attributes set D in random decision information systems are introduced. The properties of correlation coefficients are discussed, and some concepts about random information systems and random decision …information systems, such as indispensable attributes, consistent attributes and core attributes, etc, are described by using correlation coefficients. Some new methods of attribute reduction are proposed by using correlation coefficients, the corresponding algorithms based on attribute correlation coefficient are given in random information systems and in random decision information systems, the listed examples and the experimental result show that the algorithms are effective. Show more

Keywords: Random decision information system, probability distribution of attributes set, information entropy of attributes set, correlation coefficient, attribute reduction

DOI: 10.3233/JIFS-179533

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-13, 2019

Authors: Yu, Mingchao | Li, Gongfa | Jiang, Du | Jiang, Guozhang | Zeng, Fei | Zhao, Haoyi | Chen, Disi

Article Type: Research Article

Abstract: In view of the fact that independent gesture recognition cannot fully meet the natural, convenient and effective needs of actual human-computer interaction, this paper analyzes the current research status of gesture recognition based on EMG signal, and considers the practical application value of EMG signal processing in prosthetic limb control, mobile device manipulation and sign language recognition. Therefore, in this paper, the particle swarm optimization (PSO) algorithm is used to optimize the center value and the width value of the radial basis function in the RBF neural network. And the author uses the EMG signal acquisition device and the electrode …sleeve to collect the four-channel continuous EMG signals generated by eight consecutive gestures. Then, the author performs noise reduction and active segment detection based on the summation, and extracts the well-known 5 time domain features. Finally, the data obtained are normalized and divided into training set and test set to train and test the classifier. Simulation experiments show that the RBF neural network which optimizes the center value and width value of radial basis functions via particle swarm optimization algorithm achieves a high recognition rate in continuous gesture recognition. Show more

Keywords: Particle swarm optimization, RBF neural network, electromyogram signal, continuous gesture

DOI: 10.3233/JIFS-179535

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-12, 2019

Authors: Wang, Xiaohong | Wu, Huaiqin | Cao, Jinde

Article Type: Research Article

Abstract: This paper is concerned with the global leader-following consensus issue for fractional-order nonlinear multi-agent systems, where the inherent dynamics is modeled to be discontinuous, and subject to nonlinear growth. A new nonlinear control protocol, which includes discontinuous factors, is designed to realize the global leader-following consensus goal. Under fractional Filippov differential inclusion framework, by applying fractional Lyapunov functional approach and Clarke’s non-smooth analysis technique, the sufficient conditions with respect to the global consensus in finite time is achieved. In addition, the upper bound of the setting time is explicitly evaluated for the global leader-following consensus in finite time. Finally, two …examples are performed to verify the feasibility of the proposed control protocol and the validity of the theoretical results. Show more

Keywords: Fractional multi-agent systems, global finite-time consensus, discontinuous inherent dynamics, fractional Lyapunov functional approach

DOI: 10.3233/JIFS-179529

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-13, 2019

Authors: Elaiw, Ahmed M. | Almalki, Sami E. | Hobiny, A.D.

Article Type: Research Article

Abstract: This paper investigates the global dynamics of Chikungunya virus (CHIKV) infection model with antibody immune response. We incorporate two ways of transmissions CHIKV-to-cell and cell-to-cell. We incorporate three types of discrete time delays into the model. The first time delay is the time between CHIKV entry an uninfected monocyte to become latent infected. The second time delay is the time between CHIKV entry on uninfected monocyte and the production of immature CHIKV. The third time delay represents the CHIKV’s maturation time. Nonnegativity and boundedness properties of the solutions are proven. Further, global stability of the equilibria is established by constructing …Lyapunov functions and by applying applying LaSalle’s invariance principle. Show more

Keywords: Chikungunya infection, global stability, Lyapunov function, time delay, latency, cell-to-cell transmission

DOI: 10.3233/JIFS-179531

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-9, 2019

Authors: Chen, Kelvin H.-C. | Wei, Hui-Chuan | Li, Ai-Tzu | Wang, Wei-Ni | Liao, Yu-Hsien

Article Type: Research Article

Abstract: By considering the supreme-utilities among fuzzy action vectors, we adopt several sensible inequality constraints to propose a different generalization of the core on multicriteria fuzzy transferable-utility (TU) games. We also adopt the duality results of linear programming theory to analyze the non-emptiness for this extended core under inequality constraints. Further, we define an extended reduction to characterize this extended core. Based on the notion of domination among fuzzy payoff vectors, some coincidences are investigated.

Keywords: Multicriteria fuzzy TU games, the core, supreme-utilities, inequality constraint, domination

DOI: 10.3233/JIFS-18811

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-8, 2019

Authors: Yang, Hanbiao | Zeng, Dongcheng

Article Type: Research Article

Abstract:  In this paper, for a non-degenerate convex set Y in R n containing 0 , two special function spaces S 0  (Y ) and E 0  (Y ) which consist of all fuzzy star-shaped numbers and of all fuzzy numbers in R n with respect to 0 and their supports being included in Y with the endograph metric D are investigated. Some conclusions and methods in topology are used to discuss the topological structure of (S 0  (Y ) , D ) and the pair ((S 0  (Y ) , …D ) , (E 0  (Y ) , D )). The main results are as follows: 1. The space (S 0  (Y ) , D ) is homeomorphic to the Hilbert cube Q  = [-1, 1] N if and only if S 0  (Y ) is compact if and only if Y is compact. 2. There exists a homeomorphism h  : (S 0  (Y ) , D ) → Q such that h  (E 0  (Y )) = {1} × [-1, 1] N \{1} if Y is compact but not a segment. 3. The space (S 0  (Y ) , D ) homeomorphic to the pseudoboundary of the Hilbert cube if and only if S 0  (Y ) is non-compact and σ -compact if and only if Y is non-compact and locally compact. Show more

Keywords: Fuzzy star-shaped numbers, fuzzy numbers, the endograph metric, the Hilbert cube, the pseudoboundary of the Hilbert cube

DOI: 10.3233/JIFS-190272

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-10, 2019

Authors: Pereira, Javier | de Oliveira, Elaine C.B. | Morais, Danielle C. | Costa, Ana Paula C.S. | Arroyo-López, Pilar

Article Type: Research Article

Abstract: ELECTRE TRI, a family of multi-criteria methods used to sort alternatives into preference-ordered categories, defines an outranking function to measure the membership degree of an alternative to a category, whenever imprecise evaluations are available. Recent extensions use Hesitant Fuzzy Sets (HFS) to consider uncertain evaluations. However, deterministic parameters are considered, which avoids the application to cases in which non-fuzzy scores and unstable parameters are available. In this study, an approach is proposed for: 1) modeling hesitant outranking functions originated from unstable parameters provided by several DMs; 2) using the HFS to calculate the ELECTRE TRI-C indices; 3) reducing the DMs …cognitive effort when they are asked to provide information. An application to supplier development is presented by using ELECTRE TRI-C. Results are compared by using different HFS aggregation operators and sensitivity analysis shows that a robust conclusion can be obtained. Future lines of research are also suggested. Show more

Keywords: ELECTRE TRI-C, hesitant fuzzy sets, sensitivity analysis, supplier development

DOI: 10.3233/JIFS-190166

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-11, 2019

Authors: Li, Yongkun | Wang, Chun

Article Type: Research Article

Abstract:  In this paper, we consider a class of quaternion-valued inertial neural networks with time-varying delays. First, by applying a continuation theorem of coincidence degree theory, we establish the existence of anti-periodic solutions of the considered neural networks. Second, by choosing a proper variable substitution, we transform the neural networks into a system of first order differential equations, and by constructing a suitable Lyapunov function, we derive a set of sufficient conditions ensuring the global exponential stability of the system. Finally, we give two examples to illustrate the effectiveness of our results.

Keywords: Quaternion-valued inertial neural networks, anti-periodic solutions, coincidence degree, exponential stability

DOI: 10.3233/JIFS-182731

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-17, 2019

Authors: Pandey, Prateek | Litoriya, Ratnesh

Article Type: Research Article

Abstract: Irrespective of the nature of the software, the choice of a software development process plays a crucial role. A good choice may help expand the business to heights while a bad choice may wreak havoc for the stakeholders. Therefore, selecting the right software development process is an indispensable element during project planning. Undoubtedly, web-based applications differ from conventional software and are becoming so popular in society due to their distinguishing features and widespread coverage. Web application software is generally found fit candidates to be developed according to agile software processes. This article attempts to provide a model for advising an …agile software process during the planning phase of a web application development project. The proposed model takes into account the underlying web project characteristics and uses the Fuzzy Analytic Hierarchy Process (FAHP) along with TOPSIS techniques for suitable agile candidate selection. The model is also validated on a primary dataset obtained by developing twenty web application projects through four student teams. The results show that the proposed model is successful in suggesting a correct agile process with a probability of the order of 0.8. Show more

Keywords: Agile process, fuzzy AHP, TOPSIS, web application, identification model

DOI: 10.3233/JIFS-190508

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-12, 2019

Authors: Yang, Eunsuk

Article Type: Research Article

Abstract:  This paper investigates standard completeness for substructural fuzzy logics based on mianorms with n -contraction and n -mingle axioms. For this, first, right and left n -contractive and n -mingle logic systems based on mianorms , their corresponding algebraic structures, and their algebraic completeness results are discussed. Next, completeness with respect to algebras whose lattice reduct is [0, 1], known as standard completeness , is established for these systems via Yang’s construction in the style of Jenei–Montagna. Finally, further standard completeness results are introduced for their fixpointed involutive extensions.

Keywords: Mianorms, substructural logic, fuzzy logic, semilinear logic, mianorm-based logic

DOI: 10.3233/JIFS-190150

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-13, 2019

Authors: Boulaaras, Salah

Article Type: Research Article

Abstract:  In this paper, some new existence results of elliptic equation of Kirchhoff-type with changing sign data and logarithmic source terms are proved, by using three different methods: direct variational method, Galerkin approach and sub-super solutions method. Our study is natural extensions from the previous recent works in [2–19, 24, 38 ], where the authors have already studied the existence of positive solutions for some classes of Laplacian elliptic problems by using one classical method for a certain class of elliptic equations.

Keywords: Kirchhoff, existence, sub-supersolution, galerkin approach, elliptic equation

DOI: 10.3233/JIFS-190885

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-10, 2019

Authors: Samanlioglu, Funda | Ayağ, Zeki

Article Type: Research Article

Abstract: In this study, an intelligent approach is presented for the evaluation and selection of innovation projects. Selecting the best innovation project is a complicated multiple criteria decision making (MCDM) problem with several potentially competing quantitative and qualitative criteria. In this paper, two hesitant fuzzy MCDM methods; hesitant fuzzy Analytic Hierarchy Process (hesitant F-AHP) and hesitant fuzzy VIsekriterijumska optimizacija i KOmpromisno Resenje (hesitant F-VIKOR) are integrated to evaluate and rank innovation projects. In the hesitant fuzzy AHP-VIKOR, hesitant F-AHP is used to find fuzzy evaluation criteria weights and hesitant F-VIKOR is implemented to rank innovation project alternatives. A numerical example is …given where five innovation projects are evaluated based on nine criteria by three decision makers. Show more

Keywords: Innovation project selection, fuzzy, multiple-criteria decision making, AHP, VIKOR

DOI: 10.3233/JIFS-179458

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-11, 2019

Authors: Kutlu Gündoğdu, Fatma

Article Type: Research Article

Abstract:  The three dimensional extensions of ordinary fuzzy sets such as intuitionistic fuzzy sets (IFS), Pythagorean fuzzy sets (PFS), and neutrosophic sets (NS) aim at collecting experts’ judgments based on membership, non-membership and hesitancy degrees. Generalized three-dimensional spherical fuzzy sets have been introduced to the literature, including their arithmetic operations, aggregation operators, and defuzzfication operations. Expansion of classical Multi-Objective Optimization by a Ratio Analysis plus the Full Multiplicative Form (MULTIMOORA) has been performed by using ordinary fuzzy, hesitant fuzzy, intuitionistic fuzzy, and neutrosophic sets in the literature. I aim at developing the spherical fuzzy MULTIMOORA method since the spherical fuzzy point …of view can contribute to this multicriteria decision environment. By using spherical fuzzy sets (SFS), the MULTIMOORA method can be more efficient for solving complex problems, which require evaluation and estimation under unreliable data environment. The validation of the proposed approach is shown through an illustrative example. Additionally, comparative analyses with neutrosophic MULTIMOORA and intuitionistic fuzzy TOPSIS methods are presented. Show more

Keywords: Spherical fuzzy sets, multicriteria decision making, MULTIMOORA, personnel selection, TOPSIS

DOI: 10.3233/JIFS-179462

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-16, 2019

Authors: Zhang, Shuo | Zhao, Xuan | Lei, Wubin | Yu, Qiang | Wang, Yibo

Article Type: Research Article

Abstract: On account of the limitations of single sensor in obstacle detection, the paper investigates an obstacle detection method based on the fusion of 3D LiDAR and monocular visual. The spatial data fusion of the two sensors is realized according to their calibration results, and the time data fusion is realized by using double buffer technology. Considering the aspect ratio of vehicles, the image region of interest is determined based on the obstacle clustering of 3D LiDAR data. By using Haar-like features as effective characteristic of the front vehicle, integral figure is applied to extract Haar-like features of vehicle samples and …non-vehicle samples. AdaBoost algorithm is used to choose weak classifiers to constitute strong classifiers, which combine into the cascade classifier. The cascade classifier has been trained to identify the vehicle target in the image region of interest. The relevant experimental results verify the effectiveness and real-time performance of the detection method. Show more

Keywords: Obstacle detection, multi-sensor fusion, vehicle identification, AdaBoost algorithm

DOI: 10.3233/JIFS-179412

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-13, 2019

Authors: Zare, Tahereh | Jafarpour, Morteza | Çitak, Filiz | Aghabozorgi, Hossien

Article Type: Research Article

Abstract:  In this paper first, we define the notions of left and right soft int-hypergroups and derive some of their basic properties. Second, we study these concepts in the context of complete hypergroups and polygroups. Then, we introduce the notions of left and right soft int-additive hyperrings and soft int-hyperideal. In special case we study these notions for the class of Krasner hyperrings. Finally, a characterization of soft int-hyperideal for the class of Krasner hyperfields is investigated.

Keywords: left(right) soft int-hypergroup, soft int-polygroup, left(right) soft int-additive hyperring, soft int-hyperideal

DOI: 10.3233/JIFS-190791

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-9, 2019

Authors: Naeem, Khalid | Riaz, Muhammad | Afzal, Deeba

Article Type: Research Article

Abstract:  The prevailing structures like intuitionistic fuzzy sets, Pythagorean fuzzy sets and m -polar fuzzy sets etc. have their own deficiencies and limitations. There are many real life situations where multi-polar information is available and these structures fail to work due to their limitations e.g. in medical diagnosis sometimes some tests are repeated time and again to get multiple readings about symptoms to get a better diagnosis of a diseases. The motivation behind this article is to overcome these deficiencies by introducing a novel sort of set entitled Pythagorean m -polar fuzzy set (Pm FS) as hybrid structure of Pythagorean fuzzy …set and m -polar fuzzy set, m being some cardinal number. For m  = 1, this set dwindles to Pythagorean fuzzy set and becomes Pythagorean bipolar fuzzy set for m  = 2. We take the advantage to present a number of algebraic operations and some characteristics of Pm FSs. We define some linguistic terms using the notion of product of Pm FSs (⊗) by assigning different numeric values to the constant k  ∈ [0, ∞ [ and present an illustration to determine the values of membership and non-membership functions of Pm FSs for lower, middle and upper class regarding economic position. We render an application of Pm FSs in decision making problem (DMP) of selection of most appropriate mode of advertisement using the well-known tool TOPSIS. Show more

Keywords: Pythagorean m-polar fuzzy set, algebraic operations on PmFSs, α- & (α, β)-cut, decision making, TOPSIS

DOI: 10.3233/JIFS-191087

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-18, 2019

Authors: Zhao, Youen | Ji, Xiuhua | Liu, Zhaoguang

Article Type: Research Article

Abstract: Blind image quality assessment (BIQA) aims to evaluate the quality of an image without information regarding its reference image. In this paper, we proposed a novel BIQA method, which combines thirty six natural scene statistics (NSS) features, two color statistics features and four perceptual features to construct an image quality assessment model. Support Vector Regression (SVR) is adopted to build the relationship between these features and image quality scores, yielding a measure of image quality. Experimental results in LIVE, TID2013 databases and their cross validations show that the proposed method records a higher correlations with human subjective judgments of visual …quality and delivers highly competitive performance with state-of-the-art BIQA models. Show more

Keywords: Blind image quality assessment, natural scene statistics feature, perceptual feature, color statistics feature, support vector regression

DOI: 10.3233/JIFS-190998

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-12, 2019

Authors: Zhu, Ye | Shen, Xuanjing | Liu, Yi

Article Type: Research Article

Abstract: To abandon the use of overlapping block division and resist the tampering factor of illumination change, a novel copy-move forgery detection method is proposed based on Maximally Stable Extremal Regions (MSERs) and the Local Intensity Order Pattern (LIOP), that integrates block-based and keypoints-based methods. The method involves the following steps: first, affine transformation invariant MSERs are used to maintain the geometrical transformation invariance and reduce computational complexity; second, LIOP features are used to describe the texture and resist illumination change; and finally, RANdom SAmple Consensus is applied to remove false matches. The experiments indicate that the proposed method has great …performance for scaling, rotation and illumination changes. Moreover, the method has the high robustness to Gaussian noise, Gaussian blur and JPEG compression. Show more

Keywords: Image forensics, copy-move forgery detection, maximally stable extremal regions, local intensity order pattern

DOI: 10.3233/JIFS-182647

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-8, 2019

Authors: Tao, Ning | Tao, Gou | Peng, Zhang

Article Type: Research Article

Abstract: Focus on the distribution vehicle scheduling problem under travel time delay, a series of rescue modes generalized from practical vehicle planner’ experiences were presented. The measurement method of value function based on prospect theory and the disruption management strategy of customer’s psychological perception are put forward in this paper. A multi-objective optimization model for disruption management of logistics distribution is established through multi-objective programming at first. Next, the idea of gradual optimization for the target to obtain the terminal logistics distribution adjustment scheme with minimum disturbance is introduced. Acting the customer’s psychological perception time as the reference point, the degree …of the customer’s psychological perception of the expected time of goods is measured with the prospect theory. In order to optimize the disruption management model and search the optimum solution of multi-objective optimization problem, an improved quantum bacterial foraging algorithm is proposed. The effectiveness and practicability of the proposed method is verified through the comparison and analysis with rescheduling method. Show more

Keywords: Travel time delay, terminal logistics, disruption management, psychological perception, prospect theory

DOI: 10.3233/JIFS-190916

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-9, 2019

Authors: Perveen P.A., Fathima | Sunil, Jacob John | Babitha, K.V. | Garg, Harish

Article Type: Research Article

Abstract:  In this paper, the definition of spherical fuzzy soft sets and some of its properties are introduced. Spherical fuzzy soft sets are a generalization of soft sets. Notably, we showed DeMorgan’s laws that are valid in spherical fuzzy soft set theory. Also, we propose an algorithm to solve the decision-making problem based on adjustable soft discernibility matrix. It gives an order relation between all the objects of our universe. Finally, an illustrative example is discussed to prove that they can be effectively used to solve problems with uncertainties.

Keywords: Soft sets, spherical fuzzy sets, spherical fuzzy soft sets, soft discernibility matrix, decision-making problem

DOI: 10.3233/JIFS-190728

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-14, 2019

Authors: Vu, Ho | An, Truong Vinh | Van Hoa, Ngo

Article Type: Research Article

Abstract:  In this work, by using the Caputo-Hadamard fractional derivative concept, we propose a new class of fuzzy functional differential equation. In this sense, we establish the existence of the solution, the Ulam-Hyers stability and the Ulam-Hyers-Mittag-Leffler stability for the given problem by means of successive approximation method.

Keywords: Fuzzy-type Caputo-Hadamard fractional derivative, Ulam-Hyers-Mittag-Leffler stability theory, delay fractional fuzzy problems

DOI: 10.3233/JIFS-191025

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-15, 2019

Authors: Wang, Yadong | Shi, Quan | Hu, Qiwei

Article Type: Research Article

Abstract: In order to solve the problem of multi-period material supply in emergency logistics network, a dynamic multi-objective optimization mathematical model with constraints is constructed. The model takes the minimum cost and the maximum fill rate of demands as the objectives, and takes the location of distribution centers and the allocation of material as the decision variables. A dynamic self-adaptive multi-objective differential evolution algorithm is proposed to solve the mathematical model, and the feasible non-dominated solutions of the model are obtained. In the improved algorithm, on the one hand, a new environment change detect operator and a new environment change response …strategy are adopted so that the traditional static optimization algorithm can be used to solve the dynamic optimization problem. On the other hand, the improved algorithm adopts adaptive mutation strategy to improve the ability of global exploration and local exploitation. Case study shows that the improved strategy greatly improves the performance of the algorithm, and can solve the dynamic multi-objective optimization problem effectively. Show more

Keywords: Emergency logistics network, multi objective optimization, dynamic optimization, evolutionary algorithm, self-adaption

DOI: 10.3233/JIFS-191130

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-11, 2019

Authors: Akram, Muhammad | Muhammad, Ghulam | Hussain, Nawab

Article Type: Research Article

Abstract:  The notions of center and distance between two Parametric Bipolar Fuzzy Numbers (PBFNs) by giving the preference of right dominance as compared to the left dominance are presented. The solution of Bipolar Fuzzy System of Linear Equations (BFSLEs) is discussed with polynomial parametric bipolar fuzzy number coefficients matrix having crisp real variables and the right-hand side is polynomial parametric bipolar fuzzy numbers. Some of their related properties are investigated. It is proved that if the real coefficient matrix considered as crisp in an original system, while the unknown variable vectors and Right Hand Side (RHS) column vector functions are treated …as PBFNs, then initially, the general BFSLEs in polynomial parametric form is solved by the addition and subtraction of the vectors of the lower and upper bound, respectively. The solution procedure is computationally efficient in a bipolar fuzzy environment, and our proposed method is simple as well as efficient to handle the BFSLEs. Show more

Keywords: Polynomial PBFNs, center, distance, BFSLEs

DOI: 10.3233/JIFS-190764

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-13, 2019

Authors: Gülle, Esra

Article Type: Research Article

Abstract: In this paper, we study the concepts of Wijsman asymptotically statistical equivalence of order α , Wijsman asymptotically strongly p -Cesàro equivalence of order α and Hausdorff asymptotically statistical equivalence of order α for double set sequences. Also, we research some properties of these concepts and give the inclusion relationships between them.

Keywords: Asymptotic equivalence, statistical convergence, Cesàro summability, order α, Wijsman convergence, Hausdorff convergence, double set sequences

DOI: 10.3233/JIFS-190796

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-7, 2019

Authors: Zhang, Pengyu | Huang, Junchu | Zhou, Zhiheng | Chen, Zengqun | Shang, Junyuan | Niu, Chang | Yang, Zhiwei

Article Type: Research Article

Abstract: Unsupervised domain adaptation (UDA) aims to build a classifier for the unlabeled target domain by transferring knowledge from a well-labeled source domain. Recently deep domain adaptation methods can not effectively integrate discriminability with transferability of features, and these methods can only reduce, but not remove, the cross-domain discrepancy. To this end, this paper proposes a new domain adaptation method called Joint Category-Level and Discriminative Feature Learning Network (CDN). CDN not only achieves domain adaptation by minimizing category-level distribution discrepancy between domains but also learns discriminative feature representations via maximizing inter-category distance and selecting transferability samples simultaneously. Moreover, we develop a …Transferability Weighting Module (TWM), which is based on a constructed classifier, to further strengthen the discriminability of sample’s features. The experimental results demonstrate that CDN can significantly decrease the cross-domain distribution inconsistency and further promote the classification performance. Show more

Keywords: Domain adaptation, deep learning, discriminative feature learning, transfer learning

DOI: 10.3233/JIFS-191136

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-12, 2019

Authors: Dündar, Erdinç | Akın, Nimet Pancaroğlu

Article Type: Research Article

Abstract:  In this paper, we introduce the notions of regularly ( I W 2 , I W ) -convergence, regularly ( I W 2 * , I W * ) -convergence, regularly ( I W 2 , I W ) -Cauchy and regularly ( I W 2 * , I W * ) -Cauchy double sequence of sets and investigate the relationship among them.

Keywords: Regularly ideal convergence, double sequence of sets, Wijsman convergence

DOI: 10.3233/JIFS-190626

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-8, 2019

Authors: Yavuz, Enes

Article Type: Research Article

Abstract:  We introduce semicontinuous summation methods for series of fuzzy numbers and give Tauberian conditions under which summation of a series of fuzzy numbers via generalized Dirichlet series and via generalized factorial series implies its convergence. Besides, we define the concept of level Fourier series of fuzzy valued functions and obtain results concerning the summation of level Fourier series.

Keywords: series of fuzzy numbers, Tauberian theorems, fuzzy Fourier series, 03E72, 40A05, 40E05

DOI: 10.3233/JIFS-190632

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-8, 2019

Authors: Naga Muneiah, Janapati | Subba Rao, Ch D. V.

Article Type: Research Article

Abstract: Telecom sector is hugely losing profits in different degrees due to various undesired classes of its customers. Churners, a certain class of customers shifting to the competitors, are the most undesired class of customers who are the predominant reason for the losses. Still, there are other classes of customers in this business who stay with the enterprise, but they are inactive in using the services and leading to uncertainty and an insignificant amount of profits. When data mining techniques are applied to such applications they produce customer models in the form of decision trees, etc. and provide customer’s class label …only such as churner/non-churner. Furthermore, they only focus on improving the technical interestingness measures of prediction models. Thus, very limited research has been carried out on turning the prediction results into useful decision making actions. Consequently, some manual work by domain expert has to be done to postprocess the model to obtain the actionable knowledge for changing the customer from undesired class to the desired one. However, some of the existing works are suggesting the actions to convert the class of the customer from one category to another, but they have limitations in that they do not generalize to more than two classes. In this paper, a novel algorithm, which aptly fits the multi-class setting of Telecom sector, is presented that suggest actions to change the customer from an undesired class to a desirable one with maximum net profit. We explain our proposed method with the help of a case study of the Telecom sector. Empirical tests are conducted on the case study problem and also on UCI benchmark data and shown that our method is effective and scalable. With the help of comparison with state-of-the-art methods and substantial experiments, we demonstrate the efficiency of the proposed method. Show more

Keywords: Data mining, probability estimation decision trees, actionable knowledge discovery, decision making, profit maximization, Telecom sector

DOI: 10.3233/JIFS-190628

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-31, 2019

Authors: Khan, Izaz Ullah | Karam, Fazal Wahab

Article Type: Research Article

Abstract: The study presents Proposed Data Envelopment Analysis (DEA) approaches for intelligent business analytics of the US Airline industry to gain more knowledge, control, flexibility and trade-off among various inputs to the system/industry. Three new proposed DEA models are presented. The results obtained provide credible data analytics and intelligent business suggestions. Firstly the proposed input oriented and the proposed output oriented DEA models are formulated. The proposed input oriented DEA model suggests how resource utilization can be minimized while operating in with the same output level. Further, the proposed output oriented model suggests how output efficiency can be increased to a …benchmark level while keeping the input at the same level. Then the proposed Slack Based DEA model SBM is formulated. The proposed models are then solved with the DEA Excel Solver for finding the efficient points in the Pareto Frontier. Representing the Pareto Frontier as a function of total system revenue gives necessary information about the inputs growth and their trade-off with the output. Furthermore, the proposed Slack Based DEA model (SBM) intelligently measures the technical efficiency of each airline. The results show that three airlines namely American, United and Jet Blue are weakly efficient operating below the proposed SBM efficient frontier. Furthermore, the results intelligently suggest the possible inputs reduction and outputs increases to get to the efficient frontier for the management of the concerned airlines. The proposed SBM slacks suggest the possible areas of improvement for future planning and optimal operating input/output levels for the top management of the weakly efficient airlines. Show more

Keywords: Performance evaluation, date envelopment analysis (DEA), slack based DEA model (SBM), airline industry

DOI: 10.3233/JIFS-190641

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-11, 2019

Authors: Jiang, Bao | Zou, Zezhou | Lio, Waichon | Li, Jian

Article Type: Research Article

Abstract:  Identifying the specific scale status by evaluating scale efficiency of each DMU (decision making unit) is critical for policy makers to make a correct decision on inefficiency improvement. Although some traditional DEA (Data Envelopment Analysis) models can evaluate different scale efficiencies and identify the specific status of each DMU, they are unable to deal with the evaluation indicators with imprecise observation. Therefore, we propose two different uncertain DEA models with imprecise inputs and outputs to recognize two scale status of increasing returns to scale (IRS) and decreasing returns to scale (DRS), which can better help policy makers make a correct …decision on inefficiency improvement without accurate data. Moreover, we analyse the stability of these uncertain DEA models to make effective suggestions for decision makers to further improve the inefficient DMUo or to adjust the inputs and outputs on the premise of remaining the new DMUo efficient. Show more

Keywords: Data envelopment analysis, uncertainty theory, specific scale efficiency identification, stability analysis

DOI: 10.3233/JIFS-190662

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-15, 2019

Authors: Amali, D. Geraldine Bessie | Dinakaran, M.

Article Type: Research Article

Abstract: This paper proposes a new metaheuristic global optimization algorithm inspired by Wildebeest herding behavior called Wildebeest Herd Optimization (WHO) algorithm. WHO algorithm mimics the way nomadic Wildebeest herds search vast areas of grasslands efficiently for regions of high food density. The WHO algorithm models five principal Wildebeest behaviors: firstly Wildebeests have limited eyesight and can only search for food locally, secondly Wildebeests stick to the herd to escape predators, thirdly Wildebeest herd as a whole migrates to regions of high food availability based on historical knowledge of annual grass growth rates and rainfall patterns, fourthly Wildebeests move out of crowded …overgrazed regions and finally Wildebeests move to avoid starvation. The WHO algorithm is compared to Physics inspired, Swarm based, Biologically inspired and Evolution inspired global optimization algorithms on an extended test suite of benchmark optimization problems including rotated, shifted, noisy and high dimensional problems. Extensive simulation results indicate that the WHO algorithm proposed in this paper significantly outperforms state-of-the-art popular metaheuristic optimization algorithms like Particle Swarm Optimization Algorithm (PSO), Genetic Algorithm (GA), Gravitational Search Algorithm (GSA), Artificial Bee Colony Algorithm (ABC) and Simulated Annealing (SA) on shifted, high dimensional and large search range problems. Show more

Keywords: Global optimization, biologically inspired metaheuristic, heuristic optimization, heuristic search algorithm

DOI: 10.3233/JIFS-190495

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-14, 2019

Authors: Akram, Muhammad | Adeel, Arooj

Article Type: Research Article

Abstract:  Hesitant fuzzy sets (HFSs) present a general structure to express the uncertain concepts and data that have been served as in most of the generalizations of fuzzy sets. In this research article, we introduce a novel hybrid model called hesitant m -polar fuzzy sets (Hm F-sets), which is a reasonable combination of HFSs with m -polar fuzzy sets (m F sets). It is the generalization of the concept HFSs, in which the membership degrees of an element of given set deals the m different numeric and fuzzy values that enables to deal the hesitancy of multipolar information. Hesitancy integrates …the conformity for the analysis of given data, and an m F format concedes to severalize the sources of multi-polar information. We highlight and explore some useful properties, construct fundamental operations and investigate comparison laws of Hm F-sets. Moreover, we develop the hesitant m -polar fuzzy TOPSIS approach for multi-criteria group decision-making (MCGDM), which is the natural extension of TOPSIS method and used to rank and choose the best alternative under Hm F positive and negative ideal solutions to this framework. We describe applications of Hm F-sets in group decision-making and apply our proposed method in real life examples to show its efficiency. Finally, we develop an algorithm that implements our decision-making procedure by using computer programming. Show more

Keywords: Hesitant fuzzy set, m-polar fuzzy set, hesitant m-polar fuzzy set, decision-making, TOPSIS

DOI: 10.3233/JIFS-190551

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-20, 2019

Authors: Ye, Tingqing | Ralescu, Dan A. | Jia, Lifen

Article Type: Research Article

Abstract: An Ellsberg urn is filled with n balls of m different colors and each ball is marked in only one color. However, the number of balls of each color is unknown, which should be regarded as uncertain variable. Moreover, since we randomly draw a ball from the urn, Ellsberg urn problems are a mixture of uncertainty and randomness. In order to deal with such problems, we can employ probability theory, uncertainty theory, and chance theory. Until now only the case m  = 3 has been studied. This paper is aimed at studying more general cases where m  > 3. It …is concluded that the chance of drawing a ball of one color is equal to that of drawing a ball of another color. Show more

Keywords: Ellsberg urn, uncertainty theory, chance theory, chance measure

DOI: 10.3233/JIFS-190761

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-7, 2019

Authors: Başhan, Veysi | Ust, Yasin

Article Type: Research Article

Abstract: Supercritical carbon dioxide (s-CO2 ) Brayton power cycle has increasingly attracted attention due to having greater efficiency than conventional power cycles. Thus, s-CO2 systems have begun being tested all around the world, first at the laboratory scale, then as actual medium-capacity systems for ships’ main engines, and finally as large terrestrial power systems. In order to understand system performance during these tests, one must know the causes and effects of the operating regime of the system and its failures. In this context, the study analyzes 15 fundamental problems of power system-related components using the fuzzy Decision-Making Trial and Evaluation …Laboratory (DEMATEL) method. The DEMATEL method allows for identifying and analyzing important errors and/or problems in the s-CO2 Brayton cycle according to the cause-and-effect relationship scheme. Similarly, fuzzy sets are freed from uncertainty in decision-making and from the verbal comments of experts in DEMATEL. When examining the results, fire protection and/or firefighting problems, generator problems, gearbox problems, and radiator problems appear to have high importance in terms of causes. In addition, turbine problems, electrical problems, catalytic combustion-chamber problems, instrumentation, and control-system problems are also important in terms of effects. The study’s obtained results will strongly contribute to the operational safety and prevention of serious high-speed, high-temperature, and high-pressure machinery effects for laboratory-scale, medium-capacity, and actual-terrestrial s-CO2 power systems. Show more

Keywords: Super critic, carbon dioxide, Brayton, fuzzy DEMATEL, faults

DOI: 10.3233/JIFS-191133

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-16, 2019

Authors: Pekkaya, Mehmet | Erol, Figen

Article Type: Research Article

Abstract: The AHP technique application is usually for determining criteria priorities according to respondents, but no statistical query exists for instance, whether the experts’ views significantly change with respect to some characteristics, the criteria priorities significantly differentiate with each other. This research objective is along with determining the priorities of subcriteria in the evaluation of bank failure/bankruptcy risk, to show generating priority series from experts’ views for each criteria for carrying out statistical tests with respect to expert subgroups, and then produce information for researchers/decision makers. The research utilises the usage of conducting statistical hypothesis testing on generated priority series and …CAMELS approach to bank failure. This study investigates and determines the subcriteria priorities of CAMELS dimensions, and uses the data of study Pekkaya & Erol (2016) for statistical tests by generating priority series of CAMELS dimensions. Since no similar academic study, which uses statistical tests and generates priority series in bank failure/bankruptcy literature via similar approach, is observed; this study can be accepted as paving the way of the usage of AHP technique. The obtained priority values of subcriteria with main criteria of CAMELS dimensions can be used to improve the early warning system for bank failure. Show more

Keywords: AHP, bank’s bankruptcy risk, CAMELS, liquidity, asset, capital

DOI: 10.3233/JIFS-190574

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-16, 2019

Authors: Kanwal, Rani Sumaira | Shabir, Muhammad

Article Type: Research Article

Abstract: A soft set handles indeterminate data. By using an equivalence relation, Pawlak introduced the rough set concept for dealing uncertainty to approximate a set. Many authors generalized the concept and used binary relations to approximate a set. A soft set is approximated in this paper by soft binary relations in the context of the aftersets and foresets. Along these lines, we get two sets of soft sets, called the lower approximation and upper approximation with respect to the aftersets and foresets. We applied these concepts on semigroups and approximations of soft subsemigroups, soft left (right) ideals, soft interior ideals and …soft bi-ideals of semigroups are studied. Moreover, for the illustration of the concept, some examples are considered. Show more

Keywords: Soft relations, Soft set approximation, Soft substructures

DOI: 10.3233/JIFS-190328

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-14, 2019

Authors: Xing, Zhongyi

Article Type: Research Article

Abstract: In order to effectively recognize the driving intention triggering on the vehicle safety assistant system, we studied the relationship between the driving intention and driving behavior. Based on hidden Markov model (HMM) hierarchical and sequential characteristics, we established a double layer HMM model, the behavior layer and the intention layer, respectively, used for recognizing driving behavior and driving intention. After using the experimental data processed, we carried out off-line training for each identification model of the double layer HMM model. Moreover, through comparing the offline validation results of different model parameters, we selected the appropriate parameters for each model, which …can achieve the best recognition results. The research results show that the intention layer can identify long and complex driving intentions in real time. It is concluded that this research has successfully built the online recognition model of driver’s intention. Show more

Keywords: Hidden Markov model, driving behavior, driving intention, intention recognition

DOI: 10.3233/JIFS-179524

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-12, 2019

Authors: Qi, Zhanfeng | Zhai, Jingsheng | Qin, Yufeng

Article Type: Research Article

Abstract:  This paper takes the wave glider as the research object. The wave glider is studied comprehensively from the aspects of motion mechanism, motion law and hydrodynamic performance. Firstly, based on the turbulence model of RANS equation, dynamic mesh method, the hydrodynamic performance of two-dimensional tandem hydrofoils is analyzed, which has been developed twice. The paper puts forward the a obstacle avoidance algorithm of wave glider based on fuzzy control. Combining the principle of line-of-sight navigation with the idea of fuzzy control, the path planning of wave glider is carried out. The simulation and experimental results show that the algorithm can …provide real-time and stable motion path of the wave glider, effectively avoid obstacles and safely reach the target point. Show more

Keywords: Wave glider, dynamic analysis, fuzzy control, modelling, obstacle avoidance

DOI: 10.3233/JIFS-179498

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-10, 2019

Authors: Zhou, Qingyuan | Zhang, Zongming | Wang, Yuancong

Article Type: Research Article

Abstract: With the rapid popularization and rapid development of the Internet in the world, e-commerce has gradually become the mainstream trade mode. E-commerce has its own unique trading mode and brand-new global business opportunities. More and more people conduct online transactions through the Internet. According to the characteristics of data in B2C e-commerce system, data mining management module is designed in B2C e-commerce management system. Data mining technology is used to preprocess data, data mining and mining results. It is implemented using J2EE’s B/S architecture. With the continuous growth of B2C e-commerce scale, logistics bottlenecks have become increasingly prominent, and e-commerce …distribution model based on cloud logistics integrates IT information technology with traditional logistics information systems. Integrate logistics service demand and logistics distribution capabilities, and provide corresponding cloud logistics information and management platform system. It will help solve the problem of logistics and distribution of B2C e-commerce in China and promote the healthy and rapid development of e-commerce economy. Show more

Keywords: Data Cube, B2C E-Commerce, Intelligent Logistics

DOI: 10.3233/JIFS-179522

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-8, 2019

Authors: Aslam, Muhammad | Raza, Muhammad Ali | Ahmad, Liaquat

Article Type: Research Article

Abstract: In this paper, a new acceptance-sampling plan has been introduced for the two-stage process for multiple lines under the neutrosophic statistics. The parameters of the proposed sampling plan have been determined by satisfying the given risks using the optimization solution under the neutrosophic statistical interval method (NISM) Using the specific producer’s risk and consumer’s risks, the parameters of the proposed plan have also been determined under neutrosophic operating function (NOF). The comparison based on the sample size of the proposed and the existing plans has been given at different plan parameters. The tables are provided, and an industrial example is …illustrated for the practical use of the proposed sampling plan. From the comparison, it is found that the proposed plan is more efficient, flexible and adequate to be used under uncertainty. Show more

Keywords: Neutrosophic statistic, EWMA, sampling plan, producer’s and consumer’s risks, multistage neutrosophic, average sample number

DOI: 10.3233/JIFS-182849

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-12, 2019

Authors: Chao, Chen | Dawei, Liu | Lijun, Song

Article Type: Research Article

Abstract: In order to solve the problem of effective allocation of spectrum resources and provide an effective spectrum access method for the Internet of Things, a cognitive wireless system based on MCCDMA structure is proposed, and the performance of the system is studied. Two strategies named Underlay and Overlay are proposed and corresponding BER performance are analyzed when the main users are occupying the spectrum. The trend of probability of outage are researched when the number of secondary users are mutative. Theoretical analysis and simulation results show that the cognitive wireless system can use spectrum resources more flexibly and effectively, which …is very suitable for application in IoT systems. Show more

Keywords: Cognitive radio, IoT, MCCDMA, overlay, spectrum hole, underlay

DOI: 10.3233/JIFS-179497

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-9, 2019

Authors: Mahesh, Miriyala | Harigovindan, V.P.

Article Type: Research Article

Abstract:  IEEE 802.11ah defines amendments to IEEE 802.11 to support the Internet of Things (IoT). IEEE 802.11ah implements restricted access window (RAW) mechanism to reduce the contention and energy consumption in dense IoT networks. The RAW mechanism is a group-based MAC protocol that partitions the devices into various groups and confines the channel access of a group of devices to the restricted time interval known as the RAW slot. However, the standard does not specify, grouping mechanism, duration of RAW slots, and the number of RAW slots while configuring the RAW mechanism. In an IoT network, each device has distinct transmission …requirements. Thus, it is necessary to find the optimal number of RAW slots that can maximize the network performance, to group the devices with similar transmission requirements and to assign a RAW slot that adaptively varies with the traffic requirements of the respective group. In this paper, we exploit fuzzy logic to find the optimal number of RAW slots by considering network size, collision probability, and modulation and coding schemes. Further, we propose a traffic-aware adaptive RAW slot allocation (TARA) scheme that uses fuzzy c-means clustering algorithm to group the devices with similar traffic requirements and to assign each group with a RAW slot whose duration adaptively varies with the transmission requirements of the devices. We have also presented a simple yet accurate analytical model to evaluate the performance of the RAW mechanism. Results show that the optimal number of RAW slots found using fuzzy logic significantly enhances the performance of the RAW mechanism in terms of throughput and energy consumption. Further, it is observed that the TARA scheme can effectively meet the traffic requirements of different group of devices when compared to the uniform grouping scheme. Finally, extensive simulations are conducted using ns-3 to validate the analytical results. Show more

Keywords: Internet of Things (IoT), restricted access window (RAW), IEEE 802.11ah, fuzzy logic, Wi-Fi HaLow, fuzzy c-means clustering

DOI: 10.3233/JIFS-182899

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-14, 2019

Authors: Yufeng, Shu | Dali, Zuo | Junhua, Zhang | Junlong, Li | Haoquan, Gan | yu, Chen Tian | Lixing, Luo

Article Type: Research Article

Abstract: Textile defects are not only the key to product quality control, but also play an important role in the textile industry. In this paper, by analyzing and studying the traditional detection methods of textile defects, the defects in the detection are confirmed. In view of how to reduce the deviation caused by environmental factors in the information collection process, as well as the improvement of the class separability between the defect part and the normal area, the introduction of PCA-NLM is proposed. PCA-NLM adopts the principle of combination of texture image enhancement module and automatic defect detection. By enhancing the …texture to achieve the original characteristics of the product itself, PCA-NLM is more excellent in de-noising effect and image acquisition accuracy compared with the same type of texture enhancement method. To improve the separation accuracy and defect recognition and detection ability of defect parts, effectively improve the image collect Ion of the product’s own texture characteristics, at the same time, enhance the effectiveness of defect parts and reduce defect detection defect rate. It has been proved that the ability of seven kinds of defects in textile production is significantly improved compared with the traditional methods. Show more

Keywords: Textiles, defect detection, texture enhancement, class separability

DOI: 10.3233/JIFS-179509

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-8, 2019

Authors: Tang, Ziyan

Article Type: Research Article

Abstract: This paper uses the improved AHP comprehensive evaluation method to evaluate the purchase intention of Chinese retailer private brands. This method can reduce the subjectivity of the weight selection and improve the accuracy of weights. The paper also uses the degree of membership to grade the evaluation levels and conducts the backward evaluation to the different levels of indicators one by one, thus obtaining the relative development level of each indicator. The evaluation results show that consumers have higher acceptance of retailer private brands and they have strong purchase intentions.

Keywords: Fuzzy comprehensive evaluation, intention of retailer private brands, improved AHP method

DOI: 10.3233/JIFS-179521

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-6, 2019

Authors: Mao, Kedun

Article Type: Research Article

Abstract: Patent documents, the paper constructs a patent model tree and establishes a similar patent determination method based on vector space model and patent document features. The paper then proposes to use the patent application number as the association identifier, and associate the ontology and the ontology instance with the existing patent information database, which improves the speed of establishing the ontology and reduces the maintenance and update of the ontology. At the same time, based on the integration of existing workflow management and knowledge flow management, this paper proposes an integration framework with patent knowledge as the core knowledge and …integration link, and describes the nature of knowledge retrieval and the method of importance differentiation. Finally, the paper designs a patent retrieval system, establishes the structural model and functional model of the system and the technical framework of the implementation system. On this basis, the design of the update module of the PMAS system is discussed. Finally, the performance optimization of the PMAS system is designed in detail. Show more

Keywords: Patent management analysis system, workflow, integrated knowledge environment, key technology analysis

DOI: 10.3233/JIFS-179495

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-10, 2019

Authors: Park, Jun Yong | Kim, Dong W. | Kang, Tae-Koo | Lim, Myo Taeg

Article Type: Research Article

Abstract: This paper proposes a biosignal distortion detection algorithm for a driver healthcare system based on a contact biosensor and a linked adaptive neuro-fuzzy inference system (ANFIS), and demonstrate its superiority using actual vehicle experiments. Contact biosensors are highly sensitive to vehicle vibration and turning. Although vehicle suspension contributes significantly to ride quality, vibration transfers to the driver and contact between the driver and biosensor can become unstable when executing a turn, causing the driver’s biosignal to not be measured well. This study estimated the driver’s biosignal state using acceleration, angular velocity, and slip ratio measurements obtained from sensor fusion. When …the measurement exceeded a defined threshold, the driver healthcare system removed unreliable biosignal data. We adopted ANFIS to improve the proposed sensor fusion algorithm estimate accuracy for the driver’s biosignal state and improved the healthcare system robustness to road conditions. The effectiveness of the proposed algorithm was demonstrated experimentally by comparing the system using sensor fusion and linked ANFIS. Show more

Keywords: Linked adaptive neuro fuzzy inference system, biosignal distortion detection, driver healthcare system, sensor fusion

DOI: 10.3233/JIFS-182532

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-11, 2019

Authors: Liu, Qingjie | Wang, Xiaoying | Pan, Zhian

Article Type: Research Article

Abstract: In view of the large data volume and complex structure of big data in the operation of major systems, the traditional cloud computing distributed multi-layer architecture data retrieval method has been difficult to meet the needs of big data retrieval. Therefore, related research must be centered around the structure of complex big data is unfolded, especially unstructured big data, to shape a new data cluster infrastructure. The cluster environment needs to implement stable retrieval of unstructured data through a cloud-centric method. The system introduces an unstructured big data retrieval framework as an unstructured database, as a data retrieval engine to …improve the cloud computing big data non-structure retrieval service, and obtain the key code of unstructured big data under the retrieval technology. Finally, the system is applied to the exsperimental system, and an experimental unstructured big data integration system is built to realize the unified retrieval of large-scale different business functions and business data, so as to satisfy the users to quickly retrieve from a large number of heterogeneous business systems and massive data. Claim. Through search engine technology, the use of text mining, natural language processing, information retrieval and other fields of technology to further improve the precision and recall rate of full-text search. The application of this technology can meet the needs of unified retrieval of large-scale different business data; and at the same time meet the rapid response requirements of large-scale data retrieval requests. The experimental results show that the designed system has high precision and low retrieval time in the process of retrieving unstructured big data under cloud computing, which can realize the stable retrieval of unstructured cloud data. Show more

Keywords: Cloud computing, big data, unstructured stability retrieval, data retrieval engine

DOI: 10.3233/JIFS-179496

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-9, 2019

Authors: Bhatt, Priyang | Thakker, Bhasker

Article Type: Research Article

Abstract: In an Internet of Things (IoT) environment, any object, which is equipped with sensor node and other electronic devices can involve in the communication over wireless network. Hence, this environment is highly vulnerable to botnet attack. Nevertheless, the challenge prevailed in detection of botnet attack due to its unique structurally repetitive nature, performing dissimilar activities that are non-linear, and an invisible nature by deleting the history. Even though existing mechanisms have taken action against the botnet attack proactively, it failed to capture the frequent abnormal activities of botnet attackers due to frequent monitoring. Moreover, when the number of devices in …the IoT environment has increased, existing mechanisms has missed more number of botnets due to functional complexity. Therefore, to overwhelm the issues in detecting the botnet attack, our work has proposed a Bootstrap Aggregating Surflex-PSIM Classifier. It gathers data from several sensor nodes, which are then preprocessed using Linear Random Euler complex-valued Filter (LRECF). Accordingly, the linearized data is subjected to the training phase comprising of Random Poison Forest (RPF) to predict accurately the botnet creating Distributed Denial of Service (DDoS) and Spam attacks within less time. After being trained, similar botnets are clustered using surflex-PSIM that isolates the botnet attacked clusters based on automatic trained characteristics pocket value. Thus, with the aid our proposed classifier, botnet is detected and isolated with high accuracy at reduced time, thereby ensures system reliability with enhanced system performance. Show more

Keywords: Random Poisson forest, Linear Random Euler complex-valued filter, Psim-protein similarity

DOI: 10.3233/JIFS-190183

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-14, 2019

Authors: He, Yuan | Sun, Xiang | Huang, Ping | Xu, Hong

Article Type: Research Article

Abstract: Plane problem is a typical combinatorial optimization problem. Aiming at the difference method of plane problem, BP neural network is proposed, the algorithm of solving difference equation is established, and the corresponding program is compiled. By calculating the calculation example, the continuity condition under the condition of modulus abruption is further discussed. The correctness and practicability of the difference equation algorithm are verified. A dynamic model of the parallel difference equation is constructed according to the characteristics of the parallel structure of BP neural network. The study shows that the two groups of differential equations are used to identify and …verify the model, and the energy function that satisfies both the linear embedding condition and the correct wiring is given. Furthermore, BP neural network is used to realize the search and routing of the maximum plane subgraph of the planable line and the non-planar plan. The results show that the verification used is effective. Difference equation calculations have the ability to help BP networks get rid of local minima and get better results. Show more

Keywords: BP neural network algorithm, Plane problem, Difference equation

DOI: 10.3233/JIFS-179523

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-10, 2019

Authors: Zeng, Xiang-Tian | Yu, Gao-Feng | Wu, Jian

Article Type: Research Article

Abstract: In this paper, we present a newly developed methodology for solving hybrid multi-attribute decision making (HMADM) problems with multiple types of attribute values (MTAVs) by introducing the satisfaction degrees of alternatives’ closeness to the positive ideal solution for the decision maker (DM) and a compromise-typed variable weight decision method, where the weights of attributes are related to the satisfaction degrees of MTAVs and the DM’s behavior characteristics. An example is presented to show the application of the decision process and a detailed comparison analysis is provided to show the applicability and validity of the method proposed.

Keywords: Multiple attribute decision making, variable weight decision method, prospect theory, multiple types of attribute values

DOI: 10.3233/JIFS-182539

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-10, 2019

Authors: Bordbar, Hashem | Song, Seok-Zun | Bordbar, Mohammad Rahim | Jun, Young Bae | (To the memory of Professor Lotfi A. Zadeh)

Article Type: Research Article

Abstract:  In the paper [P.K. Maji, R. Biswas, A.R. Roy, Fuzzy soft sets, J. Fuzzy Math. 9 (3) (2001) 589–602], Maji et al. introduced the concept of fuzzy soft sets as a generalization of the standard soft sets, and presented an application of fuzzy soft sets in a decision making problem. The aim of this paper is to apply fuzzy soft set for dealing with several kinds of theories in hyper BCK -algebras. The notions of fuzzy soft hyper BCK -ideal, fuzzy soft weak hyper BCK -ideal, fuzzy soft s -weak hyper BCK -ideal and fuzzy soft strong hyper BCK -ideal …are introduced, and related properties and relations are investigated. Show more

Keywords: fuzzy soft hyper BCK-ideal,, fuzzy soft weak hyper BCK-ideal,, fuzzy soft s-weak hyper BCK-ideal,, fuzzy soft strong hyper BCK-ideal, 06F35, 03G25, 06D72

DOI: 10.3233/JIFS-190103

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-9, 2019

Authors: Gu, Musong | Du, Xiaodan | Fan, Wenjie | Han, Qiyi | He, Zishu | You, Lei

Article Type: Research Article

Abstract:  In emergency, it is very important to make a real-time and precise positioning of emergency address. As a large amount of emergencies take place in mountainous region, river valley and high building, original node location based on plane does not apply any more, thus, in order to improve precision of early warning and location of disaster, we have proposed a 3D-DVHop localization algorithm, and compare it with the typical 3-D location algorithm APIS. Through the simulation experiment, the localization error of the improved 3D-DVHop algorithm is far less than that of APIS algorithm, which improves the localization accuracy greatly under …unexpected circumstances and laying a solid foundation for the following decision-making and rescuing work. Show more

Keywords: Geological disaster warning, 3D-DVHop algorithm, localization problem, wireless sensor network

DOI: 10.3233/JIFS-179494

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-8, 2019

Authors: Dai, Songsong | Cheng, Wentao

Article Type: Research Article

Abstract:  This paper introduces noncommutative symmetric difference operators for fuzzy logics. Structures and properties of these operators are investigated. Finally, pseudo-quasi-metric and pseudo-metric are constructed on [0,1] based on the noncommutative symmetric differences.

Keywords: Noncommutative symmetric difference, t-norm, difference operator, pseudo-quasi-metric

DOI: 10.3233/JIFS-190400

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-9, 2019

Authors: Deng, Xue | Liu, Guandong

Article Type: Research Article

Abstract: Considering the uncertainty of financial market and the investor’s different attitudes towards risk caused by the various goals, in this paper, a portfolio selection problem with background risks and mental accounts constraints is studied to explore their impact on investment decisions. Firstly, we establish a model with normal uncertain variables, and the optimal solutions of portfolio models with and without background risk are compared. Secondly, considering that the investors always divide an account into several sub-accounts, we put forward an uncertain portfolio model combining uncertainty theory and mental account theory. Thirdly, a portfolio model with background risk and mental accounts …is proposed, and the total expected returns of the models in with different proportions of mental accounts are compared. Finally, some numerical applications are provided to validate the model. The result shows that when the levels of tolerance are the same, the expected return of a portfolio with background risk is lower than that without background risk. In addition, the result also shows that when the percent of savings account decreases and that of the consumption account increases, the total expected return increases. Show more

Keywords: Uncertain theory, portfolio selection, background risk, mental account, saving account

DOI: 10.3233/JIFS-190157

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-13, 2019

Authors: Dey, Arindam | Agarwal, Aayush | Dixit, Pranav | Long, Hoang Viet | Werner, Frank | Pal, Tandra | Son, Le Hoang

Article Type: Research Article

Abstract: A genetic algorithm (GA) belongs to the class of evolutionary algorithms and it is one of the most studied heuristic algorithms to solve graph coloring problems. In this paper, we propose a new GA algorithm for the total graph coloring problem. To the best of our knowledge, no algorithm based on a GA exists in the literature for total graph coloring. In the proposed approach, a novel encoding scheme is introduced, where all the edges and vertices of the graph are represented in a chromosome without any repetition. For the initialization of the population, a greedy algorithm is used to …determine the total number of colors required for a total coloring of the graph. The number of colors is used as the fitness value of a chromosome which depends on the sequence of vertices and edges representing the chromosome. We introduce a convergence criteria for GA based on the total coloring conjecture. A two-point crossover and mutation operations, suitable for total coloring, are suggested. The proposed algorithm is applied on some well-known and standard graphs. In our computational tests, graphs are used with a maximum number of 690 vertices and 6650 edges of the graph, respectively. The proposed algorithm determines an optimal solution for 21 graphs among the 27 graphs. The solution of remaining the 6 graphs is near optimal and differs by at most one unit from the optimal value. The results show the effectiveness of the proposed approach. Show more

Keywords: Total coloring, total chromatic number, total coloring conjecture, genetic algorithm, crossover, mutation

DOI: 10.3233/JIFS-182816

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-8, 2019

Authors: Eslami, Mohammad | Shayesteh, Mohammad Reza | Pourahmadi, Majid | Ayatollahitafti, Vahid

Article Type: Research Article

Abstract: Generally, increase in energy demand and consequently unwanted events in a current system will lead to instability. To increase the power system reliability, the current system can be expanded, resulting in a high financial burden. Therefore, one of the most effective options is appropriate controllers usage for stability. In order to overcome the defects of classical controllers such as non-linear, complex uncertain systems, an appropriate mathematical model needs to be designed in limited working conditions. In this paper, a new fractional-order fuzzy proportional-integral-deferential (FOPID) controller is proposed. The proposed controller in its structure is an integral, derivative gain with a …fractional order. This controller is structurally adjustable with two fractional orders, performing the stability process in a short time. On the other hand, in the proposed controller, the optimal adjustment of the controller gain and membership functions has turned into an optimization problem, which is done by a hybrid algorithm based on the virus colony search (VCS) and artificial bee colony (ABC). Local and final search powers in the proposed hybrid algorithm reduce the possibility of local presence dramatically. Simulation results have shown that the proposed controller achieves the higher robustness, the lower fall time, and the lower frequency oscillations compared to the existing controllers. Show more

Keywords: Fractional-order fuzzy controller, intelligent hybrid algorithm, virus serach colony, bee colony, optimization, low frequency oscillation

DOI: 10.3233/JIFS-182918

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-18, 2019

Authors: Lu, Shan | Zhang, Ning | Qiu, Yue

Article Type: Research Article

Abstract:  In the complex financial market, there are situations where the security returns have to be evaluated by experienced experts due to the lack of historical data. In this paper, within the framework of uncertainty theory, we propose a multi-period bi-objective regret minimization model for portfolio selection, in which bankruptcy risk and liquidity risk are both considered. Furthermore, in order to solve the proposed multi-objective optimization problem, a novel hybrid algorithm named MFA-SCA is proposed by combining the advantages of the firefly algorithm (FA) and sine cosine algorithm (SCA). Finally, a numerical example is given to illustrate the effectiveness of the …proposed approaches. Show more

Keywords: Uncertain portfolio selection, Regret factor, Multi-objective optimization, Bankruptcy risk, Firefly algorithm

DOI: 10.3233/JIFS-190936

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-23, 2019

Authors: Afraz, Arash | Rezaeealam, Behrooz | SeyedShenava, SeyedJalal | Doostizadeh, Meysam

Article Type: Research Article

Abstract: Due to the necessity of using distributed generation and storage devices in the operation of power systems and with the advancement of technology and industry in the distribution networks, network operators are trying to transform these systems from passive distribution networks to active ones. To this aim, the present study introduces a novel model to exploit an active distribution network from the cost, operation conditions, and reliability points of view. A shared demand management procedure in the presence of storage devices and price-responsive loads is used to improve operational efficiency, and it is presented using a sensitivity matrix. Probability density …functions (PDFs) are used to model uncertainty in power generated by wind systems and PVs, and the fuzzy membership function is used to improve the voltage profile of the network. To optimize the objective function, given that the problem goals are not of the same kind, the multi-objective genetic algorithm, based on the non-dominated concept, is implemented. Proposed optimal planning and exploiting of the active distribution network based on the shared demand management procedure, not only maximize profit, because of peak shaving, upgrade deferral, power exchange, and loss reduction but also, technical indexes and reliability improvement are obtained due to energy storage systems (ESS) and price-responsive loads simultaneous management. The rationality and effectiveness of the proposed method are verified by the simulation results of a 33-bus active distribution network. Show more

Keywords: Active distribution network, energy storage, non-dominated sorting, shared demand management

DOI: 10.3233/JIFS-190420

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-14, 2019

Authors: Wang, Chang | Sun, Qinyu | Li, Zhen | Zhang, Hongjia | Rui, Fu

Article Type: Research Article

Abstract: The frequent false alarms in Forward Collision Warning systems not only disturb the normal operation of drivers, but also reduce the user acceptance of the warning systems. However, drivers with disparate driving characteristics possess different safety cognition of car-following braking behavior; systems with stationary warning thresholds inevitably lead to higher false positive and false negative rates for aggressive and conservative drivers, respectively. In this study, we proposed an adaptive algorithm that learns the characteristics of individual drivers during car-following braking processes, and determined the optimal threshold online to adapt to different drivers. Signal detection theory was employed and the results …of the accuracy, false negative rate, and false positive rate were used to capture drivers’ characteristics of car-following braking behavior. The optimal warning thresholds were continuously selected online during the learning stage based on changes in the drivers’ characteristics. The developed algorithm by conducting actual vehicle tests with two participants were evaluated. The offline statistical analysis results of the participants’ car-following braking characteristics were compared with the online results of the warning threshold adjustments from the adaptive algorithm. The comparison results indicated that the adaptive algorithm could effectively capture the drivers’ car-following braking characteristics and determine an appropriate warning threshold. Show more

Keywords: Car-following braking, forward collision warning system, self-learning, signal detection theory

DOI: 10.3233/JIFS-179515

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-12, 2019

Authors: Sakho, Seybou | Jianbiao, Zhang | Essaf, Firdaous | Mbyamm Kiki, Mesmin J.

Article Type: Research Article

Abstract: The tamper-proof digital database on which are written all exchanges between its users since its inception is named Blockchain. The blockchain is a system of storage distributed on a peer-to-peer network (p2p) using consensus mechanism, asymmetric encryption, smart contracts and other key technologies. In an untrusted environment, blockchain comes to associate the implementation of a mechanism for the exchange of information, transfer of value intended to ensure consistency, and integrity data is the cornerstone of the creation of value future of the Internet. Blockchain technology has the following features: decentralized, safe, reliable, open and transparent. Its characteristics make the most …attractive blockchain and is the subject of all the debates at the safe level. File storage, healthcare, banking, insurance, field and other scenarios are widely used. However, the technology of the blockchain is still some problems, such as the low flow of transactions, easy disclosure of user information, the confidentiality of the data of transactions and the safe limits of algorithms encryption. His problems that must be resolved urgently in its development and its application. As an emerging technology, the blockchain still has plenty other still undiscovered problems, but it has broad prospects of development and should allow the creation of a new decentralized era and a new world of Central governance without organ of management. Show more

Keywords: Blockchain, blockchain security, Privacy protection issue, Scalability issues, peer-to-peer network technology (P2P), consensus mechanism, smart contract, Merkle tree

DOI: 10.3233/JIFS-190449

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-24, 2019

Authors: Siguang, Dai | Guihua, Nie | Pingfeng, Liu

Article Type: Research Article

Abstract: An optimization algorithm is designed for the solution of the two-way principal-agent model with lower and upper bounds. This work analyzed the two-way principal-agent relationship between the two players who both have dual status: the principal status and the agent status, then proposed the expected utility function for the virtual principal, and a two-way principal-agent model with lower and upper bounds which embodies two players and two-side constraints was established too, then the upper and lower bounds of the parameters are determined by the fixed point theorem, finally Pivoting algorithm and sequence of quadratic programming method were used to solve …those models. The example indicated that it is necessary to balance the investment and return values of the alliance members to maximize the utility of the alliance and achieve real incentive for them by determining the appropriate reserved utility value. Show more

Keywords: Lower and upper bounds, two-way principal-agent model, virtual principal, pivoting algorithm, sequential quadratic programming

DOI: 10.3233/JIFS-179513

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-10, 2019

Authors: Fan, Linyuan

Article Type: Research Article

Abstract: Locally linear embedding (LLE) is a classical nonlinear dimensionality reduction algorithm, and it has been widely used in image feature selection. LLE reduces the dimensions of a data set only by exploring the geometric structure, which is calculated by Euclidean distance and makes the embedding result be sensitive to noise. Moreover, the choice of the number of nearest neighbors is fixed for all data points and only given by human experience. In order to overcome these problems, a geometric parameter adaptive LLE (PALLE) algorithm is proposed in this paper. This algorithm jointly uses Geodesic distance and Cosine similarity to replace …Euclidean distance, and then the number of neighbors is adaptable selected by weak-σ rule. Extensive experimental results over various real-life data sets have demonstrated the superiority of the proposed algorithm in terms of image feature dimensionality reduction compared with classical LLE and other well-known algorithms. Show more

Keywords: Image feature, dimensionality reduction, LLE, parameter adaptive

DOI: 10.3233/JIFS-179520

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-9, 2019

Authors: Li, Wen | Zhuang, Yaming | Ren, Zhiliang

Article Type: Research Article

Abstract: Uncertain information is inevitable in real life due to decision makers’ limited rationality and the complexity of correlative problems. Dual hesitant fuzzy linguistic elements (DHFLEs) can collect all the information from two different viewpoints qualitatively and it has become one of the most effective tools for dealing with uncertain information. In this paper, the main contribution is to propose an extended TODIM method under dual hesitant fuzzy linguistic information and to apply this method to deal with a stock selection problem. Firstly, a new distance measure of DHFLEs is proposed for determining the deviation degree between different DHFLEs. Secondly, in …order to distinguish between different DHFLEs effectively, we construct a novel score function of the DHFLE. The score function and the new distance measure are used to complete the extended TODIM method under dual hesitant fuzzy linguistic information. Finally, to show the validity and the practicability, we use the extended TODIM method to solve a practical problem of stock selection. Show more

Keywords: Multi-criteria decision-making, dual hesitant fuzzy linguistic element (DHFLE), TODIM method, distance measure, score function

DOI: 10.3233/JIFS-190194

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-16, 2019

Authors: Hui, Liu | Xiaojun, Zhang

Article Type: Research Article

Abstract: In view of identification of strong mine quake and rock burst, the mine geology, structural mechanics, mining production data and acoustic emission monitoring process data are infused to build two fuzzy process neural network models based on fuzzy set theory. The model integrates fuzzy logic inference mechanism with process neural network process signal analysis and learning capacity. It presents domain knowledge based on fuzzy set and membership function, and adaptively establishes computational logic and fuzzy decision rules based on process signal distribution features, which can effectively infuse multi-source information and prior knowledge, demonstrating good ability to comprehensively analyze various quantitative …and qualitative mixed information and identify microquake features, as well as small sample modeling capacity. It has good adaptability for predictive analysis of strong mine quake and rock burst with uncertainty. Show more

Keywords: Coal rock mass impact, fuzzy, neural network

DOI: 10.3233/JIFS-179514

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-10, 2019

Authors: Xu, Mo-Li | Xiong, Deping

Article Type: Research Article

Abstract: In view of the current demand for risk identification and classification prevention of bank outlets caused by the difficulty in identifying operational efficiency and wind control capability, a risk data measurement and warning classification model based on information entropy and BP neural network is proposed. The model establishes two-level risk data measurement elements from three dimensions. Based on the data set itself, the information entropy is used to determine the weights of the two-level risk elements, and then calculates the risk quantities recorded under the first-level risk measurement elements in the data set. The BP neural network is used to …output the risk data classification results without presupposing the weights of the measurement. The proposed model obtains smaller reductions and higher classification accuracies with relatively low computational cost. Experiments show that the model can measure and classify risk data with very low mis-judgment rate and small mis-judgment bias. Show more

Keywords: Information Entropy, BP neural network, risk classification

DOI: 10.3233/JIFS-179516

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-8, 2019

Authors: Yu, Kang | Qiang, Wu

Article Type: Research Article

Abstract: In order to better solve the problem of gas outburst prediction, based on the in-depth study of ant colony algorithm, the ant colony clustering algorithm is improved, and the population classification and ant sensory perception characteristics are applied to make the ant colony the most likely to find. The optimal solution effectively avoids the possibility of local optimization, improves the global optimization performance and convergence speed of the algorithm, and reduces the influence of human subjective factors. Based on the prominent basic speech and actual working conditions, the paper selects five indexes of gas velocity, initial gas velocity, gas content, …gas pressure and coal firmness coefficient as clustering attributes, and uses ant colony clustering algorithm to judge outstanding the state of occurrence. The paper uses MATLAB programming language to write a coal and gas outburst prediction program based on improved ant colony clustering algorithm, and predicts a coal mine. The final result is the same as the actual observation. Show more

Keywords: Coal and gas outburst, prediction, ant colony clustering algorithm, K-means algorithm

DOI: 10.3233/JIFS-179501

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-10, 2019

Authors: Changcheng, Xin | Chaohu, He

Article Type: Research Article

Abstract:  The development of this system is based on ASP technology, and through the application of B/S structure and SQL Server database, it provides necessary scientific research data support for the sharing of scientific research information in colleges and universities, and basically realizes the management of personnel files, personnel management and professional title. Management integration of scientific research projects and management of information systems. Develop a research goal of web-based network research management information system. Through this system, it can manage and standardize more scientific research projects. The system is a complete set of college plans, declarations, contracts, Research management information …systems for results, patents, funds, personnel, equipment, etc. The system is based on the B/S mode, perfecting the output system of the report, and providing corresponding data support for the smooth development of scientific research projects, providing a solid material foundation and software hardware for the research and management of scientific research projects. Support, providing an electronic data platform for scientific research and academic exchanges, successfully achieved design tasks and goals. Show more

Keywords: University scientific research patent management, BS mode, ASP technology, SQL server database, information system design

DOI: 10.3233/JIFS-179500

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-10, 2019

Authors: Fang, Weijian | Tan, Xiaoling | Wilbur, Dominic

Article Type: Research Article

Abstract: With the increasingly serious network security situation, intrusion detection technology has become an important means to ensure network security. Therefore, it has become a consensus to introduce the theory and method of machine learning into intrusion detection, and has made good progress in this research field in recent years. In this paper, a machine learning intrusion detection system is proposed. The system uses the intrusion detection of Elman neural network and the intrusion detection of robust SVM neighbour classification to solve the above problems. Elman neural network intrusion detection uses clustering algorithm to cluster the text of the network packet, …which overcomes the defect of missing the text information of the network packet. At the same time, the ability to detect abnormal behaviour between network packet sequences is improved. At the same time, robust SVM neighbour classification intrusion detection can achieve the feature space weighting of the optimal classification face host system log, eliminate the negative impact of noise data, reduce the false alarm rate of intrusion detection, and improve the detection accuracy. Under the requirement of false alarm rate of 0, the intrusion detection based on robust SVM neighbour classification can achieve 87.3% detection rate; when the false alarm rate is 2.8%, the detection rate is 100%. Show more

Keywords: Information security, machine learning method, intrusion detection technology, Elman neural network, robust SVM

DOI: 10.3233/JIFS-179518

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-10, 2019

Authors: Zheng, Leina | Pan, Tiejun | Liu, Jun | Ming, Guo | Zhang, Mengli | Wang, Jun

Article Type: Research Article

Abstract: Quantitative Trading based on Machine Learning can increase the stock exchanging competitive and further enhance stability in the Chinese financial market, while the Risk to income ratio in the A share sector haven’t been studied well enough so far in the Quantitative Trading. The paper study the risk and opportunity in the Chinese share market over the period 2005–2013 under Hidden Markov Model (HMM) system estimator. And then, the quantitative stock selection strategy based on neural network is studied based on multiple factors of the total market value of the constituent stocks in the SSE 50 Index, the OBV energy …wave, the price-earnings ratio, the Bollinger Bands, the KDJ stochastic index, and the RSI indicators. Back testing obtained the conclusion that the Machine Learning strategy is equally valid for Chinese finical market. By analysing the risk of strategic returns, we can also conclude that the Chinese share market is effective in QuantitativeTrading. Show more

Keywords: Machine learning, quantitative trading, hidden markov, neural network

DOI: 10.3233/JIFS-179505

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-11, 2019

Authors: Si, Haiping | Sun, Changxia | Qiao, Hongbo | Li, Yanling

Article Type: Research Article

Abstract: At this stage, with the continuous development of data acquisition technology, the mining of high-dimensional spatial data has become a hot issue. And so on. The spatial data mining component studied in this paper is part of the spatiotemporal data middleware. The main research result is to propose a density-based and grid-based extended adjacent spatial clustering method and apply this method to the space for agricultural informatition. In data mining, we also used the middleware technology to complete the agricultural geographic information system based on MapXtreme, and applied the spatial data mining for agricultural informatization to develop the middleware of …agricultural variety division, which solved the agricultural informatization. The practical application is of our country. Show more

Keywords: Data mining, WebGIS, agricultural informatization, middleware, multidimensional space

DOI: 10.3233/JIFS-179499

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-11, 2019

Authors: Sun, Haiyong | Lei, Hang

Article Type: Research Article

Abstract: A task scheduler plays an important role in Embedded Operating Systems (EOS). In order to ensure the scheduling properties of an EOS, it is important to verify the implementation of its task scheduler. However, the implementation of a task scheduler requires the manipulation of machine registers directly and uses very complex C pointer structures to manage the task related data. Thus, we need a verification system that can formally describe both C pointer programs and embedded code pointers (e.g., update the stack register) naturally. Based on the Verified Software Toolchain and the CompCert ARM assembly syntax and semantics, we utilize …the Coq proof assistant to develop formal reasoning support for the verification of a low-level task scheduler. Our verification system has the capability to verify both C and ARM assembly language; it supports the separation of logical abstractions and specific implementations. More importantly, all the verification can be done in a unified modular verification framework, which minimizes semantic gaps at specification interfaces. Show more

Keywords: Task scheduler, program verification, embedded operating system, formal methods

DOI: 10.3233/JIFS-179502

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-9, 2019

Authors: Tan, Huobin | Tian, Yongfeng | Wang, Linfeng | Lin, Guangyan

Article Type: Research Article

Abstract: The name disambiguation task is designed to solve the name ambiguity problem of documents of multiple persons who have the same name with one another. The task aims to partition all the publications belonging to multiple person with the same name and realize that each decomposed partition is composed of publications of a unique person. Many works on name disambiguation task have a common feature that clustering method is usually used in the last step. The paper presents a complementary study to these works from another point of view. Based on the idea that documents with strong association relationships are …likely to belong to the same author, this paper proposes a method of discovering meta clusters by graph partition with a heuristic rule to improve these clustering-based works. Specially, different from these works, this work uses clustering ensemble method instead of clustering method in the last step. Experimental results on a real-life dataset show that the improved method has satisfactory performance compared with the clustering-based baseline method. Show more

Keywords: Name disambiguation, meta clusters, clustering ensemble, graph partition

DOI: 10.3233/JIFS-179519

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-10, 2019

Authors: Tian, Yiming | Wang, Xitai | Geng, Yanli | Liuand, Zuojun | Chen, Lingling

Article Type: Research Article

Abstract: Sensor-based human activity recognition has a wide range of applications including caring the elderly, helping chronic patients, fitness, etc. As a new kind of single-layer feedforward network, extreme learning machine (ELM) has faster training speed and stronger generalization performance, which provides an effective technique for activity recognition. However, due to the random determination of input weights and hidden deviations, the ELM may converge to a local minimum in some cases. Therefore, in order to overcome the shortcomings of ELM and design a reliable and accurate recognition system, this paper proposes a multi-classifier recognition framework which utilizes extreme learning machines optimized …by quantum-behaved particle swarm optimization (QPSO) as the base classifiers. The quantum-behaved particle swarm optimization was used to select the optimal parameters of base ELMs which are trained on different attribute characteristics. The proposed approach is assessed with two inertial sensor data sets. Comparative experiments with other optimization methods indicated that QPSO-ELM has better accuracy performance for inertial sensor-based human activityrecognition. The experiment showed that the proposed ensemble QPSO-ELM recognition method achieves an accuracy of 96.4% for recognizing six activities. Show more

Keywords: Activity recognition, extreme learning machine (ELM), quantum-behaved particle swarm optimization (QPSO), multi-classifier fusion

DOI: 10.3233/JIFS-179507

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-11, 2019

Authors: Cai, Fangbo | He, Jingsha | Ali Zardari, Zulfiqar | Han, Song

Article Type: Research Article

Abstract: Access control is an important mechanism to protect sensitive information and relational system resources. The traditional access control model (TACM), such as DAC, MAC, RBAC, etc., is no longer suitable for open network due to the lack of dynamic permission management. The increasing network nodes make the information storage and resource access more and more distributed. The traditional access control model has the characteristics of low adaptive ability and single deployment and application mode due to the centralized management mode. Therefore, this access control environment inevitably puts access control pressure on access control authorization. In order to overcome the shortcomings …of traditional access control model, a new access control model named DMPAC (Distributed management of permission for access control model) is proposed in the paper. The authorization mechanism of the model has a distributed and dynamic management access permission, and all nodes covered by the model have the opportunity to participate in the execution of access and control. The model DMPAC provides the benefits of traditional access control models in terms of secure access and dynamic management. We also describe the framework and execution process of the model and the application of DMPAC in access control. At last, we will present some experimental results to show that while maintaining the effectiveness of distributed access control through the management of access permissions, DMPAC can achieve the performance of traditional access control models. Show more

Keywords: Network security, access control, distributed model

DOI: 10.3233/JIFS-179517

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-10, 2019

Authors: Wang, Li | Xie, Yuxin | Xu, Jiping | Zhang, Huiyan | Wang, Xiaoyi | Yu, Jiabin | Sun, Qian | Zhao, Zhiyao

Article Type: Research Article

Abstract: The process of cyanobacteria bloom in rivers and lakes is a highly non-stationary and non-linear process. The existing cyanobacterial bloom prediction method mainly uses time series model and single intelligent model, but time series model and single intelligent model cannot effectively explain the cyanobacterial bloom generation process, and the prediction accuracy is not high. In view of the above deficiencies, this paper proposes to use the cyanobacteria bloom spatiotemporal sequence data for modeling. Considering the characteristics of large-scale nonlinear trend term and small-scale residual term in the cyanobacteria bloom spatial-temporal sequence, the deep belief networks is used to model and …explain the large-scale nonlinear trend term of the cyanobacteria bloom spatiotemporal sequence. Then use the time autocorrelation model and the multivariate spatiotemporal autocorrelation model to model and interpret the small-scale residual term; finally, after superimposing the large-scale nonlinear trend term and the small-scale residual term, the adaptive neuro-fuzzy system model is used to predict the chlorophyll a value of the water. Therefore, a fuzzy spatial and temporal sequence prediction method based on fuzzy expert system is proposed. The model verification results show that compared with the existing time series model and single intelligent model, the method can more fully explain the non-stationary and nonlinear dynamic changes of the cyanobacterial bloom spatial-temporal sequence. It provides a new method for accurately predicting cyanobacteria bloom in rivers and lakes. Show more

Keywords: Cyanobacteria bloom prediction, deep belief networks, fuzzy expert system, spatiotemporal sequence

DOI: 10.3233/JIFS-179512

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-12, 2019

Authors: Yu, Xiaoqing | Zhang, Zenglin | Chai, Rui

Article Type: Research Article

Abstract: To explore wireless sensor network signal transmission characteristics in through-the-earth communication, this paper focused on wireless network signal transmission attenuation by using 433MHz carrier frequency. Sensor nodes electromagnetic wave transmission characteristics were studied under the condition the different receiving node height, horizontal distance between the transmitting node and the receiving node through the wheat field experiments and computer simulation, the relationship between the received signal strength was established, transmission characteristics of field soil information collection sensor nodes in the soil under four wheat stages were put forwarded. The experiment demonstrated that 8 model goodness of fit R2 of effection …of receiving node high and inter-nodes horizontal distance on RSSI(Received Signal Strength Indicator). Besides, three-dimensional surface of RSSI was built in four wheat growing periods, which the fitting model and goodness of fit of RSSI are obtained, and the model verification was conducted through SPASS software. Validation results showed that the model could better predict the received signal strength at different condition through-the-earth communication. The study can provide the technical support for sensor network node deployment and the establishment of the system in soil information acquisition. Show more

Keywords: Wireless sensor networks, experiments, node high, received signal strength, horizontal distance between nodes

DOI: 10.3233/JIFS-179503

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-10, 2019

Authors: Luo, Hongying | Liu, Jun | Li, Xuebin

Article Type: Research Article

Abstract: In this paper, the periodic state of a class of nonlinear hydrodynamic models is studied. This study is applicable to many fields, such as engineering, cybernetics and so on. We use the Runge Kutta algorithm. First, we give a four order nonlinear hydrodynamic model based on the Runge Kutta algorithm. Then, we study the periodic dynamic characteristics of the nonlinear model and establish some new sufficient conditions. The results of our study promote and improve the existing results. And the numerical results are also verified by the numerical experiments. Therefore, the study of this paper has a great help to …master the periodic motion of the fluid. Show more

Keywords: Runge-Kutta algorithm, nonlinear dynamic system, periodic solution, Liapunov function method

DOI: 10.3233/JIFS-179510

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-6, 2019

Authors: Falehi, Ali Darvish | Talavari, Mashallah | Talavari, Abbas

Article Type: Research Article

Abstract: The prominent responsibility of Automatic Generation Control (AGC) is controlling the interchange power flow deviations toward suppression of both the frequency and tie-line power deviation during the disturbance occurrence in the interconnected multi-area power system. To appropriately deliver an electric power with high quality, AGC system needs to be equipped with an efficient and intelligent controller. In this regard, Fractional Order Fuzzy-PID (FOFPID) is proposed for AGC system to enhance the dynamic stability of multi-area interconnected power system. Due to multi-objective nature and importance of the design problem, the parameters of FOFPID controller have been optimally tuned by two multi-objective …optimization algorithms i.e., Multi-Objective Dragonfly Algorithm (MODA) and Non-Dominated Sorting Genetic Algorithm-II (NSGA-II). The damping performance of self-defined FOFPID-AGC has been thoroughly evaluated under different disturbance conditions namely short circuit, load variation and excitation voltage change in the Four-Machine Kundur and Ten-Machine New England. To precisely extract the FOFPID’s parameters, concomitant optimization scheme has been scheduled with consideration of all these disturbances. At last, the damping performance of FOFPID-AGC has been mainly approved by MODA and NSGA-II, and its damping capability has been accordingly validated compared to two defined controllers. Show more

Keywords: FOFPID-AGC, MODA, NSGA-II, dynamic stability, concomitant optimization scheme, multi-area interconnected power system

DOI: 10.3233/JIFS-190228

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-14, 2019

Authors: Zhang, Niankun | Huang, Zhigang | Huang, Peidi | Zhao, Ningshe

Article Type: Research Article

Abstract: In order to master the training state and the characteristics of fighting athletes, it need to obtain a lot of real-time data. By analyzing the characteristics of the test and training process of fighting sports, a defensive and offensive model of sport response test and training is constructed, which is easy to monitor and collect the human fighting sports data, aiming at the special needs for the fast response and data accquisition of sport training. Based on this model, the basic requirements of fast response training and testing system are summed up, and a four-layer architecture design scheme is put …forward by using software engineering technology, which is realized by computer hardware and software technology combined with real-time data acquisition and interface design. Finally, the practical verification is carried out by the application of the system, and the visual expression is given by the graph, and the design and implement can meet the requirement of the task. Show more

Keywords: Data acquisition, fast response, system model, design and implement

DOI: 10.3233/JIFS-179508

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-7, 2019

Authors: Otay, İrem | Jaller, Miguel

Article Type: Research Article

Abstract: This study focuses on the evaluation of disaster risk management and response (DRMR) processes and capabilities using a multi-expert multi-criteria decision making (MCDM) framework. The proposed framework considers four sets of evaluation and performance criteria: risk knowledge and organization, risk reduction, disaster response management, and disaster response support; and 22 sub-criteria such as regulating risk management, financial management, energy, and public safety. To contend with random perception and utility, lack of information and subjectivity in the human (expert) judgment processes that could be present in expert-based models, the authors propose an interval-valued intuitionistic fuzzy sets (IVIFSs) approach. IVIFSs can handle …high levels of uncertainty and define appropriate membership functions. Specifically, the proposed approach incorporates score judgement and possibility degree matrices, and estimates the local and global weights for each assessment criteria. And finally, evaluates the overall performances of the alternatives using intuitionistic fuzzy Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) approach. The authors implemented the framework to the Atlantico State of Colombia, and assessed the disaster risk management and response processes for each for the State’s 23 municipalities. The authors discuss sensitivity analysis that illustrates the robustness of the results. Show more

Keywords: Disaster management, risk management, interval-valued intuitionistic fuzzy sets, MCDM, TOPSIS

DOI: 10.3233/JIFS-179452

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-18, 2019

Authors: Wang, Hailun | Fei, Wu

Article Type: Research Article

Abstract: Compressive sensing retains the substantive characteristics of the original signal based on several sampling values and can realize distortionless reconstruction of signals with high probability. Hence, compressive sensing solves the contradictions among massive sampling data, signal processing speed and hardware equipment in the framework of traditional Shannon’s sampling theorem. In this study, as a means of compressive sensing, a new failure recognition method of rolling bearing based on the characteristic parameters of compressed data and fuzzy-C mean (FCM) clustering is proposed. In this method, kurtosis, variance and waveform factor are used as the characteristic parameters. Using the proposed method, the …sensitive characteristics were extracted by using the compressed information directly, and the eigenvectors of the sample signals were classified and identified through FCM clustering. In the experiment, the proposed method was compared with different compressed matrix methods and the traditional signal acquisition methods under the same axis diameter and different axis diameters. The results demonstrated the improved performance of the proposed method compared to the other methods. Show more

Keywords: Failure recognition, compressive sensing, FCM clustering, characteristic parameters

DOI: 10.3233/JIFS-179511

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-9, 2019

Authors: Pan, Tiejun | Zheng, Leina | Liu, Jun | Guo, Ming | Honghui, Chai | Wang, Jun

Article Type: Research Article

Abstract: At present, the identification of wine is artificial, and it has certain subjectivity. An alternative way that predicting brand based on fusion spectrum combined with Compressive Sampling as a dimensionality reduction technique is proposed in order to achieve the fast, scientific quality evaluation for wine. Successful results have been obtained in the wine identification use Artificial Neural Networks (ANNs) which has the faster speed and precision than typical algorithm. In the end, a multi-spectral information fusion analysis method for wine identification is proposed, which is an efficient solution to the problem of counterfeiting wine.

Keywords: Wine identification, fusion spectrum, compressive sampling, artificial neural network

DOI: 10.3233/JIFS-179506

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-7, 2019

Authors: Liyang, Zheng | Xinling, Zhang

Article Type: Research Article

Abstract: The collection stability of traditional systems is low, it is not easy to delete interference data, the access speed is slow, and the error cannot be effectively detected. For this reason, this paper designs a new automatic filing optimization system of financial management information under the background of information technology development. From four aspects of data dynamic collection, data de-duplication, data access control and RAID error detection scheme improvement, the traditional system is optimized. The financial management information is collected through a data collection method that ensures high efficiency and high stability. In the process of accessing, the semantic ontology …is formed, and the access group in the time domain is classified by the support vector machine method to improve the access speed. The repetitive data model is established, and the deduplication processing is realized by the fractional Fourier transform technique combined with the post-processing result of fourth-order cumulant. The limited set of HDD error detection is reset to help with long-term filing of RAID system data. The result is high filing speed and good filing effect, and the conclusion that the design system is highly practical is obtained. Show more

Keywords: Information technology, financial management information, automatic, filing system, optimization

DOI: 10.3233/JIFS-179504

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-12, 2019