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