Journal of Intelligent & Fuzzy Systems - Volume 37, issue 6

Authors: Jodłowiec, Marcin | Krótkiewicz, Marek | Wojtkiewicz, Krystian

Article Type: Research Article

Abstract:  Knowledge representation is one of the most explored areas in nowadays computer science research. In this paper authors pursue definition and semantics of semantic networks that are defined as part of Semantic Knowledge Base being a hybrid knowledge oriented system. The approach presented in here aims at introducing advanced properties of networks such as cardinality, partitioning or certainty at the same time using simple structure based on two operands and operators. Following paper is an extension of a conference publication that introduced advanced aspects of semantic networks modelling with the use of Association-Oriented Metamodel. The extension includes a discussion related …to the formal description of the structure, as well as the description and use of association-oriented design patterns. Show more

Keywords: Semantic networks, Semantic Knowledge Base, partitioned semantic nets, association design patterns

DOI: 10.3233/JIFS-179353

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 6, pp. 7453-7464, 2019

Authors: Chen, Chun-Hao | Chiang, Bing-Yang | Hong, Tzung-Pei | Wang, Ding-Chau | Lin, Jerry Chun-Wei | Gankhuyag, Munkhjargal

Article Type: Research Article

Abstract: Investment is always an interesting and important issue for people since the international financial crises are hard to predict and the government’s policy may have an influence on economic activities. In the past, many researches have been proposed on portfolio issues. In some of these studies, the group stock portfolio (GSP) is utilized to provide various alternative stocks to an investor. The diverse group stock portfolio (DGSP) optimization approach has then been designed because the diversity of industries within a group can affect the performance of a final GSP. However, these approaches still have some problems to be solved. In …this paper, we propose an algorithm to improve the efficiency and effectiveness of the previous work. In the proposed approach, a new chromosome representation and an enhanced fitness function are applied to find a better DGSP with lower risk than before. Moreover, we design a fuzzy grouping genetic algorithm (FGGA) based on the concept of collective intelligence which utilizes the fuzzy logic to dynamically tune the parameters in the evolution process for finding an appropriate DGSP. A mechanism is also designed to repair non-feasible chromosomes in the population. Through the above improvements, the proposed approach can not only focus on finding the best solution but also speed up the evolution process. Finally, experiments made on real datasets show the merits of the proposed approach. Show more

Keywords: Collective intelligence, diverse group stock portfolio, fuzzy grouping genetic algorithm, grouping problem, individual repair mechanism, portfolio optimization

DOI: 10.3233/JIFS-179354

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 6, pp. 7465-7479, 2019

Authors: Grzonka, Daniel | Kołodziej, Joanna | Jakóbik, Agnieszka

Article Type: Research Article

Abstract: The monitoring of the computational processes in highly distributed environments remains challenging in today’s High Performance Computing. In this paper, we define the agent-based cloud monitoring system for supporting the computational tasks scheduling and resource allocation. The system consists of two types of agents, which may decide about the initialization of the schedule execution and monitor the work of the cloud computational nodes. The decision about running the new scheduling process is based on the expected number of available computational units in the specified time window. The efficiency of the proposed MAS-based model was justified through 40 empirical tests, where …clouds without and within the MAS support were compared. The multiagent system (MAS) effectiveness has been expressed in the average number of floating point operations completed at the cloud resources in one second. The obtained results show the importance of setting the optimal initial time for execution of the new schedule. Our experiments show that for running the new schedule, at least 25% of the computing units in the clouds should be in the idle mode. Also the batches of tasks should not be too large, cause the waiting time for new schedule for execution should be short and not greater than 10% of expected batch execution time. Show more

Keywords: multiagent systems, monitoring, computational cloud, autonomous agent, batch scheduling

DOI: 10.3233/JIFS-179355

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 6, pp. 7481-7492, 2019

Authors: Huk, Maciej

Article Type: Research Article

Abstract: Contextual neural networks are effective and very usable machine learning models being generalization of multilayer perceptron. They allow to solve classification problems with high accuracy while strongly limiting activity of connections between hidden neurons. Within this article we present novel study of properties of contextual neuronal networks with Hard and Exponential Rectifier activation functions and of their influence on behavior of the Generalized Error Backpropagation method. It is used to show how to optimize efficiency of the sorting phase of this algorithm when applied to train evaluated models. This considerably extends our previous related paper which was limited to analysis …of contextual neuronal networks with Leaky Rectifier and Sigmoidal activation functions. This article includes wide description of contextual neural networks and generalized error backpropagation algorithm as well as the discussion of their connection with self-consistency paradigm, which is frequently used in quantum physics. Also the relation of the latter with sorting methods and considered rectifier functions during training of contextual neural networks is studied in details. Conclusions are backed up by the results of performed experiments. Reported outcomes of simulations confirm the ability of contextual neural networks to limit activity of connections between their neurons and – what is more important – indicate the detailed rules of selection of the most efficient sorting algorithm for updating scan-paths of contextual neurons that are using Hard and Exponential Rectifier activation functions. Presented results have considerable value both for research and practical applications – especially where the efficiency of training of contextual neural networks is crucial. Show more

Keywords: Classifiers, self-consistency, aggregation functions, scan-paths

DOI: 10.3233/JIFS-179356

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 6, pp. 7493-7502, 2019

Authors: Nguyen, Binh Thanh

Article Type: Research Article

Abstract: The usefulness and ease of use of Big5 dashboard have been proposed to explore hierarchical structure of personality traits. First, Big5 system architecture and its components are described. Afterwards, we present how to calculate Big5 indicators from available big mobile data sets. Hereafter, Big5 traits can be predicted based on those just-specified indicators. To proof of our concepts, implementation results will be presented in the context of the Big5 dashboard which has been designed and developed to predict Big5 personalities in a representative and interactive manner.

Keywords: Big5 traits, personality, indicators, data warehouse, mobile logs, Naive Bayes classification, dashboard

DOI: 10.3233/JIFS-179357

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 6, pp. 7503-7509, 2019

Authors: Le Thi, Hoai An

Article Type: Research Article

Abstract: This paper deals with a new and efficient collective optimization approach, based on DC (Difference of Convex functions) programming and DCA (DC Algorithm), powerful tools of nonconvex programming. Exploiting the efficiency and the flexibility of DCA we develop the so-called collaborative DCA in which divers DCA based algorithms are cooperated in an effective way. Two versions of collaborative DCA are proposed and their applications on clustering, a fundamental problem in unsupervised learning, are studied. Numerical experiments are performed on several datasets. The comparative results with three DCA component algorithms show that the collaborative DCA outperforms them on quality and it …realizes a good trade-off between the quality of solutions and the running time. Show more

Keywords: Collective optimization, DC programming, DCA, Collaborative DCA, Clustering.

DOI: 10.3233/JIFS-179358

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 6, pp. 7511-7518, 2019

Authors: Li, Honggui | Trocan, Maria

Article Type: Research Article

Abstract: Isometric feature mapping (ISOMAP) is one of the classical methods of nonlinear dimensionality reduction (NLDR) and seeks for low dimensional (LD) structure of high dimensional (HD) data. However, the inverse problem of ISOMAP has never been investigated, which recovers the HD sample from the related LD sample, and its application prospect in data representation, generation, compression and visualization will be very brilliant. Because the inverse problem of ISOMAP is ill-posed and undetermined, the sparsity of HD data is employed to reconstruct the HD data from the corresponding LD data. The theoretical architecture of sparse reconstruction of ISOMAP representation comprises the …original ISOMAP algorithm, learning algorithm of sparse dictionary, general ISOAMAP embedding algorithm and sparse ISOMAP reconstruction algorithm. The sparse ISOMAP reconstruction algorithm is an optimization problem with sparse priors of the HD data, which is resolved by the alternating directions method of multipliers (ADMM). It is uncovered from the experimental results that, in the case of very LD ISOMAP representation, the proposed method outperforms the state-of-the-art methods, such as discrete cosine transformation (DCT) and sparse representation (SR), in the reconstruction performance of signal, image and video data. Show more

Keywords: Isometric feature mapping, inverse problem, sparse priors, sparse reconstruction, alternating directions method of multipliers

DOI: 10.3233/JIFS-179359

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 6, pp. 7519-7536, 2019

Authors: Kurowski, Adam | Mrozik, Katarzyna | Kostek, Bozena | Czyzewski, Andrzej

Article Type: Research Article

Abstract:  In this paper, a methodology for automatic brain activity class identification of EEG (electroencephalographic) signals is presented. EEG signals are gathered from seventeen subjects performing one of the three tasks: resting, watching a music video and playing a simple logic game. The methodology applied consists of several steps, namely: signal acquisition, signal processing utilizing z-score normalization, parametrization and activity classification. The EEG signal is acquired from a headset containing 14 electrodes. For the parametrization two methods are used, namely, Discrete Wavelet Transform (DWT) employed as a reference parametrization technique and autoencoder neural network. Parameters obtained with those methods are fed …to the input of classifiers which assigned them to one of three activity classes. Then, the effectiveness of the assignment of the frames of EEG data into appropriate classes is observed and compared. Results obtained using both methods show differences in accuracy with regard to the task detected depending on factors such as type of parametrization or complexity of the classifier employed for EEG activity classification. Show more

Keywords: EEG signal, discrete wavelet transform (DWT), autoencoder, EEG signal classification

DOI: 10.3233/JIFS-179360

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 6, pp. 7537-7543, 2019

Authors: Koczkodaj, Waldemar W. | Kakiashvili, T. | Li, Feng | Wolny-Dominiak, Alicja | Masiak, Jolanta

Article Type: Research Article

Abstract:  In this study, differential evolution (DE) optimization is proposed for rating scale predictability improvement. An arbitrary assignment of equal values for rating scale items is used as the classifier although domain experts are aware that the contribution of individual items may vary. Most academic examinations are conducted by the use of rating scales. Rating scales are also used in psychiatry (especially for screening). This study demonstrates that the differential evolution is effective for optimizing the predictability of rating scales.

Keywords: Rating scale, DE

DOI: 10.3233/JIFS-179361

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 6, pp. 7545-7553, 2019

Authors: Phuc, Do

Article Type: Research Article

Abstract: Real world data is often interconnected, forming large and complex heterogeneous information networks (HINs) with multiple types of objects and links such as bibliographic network (DBLP) and knowledge bases (YaGo). Querying meta-paths requires exploration of path instances which can be computational cost in large HINs. However, existing meta-path based studies mostly focus on analytical applications of meta-paths, rather than systems to query meta-paths efficiently in large HINs. To bridge this gap, in this work we present SparkHINlog, a system based on Apache Spark, to handle meta-paths queries efficiently on large scale HINs. In SparkHINlog we propose an algorithm to not …only translate meta-paths to Datalog rules, but also to manage the working memory area of Datalog efficiently to increase the scalability of SparkHINlog. To avoid the computing overhead of join operation to discover path instances when evaluating these rules, we leverage Motif Finding, a powerful tool of GraphFrames Library. With motif finding, SparkHINLog can speed up the time to evaluate the rules by path finding on graph instead on joining two relations. We conduct experimental comparisons with SparkDatalog, the state-of-the-art large-scale Datalog system, and verify the efficacy and effectiveness of our system in supporting meta-path queries. Show more

Keywords: Bibliographic network, datalog rules, heterogeneous information networks, meta-path, spark graphframes

DOI: 10.3233/JIFS-179362

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 6, pp. 7555-7566, 2019

Authors: Kisiel-Dorohinicki, Marek

Article Type: Research Article

Abstract: Agent-based metaheuristics computing paradigm (EMAS) has been proposed over 20 years ago by Cetnarowicz. Since then, many efforts were made in order to evaluate, formally analyze and further develop this paradigm towards creating new algorithms as EMAS hybrids, or EMAS-inspired techniques. However, at the same time a significant work has been done in order to build efficient software frameworks supporting this (and similar) computing paradigms. These frameworks were based not only on classic object-oriented programming, but also on functional approach and recently also utilizing heterogeneous infrastructure. This paper presents an overview of the most important findings in this area, including …novel ways of processing the agents and component orientation, which allow for both high flexibility and high efficiency of provided solutions. The discussed concepts are illustrated with a case study of a system solving hard computational problem leveraging GPGPU. Show more

Keywords: parallel and distributed computing, agent-based platform, metaheuristics

DOI: 10.3233/JIFS-179363

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 6, pp. 7567-7578, 2019

Authors: Wikarek, Jarosław | Sitek, Paweł | Bocewicz, Grzegorz

Article Type: Research Article

Abstract: The resource constrained portfolio scheduling problem (RCPoSP), in which orders are grouped in portfolios, is proposed in this study. In the RCPoSP the objective is to deliver all orders in the portfolio at the same time after processing. This problem finds many applications in industrial services, manufacturing companies and, where all items (products, services, items etc.) ordered by the customer have to be delivered at the same time in one lot. The goal is to reduce the delivery costs and/or that all elements of the delivery have the same priority, etc. The presented problem also concerns the scheduling of new …orders in project portfolios and/or a new project portfolio etc. The minimizations of makespan and/or resource needs for the portfolio are also discussed. The authors present a reference model for the RCPoSP and an intelligent framework for modeling and solving the modeled problem based on the original hybrid approach. The opportunity to ask questions, receive answers as well as data representation in the form of facts constitute an invaluable intelligent support to users utilizing this framework. The goal is to provide an intelligent hybrid framework for stating and solving constraint satisfaction or optimization of RCPoSPs. The calculation examples illustrate the capabilities and computational efficiency of the proposed framework. Show more

Keywords: Resource constrained scheduling, constraint satisfaction problem, constraint logic programming, mathematical programming, decision support, group scheduling, fact-based representation, hybrid methods

DOI: 10.3233/JIFS-179364

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 6, pp. 7579-7593, 2019

Authors: López-Fuentes, Francisco de Asís | Ibañez-Ramírez, Juan Alejandro | Chantes Barrios, Abigail

Article Type: Research Article

Abstract: Currently, distributed systems are used to store information in remote sites. However, these systems are exposed to different types of security risks such as virus, Trojans or ramsomware, and security mechanisms are required to protect the access to these data and guarantee their privacy and integrity. Authentication plays an important role for security issues in a computer system. Authentication is used to prove the user identity, and it is strongly related with the access control to limits the actions and operations that an authenticated user can do in a computer system. However, authentication is a previously step to the access …control, and it assumes that authentication of a user has been done successfully. Several cryptography methods can be integrated in an authentication mechanism in order to obtain robust authentication schemes. An authentication scheme based on Kerberos to access data in multiples domains is presented in this paper. A challenge in our authentication scheme is related with the authentication of Kerberos servers. To deal with this problem a keys distribution architecture is added to authentication scheme in order to authenticate the Kerberos servers in a secure way. Show more

Keywords: Security, authentication, access control, keys distribution, kerberos

DOI: 10.3233/JIFS-179365

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 6, pp. 7595-7606, 2019

Authors: Siemiński, Andrzej | Kopel, Marek

Article Type: Research Article

Abstract: The paper verifies the usefulness of a parallel and adaptive Ant Colony Communities (ACC) for solving the dynamic Travelling Salesman Problem (DTSP). ACC consists of a set of client colonies with a server to coordinate their work. Each one of the client colonies implements a standard ACO algorithm. The paper contains a detailed analysis of the operation of ACO for static TSP in order to identify its most dominant parameters. Graph Generator is used to modify the distances in TSP. In order to catch up with the constant changes the ACC should work in parallel and to adopt to the …current distances. This is accomplished by modifying the number of iterations and changing the size of its internal prospective solutions buffer. Two implementations of ACC are presented: an asynchronous that works on computers connected through a LAN and a synchronous that uses a Hadoop environment. Numerous experiments clearly indicate, that the adaptive, parallel ACC outperforms both standard version of ACO as well as its versions adopted for DTSP. This is especially true for highly dynamic Graph Generators. Show more

Keywords: Dynamic TSP, Ant Colony Community, PACO, immigrant based colonies, ACO parallel implementation

DOI: 10.3233/JIFS-179366

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 6, pp. 7607-7618, 2019

Authors: Tabakov, Martin | Quesada, Joel

Article Type: Research Article

Abstract:  In this research, we succeeded in introducing a new reasoning procedure which applies interval type-2 fuzzy sets into a rule induction process. Our proposal allows information granulation which resulted in achieving good experimental results. We introduced decision tables with elements assumed as interval type-2 fuzzy sets which greatly generalize information. Next, by applying corresponding rule induction procedure, we introduced the possibility to generate directly from a benchmark data fuzzy rulebases for type-2 fuzzy inference models. We strongly believe that our reasoning approach will be a proper solution for different research issues such as classification or ranking procedures as well as …determining knowledge for fuzzy inference models. The method proposed was tested in a classification problem verified by using medical benchmark data. Show more

Keywords: Fuzzy sets, fuzzy reasoning, interval type-2 fuzzy sets, data classification, data discovery, pawlak’s information system, information granulation, rule induction, fuzzy rules

DOI: 10.3233/JIFS-179367

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 6, pp. 7619-7630, 2019

Authors: Nguyen, Ngoc Thang | Phan, Van Thanh | Malara, Zbigniew

Article Type: Research Article

Abstract: In recent decades, the Nonlinear Grey Bernoulli Model “NGBM (1, 1)” has been applied in various fields and achieved positive results. However, its prediction results may be inaccurate in different scenarios. In order to expand the field of application and to improve the predictive quality of the NGBM (1, 1) model, this paper proposes an effective model (named Fourier-NGBM (1, 1)). This model includes two main stages; first, we get the error values based on the actual data and predicted value of NGBM (1, 1). Then, we use a Fourier series to filter out and to select the low-frequency error …values. To test the superior ability of the proposed model, two numerical data sets were used. One is the historical data of annual water consumption in Wuhan from 2005 to 2012 in He et al. ’s paper, and the other is example data from Wang et al. ’s paper. The forecasted results prove that the performance of the Fourier-NGBM (1, 1) model is better than three other forecasting models, namely GM (1, 1), NGBM (1, 1) and the improved Grey Regression model. Furthermore, this study also applied the proposed model to forecast the electricity consumption in Vietnam up to the year 2020. The empirical results can offer valuable insights and provide basic information for model building to develop future policies regarding electrical industry management. In subsequent research, more methodologies can be used to reduce the residual error of the NGBM (1, 1) model, such as Markov chain or different kinds of Fourier functions. Additionally, the proposed model can be applied in different industries with fluctuating data and uncertain information. Show more

Keywords: Fourier series, nonlinear grey Bernoulli model, prediction accuracy, residual error, electricity consumption, Vietnam

DOI: 10.3233/JIFS-179368

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 6, pp. 7631-7641, 2019

Authors: Madeyski, Lech | Kawalerowicz, Marcin

Article Type: Research Article

Abstract: BACKGROUND: Continuous Test-Driven Development (CTDD) is, proposed by the authors, enhancement of the well-established Test-Driven Development (TDD) agile software development and design practice. CTDD combines TDD with continuous testing (CT) that essentially perform background testing. The idea is to eliminate the need to execute tests manually by a TDD-inspired developer. OBJECTIVE: The objective is to compare the efficiency of CTDD vs TDD measured by the red-to-green time (RTG time), i.e., time from the moment when the project is rendered not compiling or any of the tests is failing, up until the moment when the project compiles and all …the tests are passing. We consider the RTG time to be a possible measurement of efficiency because the shorter the RTG time, the quicker the developer is advancing to the next phase of the TDD cycle. METHOD: We perform single case and small-n experiments in industrial settings presenting how our idea of Agile Experimentation materialise in practice. We analyse professional developers in a real-world software development project employing Microsoft.NET. We extend the contribution presented in our earlier paper by: 1) performing additional experimental evaluation of CTDD and thus collecting additional empirical evidence, 2) giving an extended, detailed example how to use and analyse both a single case and small-n experimental designs to evaluate a new practice (CTDD) in industrial settings taking into account natural constraints one may observe (e.g., a limited number of developers available for research purposes) and presenting how to reach more reliable conclusions using effect size measures, especially PEM and PAND which are more appropriate when data are not normally distributed or there is a large variation between or within phases. RESULTS: We observed reduced variance and trimmed means of the RTG time in CTDD in comparison to TDD. Various effect size measures (including ES, d-index, PEM, and PAND) indicate small, albeit non-zero, effect size due to CTDD. CONCLUSIONS: Eliminating the reoccurring manual task of selecting and executing tests and waiting for the results (by embracing CTDD) may slightly improve the development speed, but this small change on a level of a single developer, multiplied by a number of developers, can potentially lead to savings on the company or industry level. Show more

Keywords: empirical software engineering, agile software development, test-driven development, continuous test-driven development, human-centric experimentation, agile experimentation

DOI: 10.3233/JIFS-179369

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 6, pp. 7643-7655, 2019

Authors: Choroś, Kazimierz

Article Type: Research Article

Abstract: The automatic detection of video genre is very desirable and necessary for further analysis of videos mainly when the video processing methods should be parameterized according to the specific video features. It improves first of all the efficiency of temporal segmentation. Temporal segmentation is usually the initial stage for the analysis of edited videos, for such processes as highlights detection, removing of undesirable parts like publicity, as well as selection of play segments in sports videos, etc. Then the temporal aggregation method based on the analysis of shot length and consisting in shot grouping into scenes of a given category …can be applied to significantly reduce processing time. The analyses and the observations of videos confirm that the editions of videos and the video structures significantly depend on the video genre. Many processes can be better performed if the genre of video is known and the methods and their parameters are adequate to the video genre. The paper presents the analyses and tests in the AVI Indexer showing the impact of shot length on the results of temporal segmentation, temporal aggregation, and genre detection of video edited in a standard and typical way for a given video genre. Show more

Keywords: Content-based video indexing, digital video structures, temporal segmentation, video shot categorization, temporal relations, automatic video genre classification, temporal aggregation, shot length analysis, AVI indexer

DOI: 10.3233/JIFS-179370

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 6, pp. 7657-7667, 2019

Authors: Nguyen, Linh Anh | Nguyen, Ngoc-Thanh

Article Type: Research Article

Abstract:  We study the problem of minimizing interpretations in fuzzy description logics (DLs) under the Gödel semantics by using fuzzy bisimulations. The considered logics are fuzzy extensions of the DL 𝒜ℒ𝒞reg (a variant of propositional dynamic logic) with additional features among inverse roles, nominals and the universal role. Given a fuzzy interpretation ℐ and for E being the greatest fuzzy auto-bisimulation of ℐ w.r.t. the considered DL, we define the quotient ℐ/E of ℐ w.r.t. E and prove that it is minimum w.r.t. certain criteria. Namely, ℐ/E is a minimum fuzzy interpretation that validates the same set …of fuzzy terminological axioms in the considered DL as ℐ. Furthermore, if the considered DL allows the universal role, then ℐ/E is a minimum fuzzy interpretation bisimilar to ℐ, as well as a minimum fuzzy interpretation that validates the same set of fuzzy concept assertions in the considered DL as ℐ. Show more

Keywords: fuzzy description logic, fuzzy bisimulation, bisimilarity, Gödel semantics, minimization

DOI: 10.3233/JIFS-179371

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 6, pp. 7669-7678, 2019

Authors: Zgraja, Jakub | Moulton, Richard Hugh | Gama, João | Kasprzak, Andrzej | Woźniak, Michał

Article Type: Research Article

Abstract: Data stream mining seeks to extract useful information from quickly-arriving, infinitely-sized and evolving data streams. Although these challenges have been addressed throughout the literature, none of them can be considered “solved.” We contribute to closing this gap for the task of data stream clustering by proposing two modifications to the well-known ClusTree data stream clustering algorithm: pruning unused branches and detecting concept drift. Our experimental results show the difficulty in tackling these aspects of data stream mining and the sensitivity of stream mining algorithms to parameter values. We conclude that further research is required to better equip stream learners for …the data stream clustering task. Show more

Keywords: Concept drift, data streams, ClusTree , on-line learning

DOI: 10.3233/JIFS-179372

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 6, pp. 7679-7688, 2019

Article Type: Other

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 6, pp. 7689-7689, 2019

Authors: Dastanian, Rezvan | Abiri, Ebrahim | Ghasempour, Mehdi

Article Type: Research Article

Abstract: In this paper a full wave rectifier is presented for RFID passive tags working at 960 MHz frequency. For designing the rectifier multi-stage structure, which has high sensitivity and efficiency, is used for the low amplitude input voltage. In order to eliminate the effect of pass transistors threshold voltage, bootstrap circuit which has cross coupled structure is utilized. For optimizing power conversion efficiency (PCE) and gaining high output voltage from the low input voltage the size of the elements and number of stages are modeled and optimized with neural network and TLBO algorithm, respectively. Due to the achieved results from the …TLBO algorithm 6 stages are considered for the rectifier designing. For the low input voltage 0.6 V, the power conversion efficiency and the output DC voltage are achieved 50.8% and 1.52 V, respectively. The simulation of the proposed rectifier is done with Cadence software in 0.18μ m CMOS technology and its layout equals to 0.00525mm2 . Show more

Keywords: Vth cancellation technique, rectifier, TLBO, PCE

DOI: 10.3233/JIFS-151237

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 6, pp. 7691-7698, 2019

Authors: Samanlioglu, Funda | Ayağ, Zeki

Article Type: Research Article

Abstract: In this study, an intelligent, integrated approach is presented to help educators select the best simulation software package. Selecting the best simulation software package for educational use is a complex multiple criteria decision making (MCDM) problem with several potentially conflicting quantitative and qualitative criteria. In this paper, two fuzzy MCDM methods; fuzzy Analytic Hierarchy Process (F-AHP) and fuzzy VIsekriterijumska optimizacija i KOmpromisno Resenje (F-VIKOR) are integrated to evaluate educational use simulation software package alternatives. In the proposed fuzzy AHP-VIKOR approach, F-AHP is used to determine the fuzzy criteria weights and F-VIKOR is applied to rank simulation software package alternatives with …respect to these criteria. A case study is given where several educational use simulation software packages in Turkey are evaluated and ranked. Show more

Keywords: Simulation software package selection, fuzzy, multiple-criteria decision making, AHP, VIKOR

DOI: 10.3233/JIFS-172290

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 6, pp. 7699-7710, 2019

Authors: Xie, Li-Li | Wu, Xiu-Yun

Article Type: Research Article

Abstract: The basic system of inquisitive semantics (InqB) established by Groenendijk et al. is a general inquisitive semantic theory which doesn’t concern fuzziness. To explain the fuzzy phenomena in natural languages, this paper extends InqB into the framework of M -fuzzifying setting and establishes a basic system of M -fuzzifying inquisitive semantics. To begin with, the notion of M -fuzzifying supporting mapping is defined, where M is a completely distributive lattice with an involution operator and each subset of the universal set of all possible worlds can be regarded as a support of any well-formed formula to some degree. Then …the notions of M -fuzzifying entailment order, M -fuzzifying truth mappings, M -fuzzifying informative content mappings and M -fuzzifying inquisitive content mappings are introduced and their properties are discussed. Further, the degrees of assertiveness, informativeness, inquisitiveness and questioning of a well-formed formula are defined, by which the M -fuzzifying assertive projection operator and the M -fuzzifying questioning projection operator are introduced and characterized. Finally, a necessary and sufficient condition is obtained, where a well-formed formula is exactly the disjunction of its unique M -fuzzifying assertive projection and unique M -fuzzifying questioning projection. Show more

Keywords: M-fuzzifying supporting mapping, M-fuzzifying inquisitive content mapping, M-fuzzifying informative content mapping, M-fuzzifying assertive projection operator, M-fuzzifying questioning projection operator

DOI: 10.3233/JIFS-182500

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 6, pp. 7711-7723, 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. 37, no. 6, pp. 7725-7735, 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. 37, no. 6, pp. 7737-7746, 2019

Authors: Ðurić, Goran | Mitrović, Časlav | Komatina, Nikola | Tadić, Danijela | Vorotović, Goran

Article Type: Research Article

Abstract: Evaluation and analysis of failures which occur in the products or services in different economic areas are an important task of operational management. Solution of this problem leads to the increase of product’s/service’s quality, but in the same time it also increases business processes effectiveness and business goal’s realization. The treated problem is especially important in the information technologies domain. In this paper, the risk factors that may cause failures of the software are defined in compliance with the Failure Mode and Effect Analysis (FMEA) framework and they are assessed during the development and the maintenance phase. The relative importance …of these risk factors and their values at the level of each identified failure are described by pre-defined linguistic terms which are modelled by the interval type-2 trapezoidal fuzzy numbers (IT2TrFNs). The weights vector is calculated by using the Fuzzy Analytic Hierarchy Process (FAHP) with interval type-2 fuzzy sets. The rank of failures is obtained by using the complex proportional assessment (COPRAS) method. The example with real life data is illustrated to demonstrate the potential and applicability of the adopted methods. Show more

Keywords: MCDM, failures, software, FMEA, type-2 trapezoidal fuzzy numbers

DOI: 10.3233/JIFS-182541

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 6, pp. 7747-7759, 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. 37, no. 6, pp. 7761-7768, 2019

Authors: Khan, Shehroz S. | Ahmad, Amir | Mihailidis, Alex

Article Type: Research Article

Abstract:  Presence of missing values in a dataset can adversely affect the performance of a classifier. Single and Multiple Imputation are normally performed to fill in the missing values. In this paper, we present several variants of combining single and multiple imputation with bootstrapping to create ensembles that can model uncertainty and diversity in the data, and that are robust to high missingness in the data. We present three ensemble strategies: bootstrapping on incomplete data followed by (i) single imputation and (ii) multiple imputation, and (iii) multiple imputation ensemble without bootstrapping. We perform an extensive evaluation of the performance of the …these ensemble strategies on eight datasets by varying the missingness ratio. Our results show that bootstrapping followed by multiple imputation using expectation maximization is the most robust method even at high missingness ratio (up to 30%). For small missingness ratio (up to 10%) most of the ensemble methods perform equivalently but better than single imputation. Kappa-error plots suggest that accurate classifiers with reasonable diversity is the reason for this behaviour. A consistent observation in all the datasets suggests that for small missingness (up to 10%), bootstrapping on incomplete data without any imputation produces equivalent results to other ensemble methods. Show more

Keywords: Missingness, ensemble, bagging, multiple imputation, expectation maximization

DOI: 10.3233/JIFS-182656

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 6, pp. 7769-7783, 2019

Authors: Thao, Nguyen Xuan | Ali, Mumtaz | Nhung, Le Thi | Gianey, Hemant Kumar | Smarandache, Florentin

Article Type: Research Article

Abstract: A divergence measure plays an important part in distinguishing two probability distributions and drawing conclusions based on that discrimination. In this paper, we proposed the concept of divergence measure of picture fuzzy sets. We also built some formulas of the proposed divergence measure of picture fuzzy sets anddiscussed some basic properties of this measure.Based on the proposedmeasure, we developed a multi-criteria decision-making algorithm. Finally, we applied the proposed multi-criteria decision-making algorithm in the medical diagnosis problem and the classification problem.

Keywords: Picture fuzzy set, picture fuzzy divergence measure, medical diagnosis, classification problem

DOI: 10.3233/JIFS-182697

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 6, pp. 7785-7796, 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. 37, no. 6, pp. 7797-7813, 2019

Authors: Shoaib, Muhammad | Cheong, Joono | Kim, Younghwan | Cho, Hyeonjoong

Article Type: Research Article

Abstract: We present a novel technique for 3D point cloud simplification — the so-called fractal bubble algorithm — to minimize the computational time and overall storage space. The proposed fractal bubble algorithm generates 2D elastic bubbles and copies of themselves through 2D data sets representing planar geometric contours. Each of the bubbles, as it grows, is made to select a single point of its first contact, and all the selected points become the simplified set of points. The fractal bubble algorithm is repeatedly applied to the simplification of planar slices of general 3D point clouds corresponding to 3D geometric objects, leading …to the global simplification of 3D point clouds. The benefits of the algorithm are: first the algorithm is computationally light and memory efficient, second it is simple to implement and inherently allows the organized selection of the points of contact and finally it enables us to simplify the point cloud data through a multi-scale fashion by varying a set of user-controlled algorithm parameters. Numerical results verify the effectiveness of the proposed algorithm. Show more

Keywords: 3D point cloud, fractal bubble algorithm, data simplification, multi-scale reduction

DOI: 10.3233/JIFS-182742

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 6, pp. 7815-7830, 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. 37, no. 6, pp. 7831-7838, 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 (NSIM) Using the specific producer’s 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. The comparison reveals 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. 37, no. 6, pp. 7839-7850, 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. 37, no. 6, pp. 7851-7864, 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. 37, no. 6, pp. 7865-7882, 2019

Authors: Sirbiladze, Gia | Ghvaberidze, Bezhan | Matsaberidze, Bidzina | Midodashvili, Bidzina

Article Type: Research Article

Abstract: For the facility location problem under extreme environment a two-stage fuzzy approach is developed. On the first stage, the fuzzy multi-attribute group decision making (MAGDM) model for evaluation of the selection ranking index of a candidate service site is created. For this purpose the triangular fuzzy Choquet averaging (TFCA) operator is constructed. Interaction attributes, influencing the service centers’ selection process, are defined. Interaction indexes between attributes and importance values of attributes are taken into account in the construction of the 2-order additive triangular fuzzy valued fuzzy measure (TFVFM). On the second stage, based on the TFCA operator, a new objective …function - selection ranking index of candidate sites is constructed. We consider also two classical objective functions - total cost for opening of service centers and number of agents needed to operate the opened service centers. A new objective function together with latter ones creates the multi-objective fuzzy facility location set covering problem. A Pareto front for this problem is constructed. A simulation example of emergency service facility location planning for a city is considered. The example deals with the problem of planning fire station locations for serving emergency situations in specific demand points – critical infrastructure objects. Show more

Keywords: Multi-objective facility location problem, associated probabilities of a fuzzy measure, fuzzy numbers, choquet integral, multi-attribute group decision making

DOI: 10.3233/JIFS-18723

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 6, pp. 7883-7893, 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. 37, no. 6, pp. 7895-7907, 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. 37, no. 6, pp. 7909-7921, 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. 37, no. 6, pp. 7923-7933, 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. 37, no. 6, pp. 7935-7950, 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. 37, no. 6, pp. 7951-7964, 2019

Authors: Chang, Furong | Zhang, Bofeng | Zhao, Yue | Wu, Songxian | Zou, Guobing | Niu, Sen

Article Type: Research Article

Abstract: A bipartite network is a special kind of complex network that consists of two different types of nodes with edges existing only between the different node types. There are numerous real-world examples of bipartite networks, such as scientific collaboration networks and film-actor networks, among many others. Detecting the community structure of bipartite networks not only contributes to a deeper understanding of their hidden structure, but also lays the foundation for research into the personalized recommendation technology. Most existing algorithms, however, only focus on the detection of non-overlapping community structures while ignoring overlapping community structures. In this study, we developed a …micro-bipartite network model, Bi-EgoNet along with an algorithm called Overlapping Community Detection using Bi-EgoNet (OCDBEN). This algorithm first extracts the sub-bi-community set from each Bi-EgoNet using similarity within the bipartite network and then constructs a global community structure by merging the sub-bi-communities using the double-merger strategy. We evaluated the OCDBEN algorithm with several synthetic and real-world bipartite networks and compared it with existing state-of-the-art algorithms. The experimental results demonstrated that OCDBEN outperformed existing algorithms in both accuracy and effectiveness. Show more

Keywords: Overlapping community, bipartite networks, complex network

DOI: 10.3233/JIFS-190320

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 6, pp. 7965-7976, 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. 37, no. 6, pp. 7977-7989, 2019

Authors: Cheng, Qiang | Wang, Hao | Liu, Zhifeng | Zhang, Caixia | Sun, Dongyang | Qi, Baobao

Article Type: Research Article

Abstract: Reliability allocation is one of the most important factors to consider when determining the reliability and competitiveness of a product. The feasibility-of-objectives (FOO) technique has become the current standard for assessing reliability designs for military mechanical–electrical systems. However, the FOO method has several drawbacks: For instance, it requires that the value of reliability allocation factors is single linguistic variables, and it does not consider the ordered weight of reliability allocation factors, but simply multiplies the ISPE (Complexity (I), State of Art (S), Performance Time (P), and Environment (E)) values one by one. This can lead to erroneous results. To address …these issues, this paper combines the fuzzy allocation method with the maximum entropy ordered weighted averaging method (ME-OWA) to achieve a flexible allocation of system reliability. To verify the effectiveness of the proposed method, the CNC machine tool is taken as an example. The FOO method and the fuzzy allocation method and the proposed method were used to assign reliability to the eight subsystems of a CNC machine tool, and the results were compared to draw conclusions: The proposed method is more flexible and accurate for reliability allocation. Show more

Keywords: Reliability allocation, feasibility-of-objectives technique (FOO), the maximum entropy ordered weighted averaging method (ME-OWA), CNC machine tools

DOI: 10.3233/JIFS-190376

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 6, pp. 7991-8004, 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. 37, no. 6, pp. 8005-8013, 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. 37, no. 6, pp. 8015-8028, 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. 37, no. 6, pp. 8029-8052, 2019

Authors: Zhou, Xiao-Wu | Shi, Fu-Gui

Article Type: Research Article

Abstract: In this paper, some low-level separation axioms of L -convex spaces are introduced, including S -1 , sub-S 0 , S 0 , S 1 and S 2 separation axioms. Some relevant properties of these separation axioms are discussed. In particular, the relationships between convex spaces and induced L -convex spaces on some separation axioms are investigated.

Keywords: L-convex space; S-1; sub-S0; S0; S1; S2

DOI: 10.3233/JIFS-190471

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 6, pp. 8053-8062, 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, Wildebeest Herd Optimization Algorithm, biologically inspired metaheuristic, heuristic optimization, heuristic search algorithm

DOI: 10.3233/JIFS-190495

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 6, pp. 8063-8076, 2019