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The purpose of the Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology is to foster advancements of knowledge and help disseminate results concerning recent applications and case studies in the areas of fuzzy logic, intelligent systems, and web-based applications among working professionals and professionals in education and research, covering a broad cross-section of technical disciplines.
The journal will publish original articles on current and potential applications, case studies, and education in intelligent systems, fuzzy systems, and web-based systems for engineering and other technical fields in science and technology. The journal focuses on the disciplines of computer science, electrical engineering, manufacturing engineering, industrial engineering, chemical engineering, mechanical engineering, civil engineering, engineering management, bioengineering, and biomedical engineering. The scope of the journal also includes developing technologies in mathematics, operations research, technology management, the hard and soft sciences, and technical, social and environmental issues.
Authors: Zhang, Xuefeng | Su, Jiafu
Article Type: Research Article
Abstract: Solution selection plays an important role in crowdsourcing and is an imperative work for requesters. However, to the best of our knowledge, there is few studies focus on the problem of solution selection, especially in crowdsourcing contests for innovative tasks. This paper aims to develop a methodology incorporating quality function deployment (QFD) with 2-tuple linguistic method to assist requesters to select the right solution from a large pool of potential solutions efficiently. The methodology includes three phases. The first phase, i.e. pre-selection, is to screen potential solutions by employing the rule of non-compensatory. The second phase is to construct …relationships between requester’s requirements and solution features using quality function deployment (QFD), and further to determine the weights of solution features using 2-tuple linguistic weighted average operator and fuzzy weighted average method. The last phase is to evaluate the performance of potential solutions with respect to solution features, and further estimate their overall performance. Finally, an illustrative application case on the crowdsourcing platform-Taskcn is presented to demonstrate the implementation and effectiveness of the proposed approach. Show more
Keywords: Crowdsourcing contests, innovative tasks, solution selection, quality function deployment, 2-tuple linguistic method
DOI: 10.3233/JIFS-181122
Citation: Journal of Intelligent & Fuzzy Systems, vol. 35, no. 6, pp. 6329-6342, 2018
Authors: Hu, Bo | Bi, Lvqing | Dai, Songsong | Li, Sizhao
Article Type: Research Article
Abstract: A complex fuzzy set is a set whose membership grades are complex values in the unit circle in the complex plane. This paper introduces the concept of approximate parallelity between complex fuzzy sets based on the phase of complex-valued membership grade. After that, the property of approximate parallelity preserving for complex fuzzy operators and complex fuzzy inference are investigated.
Keywords: Approximate parallelity, approximate parallelity preserving, complex fuzzy sets, complex fuzzy operators, complex fuzzy inference
DOI: 10.3233/JIFS-181131
Citation: Journal of Intelligent & Fuzzy Systems, vol. 35, no. 6, pp. 6343-6351, 2018
Authors: Kutlu Gündoğdu, Fatma | Kahraman, Cengiz | Civan, Hatice Nida
Article Type: Research Article
Abstract: EDAS (Evaluation Based on Distance from Average Solution) is based on the distances of each alternative from the average solution. It is similar to other distance based multi-attribute decision-making methods such as TOPSIS and VIKOR. Hesitant fuzzy sets are an extension of ordinary fuzzy sets where the hesitation arises in the assignment of membership degrees of the elements to a fuzzy set. In this paper, we extend classical EDAS method to its hesitant fuzzy version in order to capture decision makers’ hesitancies. The proposed Hesitant Fuzzy Evaluation Based on Distance from Average Solution (HF-EDAS) is based on different aggregation operators …with defuzzification and without-defuzzification processes, which is presented by four HF-EDAS versions. The proposed method has been applied to a multi-criteria and multi-expert hospital selection problem for organ transplantation. Additionally, we present a comparative analysis with hesitant fuzzy TOPSIS (HF-TOPSIS). The results show that HF-EDAS selects the same best alternative as HF-TOPSIS. However, the proposed versions of HF-EDAS indicated some slight changes in the ranking of alternatives. Show more
Keywords: EDAS, multi-criteria decision making, hesitant fuzzy sets, service quality, hospital selection
DOI: 10.3233/JIFS-181172
Citation: Journal of Intelligent & Fuzzy Systems, vol. 35, no. 6, pp. 6353-6365, 2018
Authors: Daneshpayeh, Roohallah | Borumand Saeid, Arsham | Mirvakili, Saeed | Rezaei, Akbar
Article Type: Research Article
Abstract: In this paper, the notions of orthogonal, dense, regular, zero-divisor, strong and complemented elements in a pseudo BL-algebra are introduced and relation between the orthogonal and zero-divisor elements for perfect (good) pseudo BL-algebras is investigated. In particular, we get some results when a pseudo BL- algebra is good or perfect. Finally, a new characterization of these elements in a pseudo BL-algebra by a diagram is given.
Keywords: Pseudo BL-algebra, (Perfect, Primary) filter, radical, (Orthogonal, Dense, Regular, Zero divisor, Strong, Complemented) elements
DOI: 10.3233/JIFS-181218
Citation: Journal of Intelligent & Fuzzy Systems, vol. 35, no. 6, pp. 6367-6377, 2018
Authors: Mahapatra, Tanmoy | Pal, Madhumangal
Article Type: Research Article
Abstract: In this article, a new idea of fuzzy coloring of m -polar fuzzy graph is presented while establishing the relationship between chromatic number of m -polar fuzzy graph and it’s underlying crisp graph. Some properties of m -polar fuzzy graph and new concepts of independently strong edge and independently weak edge in m -polar fuzzy graph are proved. The differences between fuzzy coloring of fuzzy graph and m -polar fuzzy graph are discussed. It is also shown that a m -polar fuzzy graph can be decomposed into m fuzzy graphs. Again, from m isomorphic fuzzy graph one …can construct a m -polar fuzzy graph. A relation among chromatic numbers of m -polar fuzzy graph and m such graphs is established. Lastly a real life application of the fuzzy coloring is discussed. Show more
Keywords: m-polar fuzzy graph, α-strength cut graphs, independently weak edges, independently strong edges, chromatic number
DOI: 10.3233/JIFS-181262
Citation: Journal of Intelligent & Fuzzy Systems, vol. 35, no. 6, pp. 6379-6391, 2018
Authors: Davvaz, Bijan | Kim, Yong Chan
Article Type: Research Article
Abstract: In this paper, we introduce the concepts of Alexandrov L -neighborhood filters, Alexandrov L -topologies and Alexandrov L -convergence structures in complete residuated lattices. We investigate the Galois correspondences among Alexandrov L -neighborhood filters, Alexandrov L -topologies and Alexandrov L -convergence structures. Moreover, we investigate their topological properties and give their examples.
Keywords: Complete residuated lattices, Alexandrov L-topologies, Alexandrov L-neighborhood filters, Alexandrov L-convergence structures
DOI: 10.3233/JIFS-181295
Citation: Journal of Intelligent & Fuzzy Systems, vol. 35, no. 6, pp. 6393-6404, 2018
Authors: Hong, Jie | Qin, Xiansheng | Li, Jing | Niu, Junlong | Wang, Wenjie
Article Type: Research Article
Abstract: Over the past two decades, motor imagery brain-computer interface (MI-BCI) system has been extensively developed. In this system signal processing algorithms are critical to robust operation. In BCI community, however, there is no comprehensive review of the recent development of signal processing algorithms. Through analyzing the latest papers, signal processing algorithms of pre-processing, feature extraction, feature selection, and classification components are discussed in detail. Besides, post-processing and other existing problems are mentioned. The following key issues are addressed: (1) which components are the key of signal processing; (2) which signal processing algorithms are frequently used in each component; (3) which …signal processing algorithms attract more attention. This information can be used as reference and guidance for further research. Show more
Keywords: Motor imagery brain-computer interface (MI-BCI), signal processing algorithms, pre-processing, feature extraction, classification
DOI: 10.3233/JIFS-181309
Citation: Journal of Intelligent & Fuzzy Systems, vol. 35, no. 6, pp. 6405-6419, 2018
Authors: Prabhu, S. | Flora, T. | Arulperumjothi, M.
Article Type: Research Article
Abstract: Let G (V , E ) be a Graph. A set W ⊆ V of vertices resolves a graph G if every vertex of G is uniquely determined by its vector of distances to the vertices in W . The metric dimension of G is the minimum cardinality of a resolving set. By imposing different conditions on W we get conditional resolving sets. A resolving set W is said to be an independent resolving set if W contains isolated vertices. Independent resolving number denoted by ir (G) is referred to its …cardinality. In this paper we investigate independent resolving number for Titanium dioxide Nanotube. Show more
Keywords: Metric dimension, independent resolving set, independent resolving number, Titanium dioxide, Nanotube, Nanostructure
DOI: 10.3233/JIFS-181314
Citation: Journal of Intelligent & Fuzzy Systems, vol. 35, no. 6, pp. 6421-6425, 2018
Authors: Yang, Jinxin | Tang, Xiaoan | Yang, Shanlin
Article Type: Research Article
Abstract: Hesitant fuzzy set theory provides an effective technique for researchers and engineers to cope with vagueness and uncertainty. In recent years, to explore the correlation between hesitant fuzzy sets, traditional correlation measure in statistics has been constantly studied in hesitant fuzzy environments. In this study, extant studies of correlation measures in hesitant fuzzy contexts are recalled and analyzed. In view of the forgoing analysis, we find out that the extant correlation coefficients have some limitations. Moreover, a few correlation coefficients are not in line with the traditional definition of correlation coefficients. In order to address the flaws of the existing …proposals, a novel hesitant fuzzy correlation coefficient is proposed in this study. The new proposal of this study can not only overcome the flaws of the old hesitant fuzzy correlation coefficients, but it also shows several desirable characteristics. The weighted form of the newly defined correlation coefficient and its features are also investigated. Finally, three numerical examples concerning supplier selection and medical diagnosis are examined using the developed correlation coefficients to demonstrate their applicability. Comparison analyses with existing proposals highlight the efficiency of our proposals. Show more
Keywords: Correlation coefficient, hesitant fuzzy sets, decision making, supplier selection, medical diagnosis
DOI: 10.3233/JIFS-181393
Citation: Journal of Intelligent & Fuzzy Systems, vol. 35, no. 6, pp. 6427-6441, 2018
Authors: Rashmanlou, Hossein | Pal, Madhumangal | Borzooei, Rajab Ali | Mofidnakhaei, F. | Sarkar, Biswajit
Article Type: Research Article
Abstract: Theoretical concepts of graphs are highly utilized by computer science applications. Especially in research areas of computer science such as data mining, image segmentation, clustering, image capturing and networking. The interval-valued fuzzy graphs are more flexible and compatible than fuzzy graphs due to the fact that they have many applications in networks. In this paper, at first we define three new operations on interval-valued fuzzy graphs namely strong product, tensor product and lexicographic product. Likewise, we study about the degree of a vertex in interval-valued fuzzy graphs which are obtained from two given interval-valued fuzzy graphs using the operations Cartesian …product, composition, tensor and strong product of two interval-valued fuzzy graphs. These operations are highly utilized by computer science, geometry, algebra, number theory and operation research. In addition to the existing operations these properties will also be helpful to study large interval-valued fuzzy graph as a combination of small, interval-valued fuzzy graphs and to derive its properties from those of the smaller ones. Show more
Keywords: Cartesian product, composition, tensor product, lexicographic product
DOI: 10.3233/JIFS-181488
Citation: Journal of Intelligent & Fuzzy Systems, vol. 35, no. 6, pp. 6443-6451, 2018
Authors: Rivaz, Azim | Azizian, Mahdieh | Kamyad, Ali Vahidian | Zadeh, Somayeh Zangoei
Article Type: Research Article
Abstract: Mathematical modelling as a useful technique to obtain a better and wider perception of a complex biological subject such as cancer, has been increasingly applied in recent years. Since the parameters of a mathematical model are obtained by observations and measurements, they are exposed to errors and have uncertainty and ambiguity in their nature. In this paper, in order to achieve a more realistic mathematical model of tumor growth, a system of integro-partial differential equations which describes the growth of a tumor characterized by the presence of cancer stem cells - which are the main reason of treatment failure …and tumor relapse - is generalized to a fuzzy integro-partial differential system. Introducing some definitions, several theorems are proved to convert the fuzzy integro-partial differential system to an optimization problem. The proposed new method computes not only the approximate fuzzy solution of the full fuzzy system, but also the difference between the exact and approximate solution. It is further found that the tumor growth paradox appears in the full fuzzy mathematical model of tumor growth as well. Show more
Keywords: Fuzzy mathematical model, tumor growth model, stem cells, fuzzy integro-differential system, tumor growth paradox
DOI: 10.3233/JIFS-18261
Citation: Journal of Intelligent & Fuzzy Systems, vol. 35, no. 6, pp. 6453-6460, 2018
Authors: Ünver, Mehmet | Özçelik, Gökhan | Olgun, Murat
Article Type: Research Article
Abstract: The main goal of the present paper is to study the general structure and theoretical properties of a particular type of a fuzzy measure that can be used to model multi criteria decision making problems in which there exist some sub criteria. After constructing the general form of the non-additive set function, we deal with the interaction coefficient, Möbius representation and dual measure related to proposed measure. Finally, we are concerned with the usage of this type of fuzzy measures in multi criteria decision making problems in which at least one of the criteria contains some sub-criteria.
Keywords: Fuzzy measure, nonadditive measure, sub-criteria, multicriteria decision making, Möbius representation
DOI: 10.3233/JIFS-18396
Citation: Journal of Intelligent & Fuzzy Systems, vol. 35, no. 6, pp. 6461-6468, 2018
Authors: Kouahla, Zineddine | Anjum, Adeel | Seridi, Hamid
Article Type: Research Article
Abstract: Similarity search for content-based retrieval - a sustained problem; many applications endures. Most of the similarity measures intend focusing the least possible set of elements to find an answer. In the literature, most work is based on splitting the target data set into subsets using balls. However, in the era of big data, where efficient indexing is of vital importance, the subspace volumes grow exponentially, which could degenerate the index. This problem arises due to inherent insufficiency of space partitioning interlaced with the overlap factor among the regions. This affects the search algorithms thereby rendering these methods ineffective as it …gets hard to store, manage and analyze the aforementioned quantities. A good topology should avoid biased allocation of objects for separable sets and should not influence the structure of the index. We put-forward a novel technique for indexing; IMB-tree , which limits the volume space, excludes the empty sets; the separable partitions, does not contain objects and creates eXtended regions that will be inserted into a new index named eXtended index , implemented in a P2P environment. These can reunite all objects in one of the subsets-partitions; either in a separable set or in the exclusion set, keeping the others empty. We also discussed the efficiency of construction and search algorithms, as well as the quality of the index. The experimental results show interesting performances. Show more
Keywords: Indexing, eXtended region, parallel, metric space, complex data
DOI: 10.3233/JIFS-18398
Citation: Journal of Intelligent & Fuzzy Systems, vol. 35, no. 6, pp. 6469-6478, 2018
Authors: Qu, Guohua | Li, Tianjiao | Zhao, Xia | Qu, Weihua | An, Qianying | Yan, Junai
Article Type: Research Article
Abstract: In this paper, a stochastic decision making method based on regret theory and group satisfaction is proposed with unknown attribute weights and dual hesitant fuzzy elements. Considering that the decision makers have different levels of satisfaction with the alternatives, first of all, according to the score function and the accuracy function of dual hesitant fuzzy elements, a novel group satisfaction degree function of dual hesitant fuzzy elements is defined. And then, an attribute weight optimization model based on the new group satisfaction degree of dual hesitant fuzzy elements is established and the Lagrange function is constructed to obtain the attribute …weights. Secondly, on the basis of the regret theory, the regret and rejoice valued matrices of the program are given, and then the ranking values of each alternative can be obtained by combining with the weight of the attribute. Finally, a numerical example is given to illustrate the applicability and feasibility of the proposed method. Show more
Keywords: Dual hesitant fuzzy element, regret theory, group satisfaction degree, stochastic decision making
DOI: 10.3233/JIFS-18667
Citation: Journal of Intelligent & Fuzzy Systems, vol. 35, no. 6, pp. 6479-6488, 2018
Authors: Xu, Bingyuan | Zhou, Zhiheng | Chen, Xi | Yang, Yi | Yang, Zhiwei
Article Type: Research Article
Abstract: A new algorithm for static hand gesture recognition is proposed in this paper, which mainly includes the following four steps: hand segmentation, arm removal, feature extraction and gesture recognition. Firstly, the hand is extracted from the background by using skin-color features and geometric characteristics. Secondly, a new arm removal algorithm is proposed, which can effectively and quickly remove the arm area by using distance transformation operations, and gesture composed of palm and fingers can be obtained. Finally, Hu moments of the gesture image and the number of fingertips are calculated and entered into the Support Vector Machine (SVM) for …training. Experiments have been performed to demonstrate that the proposed algorithm is robust in complex background, and can detect and recognize gestures in real time with an accuracy of 94.89%. Show more
Keywords: Arm removal, static hand gesture recognition, distance transformation, SVM
DOI: 10.3233/JIFS-18681
Citation: Journal of Intelligent & Fuzzy Systems, vol. 35, no. 6, pp. 6489-6500, 2018
Authors: Moral-García, Serafín | Mantas, Carlos J. | Castellano, Javier G. | Abellán, Joaqu’ın
Article Type: Research Article
Abstract: Binary Relevance (BR) is a simple and direct approach to the Multi-Label Classification (MLC). It decomposes the multi-label problem into several binary problems, one per label. It uses an algorithm of traditional supervised classification in order to solve these binary problems. On the other hand, Credal C4.5 (CC4.5) is a modification of the classical C4.5. CC4.5 estimates the probability of the class variable by using imprecise probabilities. In the literature, this new classification algorithm has obtained better results than C4.5 when both have been applied on datasets with class noise. In MLC, since there are not just a class, but …multiple labels are disposed, it is more probable that there is intrinsic noise than in traditional classification. From the previous reasons, in this work it is studied the performance of BR using Credal C4.5 as base classifier versus BR with C4.5. It is carried out an experimental study with several muti-label datasets and a considerable number of measures for MLC. This study shows that the performance of BR is improved when it uses CC4.5 as base classifier versus BR with C4.5. In consequence, it is probably suitable to apply imprecise probabilities in Decision Trees within the MLC field too. Show more
Keywords: Multi-label classification, Binary Relevance, Credal C4.5, C4.5, imprecise probabilities
DOI: 10.3233/JIFS-18746
Citation: Journal of Intelligent & Fuzzy Systems, vol. 35, no. 6, pp. 6501-6512, 2018
Authors: Jin, Feifei | Ni, Zhiwei | Chen, Huayou | Langari, Reza | Zhu, Xuhui | Yuan, Hongjun
Article Type: Research Article
Abstract: The single-valued neutrosophic sets (SVNSs) are useful tools to describe uncertainty and inconsistent information that exist in real world. For SVNSs theory, two important topics are single-valued neutrosophic entropy and single-valued neutrosophic similarity measurer. This paper investigates a multi-attribute decision-making (MADM) method by using single-valued neutrosophic entropy and similarity measure. First, the concepts of single-valued neutrosophic entropy and similarity measure are presented. Then, based on the trigonometric functions (i.e., sine function and cosine function), we introduce two information measure formulas and prove that they satisfy the requirements of the single-valued neutrosophic entropy and similarity measure, respectively. Furthermore, we study the …inter-relationship between single-valued neutrosophic entropy and similarity measure. By using Lagrange Multiplier Method and closeness degree, we develop a novel single-valued neutrosophic MADM method. Finally, a numerical example of selecting the desirable supplier is provided, and the comparison with existing approaches is performed to validate the rationality and effectiveness of the proposed method. Show more
Keywords: Multi-attribute decision making, single-valued neutrosophic sets, entropy, similarity measure
DOI: 10.3233/JIFS-18854
Citation: Journal of Intelligent & Fuzzy Systems, vol. 35, no. 6, pp. 6513-6523, 2018
Authors: Li, Chengdong | Yan, Bingyang | Tang, Minjia | Yi, Jianqiang | Zhang, Xiqiao
Article Type: Research Article
Abstract: Traffic flow prediction can not only improve the reasonability of the managers’ decision-making and road planning effectively, but also provide helpful suggestions for travelers to avoid traffic congestion. In order to further improve the prediction accuracy of traffic flow, this study presents one data driven hybrid model for short-term traffic flow prediction. This hybrid model firstly extracts the periodicity pattern from the traffic flow data, then, constructs the functionally weighted single-input-rule-modules connected fuzzy inference system (FWSIRM-FIS) for the residual data after removing the periodicity pattern from the original data, and finally, generates the final prediction results through integrating the periodicity …pattern and the output from the FWSIRM-FIS model. The partial autocorrelation function (PACF) method is adopted to determine the optimal inputs for the data driven FWSIRM-FIS model, and the iterative least square method is utilized to train the parameters of the FWSIRM-FIS. Furthermore, three detailed experiments on traffic flow prediction are made, and comprehensive comparisons with three popular artificial intelligence methods are done to verify the effectiveness and advantages of the proposed hybrid model. According to five comparison indices, the proposed hybrid model can achieve the best prediction performance, although with much less fuzzy rules. The error histograms also verify that the proposed hybrid model has the smallest prediction errors comparing to the three comparative methods. The hybrid approach proposed in this study can also be extended to some other applications which have periodicity patterns, e.g. the traveling time estimate and the electricity load forecasting. Show more
Keywords: Traffic flow prediction, fuzzy method, single input rule module, least square learning, traffic-flow pattern
DOI: 10.3233/JIFS-18883
Citation: Journal of Intelligent & Fuzzy Systems, vol. 35, no. 6, pp. 6525-6536, 2018
Authors: Dian, Songyi | Liang, Weibo | Zhao, Tao
Article Type: Research Article
Abstract: Finite-time stability and stabilization problems for a class of interval type-2 (IT2) fuzzy time-delay systems are studied. In this paper, we extend the concept of finite-time stability to IT2 fuzzy time-delay systems. Based on the Lyapunov stability method, integral inequality and some advanced matrix inequalities, a sufficient condition is proposed to guarantee finite-time stability of IT2 fuzzy time-delay systems. Then, by virtue of the results on finite-time stability and Finsler’s lemma, we propose an IT2 fuzzy state feedback controller which can guarantee the closed-loop system is finite time stable. The problem of finite time stabilization can be solved with con …complementarity linearization iterative algorithm. Finally, two numerical examples are provided to verify the effectiveness of the proposed approach. Show more
Keywords: IT2 fuzzy systems, state feedback control, finite-time, time-delay
DOI: 10.3233/JIFS-18933
Citation: Journal of Intelligent & Fuzzy Systems, vol. 35, no. 6, pp. 6537-6549, 2018
Authors: Singh, Kuldeep | Singh, Shashank Sheshar | Kumar, Ajay | Biswas, Bhaskar
Article Type: Research Article
Abstract: Mining high utility itemsets (HUIs) is a basic task of frequent itemsets mining (FIM). In recent years, a trend in FIM has been to design algorithm for mining HUIs because FIM assumes that each item can not appear more than once in a transaction and all items have the same importance (weight, unit profit, price, etc.). However, in real-world, items appear more than once in a transaction and also have some importance. HUIs mining considers that items appear with some quantity and importance. Traditional HUIs mining algorithms assume that items have only positive unit profit. However, in real-world, items …may appear with negative unit profit also. For example, it is common that a retail store sells items at a loss to stimulate the sale of other related items or simply to attract customers to their retail location. Therefore, items occur with negative unit profit or negative utility. To consider negative unit profit, HUIs with negative utility has been introduced. This paper surveys recent studies on HUIs mining with negative utility and their applications. The main goal is to provide a survey of recent advancements and research opportunities. This paper presents key concepts and terminology related to HUIs mining with negative utility. This presents a taxonomy of all the algorithms consider negative utility. To the best of our knowledge, this is the first survey on the mining task of HUIs with negative utility. The paper also presents research opportunities and the challenges in HUIs mining problems. Show more
Keywords: High utility itemsets mining, utility mining, negative utility
DOI: 10.3233/JIFS-18965
Citation: Journal of Intelligent & Fuzzy Systems, vol. 35, no. 6, pp. 6551-6562, 2018
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