Journal of Intelligent & Fuzzy Systems - Volume 35, issue 6

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