Journal of Intelligent & Fuzzy Systems - Volume 32, issue 3

Authors: Song, Seok-Zun | Bordbar, Hashem | Jun, Young Bae

Article Type: Research Article

Abstract: The concept of hesitant union (⋓) is introduced. Using this, the notions of ⋓-hesitant fuzzy subalgebras and ⋓-hesitant fuzzy ideals are introduced and several properties are investigated. Relations between ∪-hesitant fuzzy subalgebras (resp. ideals) and ⋓-hesitant fuzzy subalgebras (resp. ideals) are considered. Relations between a ⋓-hesitant fuzzy subalgebra/ideal and its lower level set are investigated. Characterizations of ∪-hesitant fuzzy subalgebras/ideals are discussed. Given a subalgebra (resp., ideal) A of a BCK /BCI -algebra X , a ⋓-hesitant fuzzy subalgebra (resp., ideal) is established.

Keywords: Hesitant union, ∪-hesitant fuzzy subalgebra, ∪-hesitant fuzzy ideal, ⋓-hesitant fuzzy subalgebra, ⋓-hesitant fuzzy ideal, lower hesitant level set

DOI: 10.3233/JIFS-161601

Citation: Journal of Intelligent & Fuzzy Systems, vol. 32, no. 3, pp. 2009-2016, 2017

Authors: Guo, Jifa | Shao, Xiaodong

Article Type: Research Article

Abstract: The division of internal structures and external space of geographical entities is foundation of spatial analysis, query and reasoning. Most current division methods are crisp, and inconsistent with human cognitive habits. Usually existing geographic information systems(GISs) analyze spatial data directly by certain spatial analysis methods and then use natural language or words to explain analysis results, so the encoding process is absence but it is necessary in intelligent GIS (IGIS). Fuzzy geographical entities and phenomena occur throughout the real world, and these semantics of words related spatial locations and relations usually involve uncertainties. First, the geographical perceptual computing (GPC) model …based on CWW is proposed and it includes four modules: input, geo-encoder, geographical CWW engine and geo-decoder. Then, the trapezoidal fuzzy set is adopted to represent spatial words. A fine fuzzy spatial partitioning model of line objects based on CWW is proposed. The interior of a line object is divided into several parts according to fuzzy logic and human cognitive habits. The exterior of a line entity is then divided into several parts by combining direction relation and distance relation models with fuzzy logic methods. This model provides a full natural language description of the interior and exterior of crisp or fuzzy line entities and consistent with human cognitive habits. An application case of this model is provided in the last and proves the superiority of this model. Show more

Keywords: Fuzzy spatial relation, natural language, CWW, semantic uncertainties, artificial intelligence

DOI: 10.3233/JIFS-161616

Citation: Journal of Intelligent & Fuzzy Systems, vol. 32, no. 3, pp. 2017-2032, 2017

Authors: Blanco-Mesa, Fabio | Merigó, José M. | Gil-Lafuente, Anna M.

Article Type: Research Article

Abstract: Fuzzy decision-making consists in making decisions under complex and uncertain environments where the information can be assessed with fuzzy sets and systems. The aim of this study is to review the main contributions in this field by using a bibliometric approach. For doing so, the article uses a wide range of bibliometric indicators including the citations and the h -index. Moreover, it also uses the VOS viewer software in order to map the main trends in this area. The work considers the leading journals, articles, authors and institutions. The results indicate that the USA was the traditional leader in this …field with the most significant researcher. However, during the last years, this field is receiving more attention by Asian authors that are starting to lead the field. This discipline has a strong potential and the expectations for the future is that it will continue to grow. Show more

Keywords: Bibliometrics, fuzzy decision-making, Web of Science, VOS viewer

DOI: 10.3233/JIFS-161640

Citation: Journal of Intelligent & Fuzzy Systems, vol. 32, no. 3, pp. 2033-2050, 2017

Authors: Yang, Xiangfeng | Ni, Yaodong | Zhang, Yansheng

Article Type: Research Article

Abstract: Uncertain differential equation is a kind of differential equations driven by Liu processes, many concepts of stability for uncertain differential equations have been researched. This paper first presents a concept of convergence in inverse distribution for an uncertain sequence, and then proposes a concept of stability in inverse distribution for an uncertain differential equation. A sufficient condition is proved for an uncertain differential equation being stable in inverse distribution. Moreover, some examples are given to illustrate the reasonability of stability in inverse distribution.

Keywords: Uncertainty theory, uncertain differential equation, stability, inverse distribution

DOI: 10.3233/JIFS-161661

Citation: Journal of Intelligent & Fuzzy Systems, vol. 32, no. 3, pp. 2051-2059, 2017

Authors: Xu, Tongle | Yin, Zhaojie | Cai, Daoyong | Zheng, Diankun

Article Type: Research Article

Abstract: In order to improve the accuracy of fault diagnosis, a fault diagnosis method for rotating machinery based on Local Mean Decomposition (LMD) morphological filtering and Least Square Support Vector Machine(LS-SVM) is proposed. Firstly, the collected vibration signals are processed by LMD which decomposes them into a series of product function (PF) components, and PF components are carried out by method of the morphological filtering and signal recombination. Then, the feature vector is obtained from the new PF components by LMD method. Secondly, a new kernel function is proposed to improve LS-SVM, which can solve the problem of kernel function parameters …selection. Further, Lagrange parameters are processed by feature weighting method, and the weighted average value of the Lagrange parameters is calculated as the threshold value of Pruning algorithm, which can solve sparsity problem in LS-SVM. Thirdly, Energy features are inputted into the new LS-SVM to recognize machinery faults according to LS-SVM parameters. Finally, the performance of the proposed method was verified by a fault diagnosis case in a rolling element bearing. The results indicated that this new method could judge and classify the multi-fault of rotating machinery quickly and effectively. Show more

Keywords: Fault diagnosis for rotating machinery, Local Mean Decomposition, morphological filtering, Least Square Support Vector Machine

DOI: 10.3233/JIFS-161676

Citation: Journal of Intelligent & Fuzzy Systems, vol. 32, no. 3, pp. 2061-2070, 2017

Authors: Ma, Xueling | Zhan, Jianming | Ali, Muhammad Irfan

Article Type: Research Article

Abstract: In this paper, we propose the notion of Z -soft fuzzy rough ideals of hemirings, which is an extended concept of Z -soft rough fuzzy ideals proposed by Zhan [J. Zhan, K. Zhu, A novel soft rough fuzzy set: Z -soft rough fuzzy ideals of hemirings and corresponding decision making, Soft Comput., 2016, DOI 10.1007/s00500-016-2119-9]. By two novel pseudo fuzzy soft sets, we investigate some kinds of Z -soft fuzzy rough ideals in hemirings with respect to a soft fuzzy approximation space. Some new soft fuzzy rough operations over hemirings are explored. Some Z -lower and Z -upper soft fuzzy …rough ideals (k -ideals, h -ideals, strong h -ideals) of hemirings are investigated. Show more

Keywords: Pseudo fuzzy soft set, Z-soft fuzzy rough set, Z-soft fuzzy rough ideal, hemiring

DOI: 10.3233/JIFS-161681

Citation: Journal of Intelligent & Fuzzy Systems, vol. 32, no. 3, pp. 2071-2082, 2017

Authors: Şahin, Rıdvan | Liu, Peide

Article Type: Research Article

Abstract: Simplified neutrosophic set (SNS) is a powerful tool that attracts the attention of many scholars in dealing with uncertainty and vagueness. A SNS is based on a combination of simplified neutrosophic numbers (SNNs), whose its basic components are characterized by a truth-membership degree, an indeterminacy-membership degree and a falsity-membership degree of an object in evaluation data. Aggregation operators used to synthesize simplified neutrosophic information is commonly not very effective in case where the criteria weights provided by decision makers are in form of SNNs rather than exact real numbers. In this paper, we propose two new operational laws in which …the bases are positive real numbers and interval numbers, respectively and the exponents are SNNs, and discuss some of their desired properties. Then we apply them to derive two weighted exponential aggregation operators, such as the simplified neutrosophic weighted exponential aggregation (SNWEA) operator and dual simplified neutrosophic weighted exponential aggregation (DSNWEA) operator. Additionally, two approaches for multi-criteria decision-making (MCDM) problems under the neutrosophic weight data are explored by applying these aggregation operators. At the end of the study, a convenient example is provided to demonstrate the availability and effectiveness of the proposed methods. Show more

Keywords: Simplified neutrosophic set, dual simplified neutrosophic set, exponential operational law, exponential aggregation operator, multi-criteria decision making

DOI: 10.3233/JIFS-161695

Citation: Journal of Intelligent & Fuzzy Systems, vol. 32, no. 3, pp. 2083-2099, 2017

Authors: Yu, Hongtao | Gao, Ruibo | Wang, Kun | Zhang, Fuzhi

Article Type: Research Article

Abstract: Collaborative filtering recommendation algorithms based on traditional matrix factorization model have poor robustness and low recommendation accuracy when facing shilling attacks. To address this issue, we propose a novel robust recommendation method based on kernel matrix factorization. We first construct a robust kernel matrix factorization model for collaborative recommendation by using kernel mapping of the rating matrix and kernel distance, and regulate residual error with the scale factor, which can enhance the power of the model’s anti-attack and realize the robust estimation of user feature matrix and item feature matrix. Then we introduce kernel distance to compute the similarity between …users in order to improve the credibility of user similarity and reduce the influence of attack profiles on the recommendation results. Finally, we devise a robust collaborative recommendation algorithm based on the kernel matrix factorization model. Experimental results show that our algorithm can improve the robustness and accuracy compared with the existing algorithms. Show more

Keywords: Shilling attacks, robust collaborative recommendation, kernel matrix factorization, residual factor

DOI: 10.3233/JIFS-161705

Citation: Journal of Intelligent & Fuzzy Systems, vol. 32, no. 3, pp. 2101-2109, 2017

Authors: Zhao, Tong | Lu, Yan | Liu, Changyou

Article Type: Research Article

Abstract: Aimed at issues such as fuzziness and subjectivity in choosing a thick residual coal re-mining methodology, a comprehensive optimization system for a thick residual coal re-mining method-Fuzzy Analytic Network Process (F-ANP) that was based on fuzzy comprehensive evaluation and Analytic Network Process (ANP) was established and applied. Reasonable re-mining method evaluation indices were established based on the conditions of occurrence of the residual coal and other factors, including technological, economic and regulatory factors. The pairwise comparison judgment matrix described by triangular fuzzy numbers and a fuzzy hypermatrix, established by using a network analysis method, was applied to facilitate quantitative and …scientific evaluation. The comprehensive optimization system for a thick residual coal re-mining method based on F-ANP was applied for 3# residual coal at Shenghua Mine, and theoretical analysis revealed that the fully mechanized mining with top coal caving technology (FTCCT) was the optimized option. On-site measurements demonstrated good compatibility for the optimized and improved FTCCT in residual coal re-mining. Therefore, we can conclude that the methodology selection system that had been developed was feasible and effective. Show more

Keywords: Thick residual coal, mechanized re-mining, method optimization, fuzzy analytic network process

DOI: 10.3233/JIFS-161816

Citation: Journal of Intelligent & Fuzzy Systems, vol. 32, no. 3, pp. 2111-2122, 2017

Authors: Ghannadi, Siavash | Mehrtash, Mahdi | Mohammadi, Mohammad | Raoofat, Mahdi

Article Type: Research Article

Abstract: Scheduling for generation units in modern power markets is one of the most important tasks of independent system operators (ISO). To ensure secure and economical operation of power systems, ISOs solve the security constrained unit commitment (SCUC) problem. SCUC is a very complex and large-scale optimization problem. In addition, uncertainties imposed by wind generators and variable loads add to this complexity. Stochastic SCUC, one of the most important problems for scheduling generation units, considers different power system uncertainties. A considerable amount of previous works demonstrates the efficacy of decomposition techniques, such as benders’ decomposition for Stochastic SCUC. Solving this problem, …even with decomposition techniques, for large-scale systems with multiple uncertainties is very time-consuming. A major part of Stochastic SCUC constraints belongs to network security. This paper presents a method in which cumulants are used to detect and eliminate inactive network constraints during the solving process. As a result, the method reduces the number of network security constraints and decreases the simulation time considerably. Implementing the proposed method on a six -bus test system and a modified IEEE 118-bus system demonstrates its efficiency and accuracy. Show more

Keywords: Benders’ decomposition, cumulants method, power system uncertainties, scenario reduction, stochastic security-constrained unit commitment

DOI: 10.3233/JIFS-161916

Citation: Journal of Intelligent & Fuzzy Systems, vol. 32, no. 3, pp. 2123-2135, 2017