Journal of Intelligent & Fuzzy Systems - Volume 37, issue 3

Authors: Du, Yuxiang | Sheng, Qian | Fu, Xiaodong | Tang, Hua | Zhang, Zhenping | Zhao, Xin

Article Type: Research Article

Abstract: The stability of a colluvial slope, which is different from a rock or soil slope, is determined by the properties of both the bedrock and the colluvium. Coupled with artificial excavation and environmental effects, the stability factors of such slopes are complicated. To rapidly and effectively evaluate the risk of a colluvial cutting slope, a risk evaluation system for this type of slope is established herein. First, an evaluation index system is established, and reasonable risk evaluation indices are selected. Second, the fuzzy analytic hierarchy process (FAHP) is applied, a fuzzy pairwise comparison matrix, that must satisfy a consistency test, …is constructed, and the weight of each index is determined. Third, the risk evaluation grades are divided into 4 risk grades, and the risk evaluation criteria for each basic index are determined. Finally, the three-level fuzzy comprehensive evaluation (FCE) method is applied, the membership function for each index is constructed, the membership degree is calculated, and the risk grade of the colluvial cutting slope is determined. This risk evaluation system is used to evaluate the risks of 148 colluvial cutting slopes along the Xiaomengyang-Mohan highway in Yunnan, China. The results show that there are 24 slopes of low risk (grade I), 85 of medium risk (grade II), 22 of high risk (grade III), and 17 of very high risk (grade IV). The evaluation results obtained are in good agreement with the actual slope instability states: failure occurred in 15 out of 85 slopes of risk grade II, 13 out of 22 slopes of risk grade III, and 16 out of 17 slopes of risk grade IV. This application demonstrates that the proposed risk evaluation system for colluvial cutting slopes is universal, and stable and that the calculation results are objective. Show more

Keywords: Colluvial cutting slope, risk evaluation system, fuzzy analytic hierarchy process, fuzzy comprehensive evaluation

DOI: 10.3233/JIFS-190367

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 3, pp. 4253-4271, 2019

Authors: Rehmani, Sameeha | Sunitha, M.S.

Article Type: Research Article

Abstract: In this paper, the edge version of the geodesic number of a fuzzy graph is introduced and the properties satisfied are identified. A comparison between the vertex and edge version of the geodesic number of fuzzy graphs is obtained. The edge geodesic number of fuzzy trees, complete fuzzy graphs, complete bipartite fuzzy graphs and of fuzzy cycles are identified. A necessary and sufficient condition for the existence of an edge geodesic cover in a fuzzy graph is obtained. An application of edge geodesic sets in transportation systems in optimizing the number of traffic inspectors patrolling an urban road network is demonstrated. …The fuzziness in the problem helps to identify routes receiving less priority among passengers, elimination of which minimizes the loss suffered by various transport corporations due to lack of collection. Show more

Keywords: Edge geodesic cover, edge geodesic basis, edge geodesic number AMS Mathematics Subject Classification (2010): 05C72, 05C12, 05C38, 05C40, 90C35

DOI: 10.3233/JIFS-190383

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 3, pp. 4273-4286, 2019

Authors: Yogashanthi, T. | Mohanaselvi, S. | Ganesan, K.

Article Type: Research Article

Abstract:  In this paper a new centroid based ranking grade for generalized intuitionistic fuzzy numbers is proposed. The centroid point of membership function and non membership function of generalized intuitionistic fuzzy numbers in term of its parametric form is used for grading. The parametric representation of generalized intuitionistic fuzzy numbers involves left fuzziness index, right fuzziness index and modal value of membership and non membership functions. To reveal the performance of the proposed ranking grade, a comparison study has been made over the existing methods. Furthermore the proposed ranking method has been used for estimating the minimum total elapsed time to …a flow shop scheduling problem involving generalized intuitionistic fuzzy number. An improved result for flow shop scheduling problem has been attained using the proposed ranking grade and has been illustrated through an example. Show more

Keywords: Fuzzy set, generalized intuitionistic fuzzy numbers, centroid point, ranking grade, flow shop scheduling problem

DOI: 10.3233/JIFS-190395

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 3, pp. 4287-4297, 2019

Authors: Yadav, Nidhika | Chatterjee, Niladri

Article Type: Research Article

Abstract: Rough Sets provide a mathematical tool to handle decision making under uncertainty. One major domain that can be characterized with inherent ambiguity is natural language texts which often leads to uncertainty in understanding the intent and relative importance of a sentence with respect to its context in the whole text. As a consequence, the process of sentence selection for generation of extractive summary can logically be considered as a process of decision making under uncertainty. In this paper we use rough set based techniques to deal with this uncertainty. This paper’s contribution is two-fold. Firstly, this paper proposes a novel …Rough Set based uncertainty measure called span and define special Rough subsets of universe called spanning sets . Span is Rough Set based measure for salience of a subset of universe and spanning set is the subset that maximizes the span. This corresponds to the key elements representing a problem and can be used to solve various real-life applications. Secondly, the concepts are applied to determine extracts of text documents. The idea behind the present work is to determine the most suitable subset(s) of the universe of sentences under consideration. An optimization problem is formulated to generate the extract for the text under consideration using the proposed uncertainty measure of span and is solved using Particle Swarm Optimization. The experimental results on DUC2001, DUC2002 single document data sets and Enron Email datasets establish the effectiveness of the proposed technique. There has been substantial work on Rough Sets though considering a stochastic Rough-subset of the universe and determining its aptness as a representative of the universe is still unexplored. The proposed technique is a novel effort to fill this gap. Show more

Keywords: Rough set, extractive text summarization, span, spanning set, particle swarm optimization, ROUGE, extraction, lexical chains, DUC2001, DUC2002, LSA, graph, random indexing, GLOVE

DOI: 10.3233/JIFS-190402

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 3, pp. 4299-4309, 2019

Authors: Li, Jing | Zhang, Yulin

Article Type: Research Article

Abstract: Interval fuzzy preference relations (IFPRs) have been widely adopted in describing vagueness and uncertainty in real-life decision problems. Different methods have been applied in aggregating decision makers’ (DMs’) IFPRs. Nevertheless, the objective weights of DMs are often neglected in the group decision literature. Besides, the commonly methods used in aggregating decision makers’ (DMs’) IFPRs may make the final result too average. This paper investigates the plant growth simulation algorithm (PGSA) to aggregate interval fuzzy preference relations (IFPRs) and then derives the objective weights of decision makers (DMs) based on the deviation measure method. Next, the weighted aggregation IFPR is obtained …by PGSA and the alternatives are ranked based on the continuous ordered weighted averaging (COWA) operator. The new aggregation method creatively converts the elements of IFPRs into two-dimensional coordinates and the ideal IFPR can be aggregated by PGSA based on the minimum Euclidean distance model. Then the weight of each DM can be derived according to the Euclidean distance between the individual IFPR and ideal IFPR based on the deviation measure method. Finally, a weighted aggregated IFPR can be obtained by PGSA and the ranking of alternatives is obtained by the COWA operator. Numerical examples are given to verify the efficiency and superiority of the method. Show more

Keywords: Weights of decision makers (DMs), interval fuzzy preference relations (IFPRs), deviation measure method, the minimum Euclidean distance model, plant growth simulation algorithm (PGSA)

DOI: 10.3233/JIFS-190410

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 3, pp. 4311-4323, 2019

Authors: Li, Lei-Jun | Li, Mei-Zheng | Mi, Ju-Sheng | Xie, Bin

Article Type: Research Article

Abstract: Attribute reduction is one of the crucial issues in Formal Concept Analysis. Discernibility matrix plays an important role in attribute reduction, and has been achieved many successful applications in different concept lattice models. Nevertheless, it requires the construction of the concept lattice before the discernibility matrices are computed when applying traditional approaches, which is both time and space consuming. Furthermore, in some discernibility matrices, the comparisons between every two concepts result in a high computation complexity. To address these problems, granular concepts, i.e., the object concepts and the attribute concepts, are considered in this paper, and a simple discernibility matrix …named Object-Attribute discernibility matrix is proposed. It averts the construction of the whole concept lattice and the comparisons between every two concepts. Consequently, the time complexity is greatly reduced, and a lot of storage space can also be saved. Theoretical analysis and experimental results show the efficiency of Object-Attribute discernibility matrix. Show more

Keywords: Formal concept analysis, concept lattice, attribute reduction, discernibility matrix, granular concept

DOI: 10.3233/JIFS-190436

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 3, pp. 4325-4337, 2019

Authors: Wu, Ziheng | Wang, Bing

Article Type: Research Article

Abstract: Fuzzy c-means algorithm (Fcm) frequently applid in machine learning has been proven an effective clustering approach. However, the traditional Fcm cannot distinguish the importance of the different data objects and the discriminative ability of the different features in the clustering process. In this paper, we propose a new kind of Fcm clustering framework: DwfwFcm.Considering the different data weights and feature weights, an adaptive data weights vector and an adaptive feature weights matrix are introduced into the conventional Fcm and a new objective function is constructed. By the proposed objective function, the corresponding scientific updating iterative rules of the membership matrix, …the weights of the different feature, the weights of the different data object and the cluster centers can be derived theoretically.Experimental results have demonstrated that the algorithm proposed in this paper can deliver consistently promising results and improve the clustering performance greatly. Show more

Keywords: Fuzzy c-means algorithm, machine learning, clustering, adaptive data weights vector, adaptive feature weights vector

DOI: 10.3233/JIFS-190440

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 3, pp. 4339-4347, 2019

Authors: Yang, Qiang | Li, Yan-Lai | Chin, Kwai-Sang

Article Type: Research Article

Abstract: Quality function deployment (QFD) is an effective tool for the design and improvement of products/services. The prioritization of customer requirements (CRs), as an essential component of the house of quality, is fundamental and strategic in the whole process of QFD product planning. This study proposes a novel ordinal scale values based group decision-making (GDM) approach first and it is subsequently used to prioritize CRs in QFD product planning. The proposed approach is composed of three stages, that is, constructing the integrated preference vector, defining the extraction sequence and constructing the comprehensive preference vector. The proposed GDM approach is good for …utilizing the ordinal scale values provided by respondents due to limited experience and knowledge. An illustrative example is presented to verify the applicability and efficiency of the proposed approach. Further, to demonstrate the superiority of the proposed approach, comparisons are made between the proposed approach and two other similar methods. Practical results demonstrated that the proposed approach can be effective when the importance of customers and the preference evaluations of CRs are given by an ordinal scale. Show more

Keywords: Quality function deployment (QFD), customer requirement (CR), group decision-making (GDM), ordinal scale, preference ordering

DOI: 10.3233/JIFS-190444

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 3, pp. 4349-4367, 2019

Authors: Ali, Abbas | Rehman, Noor | Jang, Sun Young | Park, Choonkil

Article Type: Research Article

Abstract:  The notions of fuzzy upward β -covering, the fuzzy upward β -neighborhood, upward β -neighborhood and fuzzy complement β -neighborhood are introduced and several related properties are studied. Furthermore, multigranulation optimistic/pessimistic fuzzy rough sets based on fuzzy upward β -covering are initiated and their fundamental properties are investigated. We also find the upward β -neighborhood in the fuzzy upward covering approximation space and present the optimistic/pessimistic multigranulation rough sets to further enrich the presented notions. The medicine selection via fuzzy upward β -covering rough sets in medical diagnosis is another main contribution of the present work. It is also explored …that which medicine can be prescribed for which particular symtom(s) and which disease. Show more

Keywords: Fuzzy preference relation, fuzzy rough set, β-covering rough sets

DOI: 10.3233/JIFS-190447

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 3, pp. 4369-4390, 2019

Authors: Fan, Jianping | Liu, Jie | Wu, Meiqin

Article Type: Research Article

Abstract: Cross-efficiency assessment method is a useful tool for assessing the relative performance of decision-making units (DMUs). It is generally assumed that decision makers (DMs) are completely rational in the cross-efficiency model, and DMs’ risk attitude has not been considered important in the evaluation process. When the self-evaluation score of the DMU is optimal, the input and output weights are non-unique, resulting in non-unique cross-efficiency score, which affects the ranking result. The relative importance of DMUs is ignored when aggregating cross-efficiency scores. in view of the above problems, a cross-efficiency method based on prospect theory is proposed to capture the bounded …rational psychological behavior of risk DMs. This method considers all multiple optimal solutions and constructs interval cross-efficiency. The credibility of each cross-efficiency score is obtained based on the D-S evidence theory, and the weight of each DMU is obtained by using the Dempster rule. DMUs are ranked by calculating the prospect value. The validity and feasibility of the proposed method and how does the risk preference of DMs characterized by parameters α , β , λ affect the evaluation results are verified by an illustrative example. Show more

Keywords: Data envelopment analysis, cross-efficiency, interval number, dempster-shafer theory, prospect theory

DOI: 10.3233/JIFS-190450

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 3, pp. 4391-4404, 2019