Journal of Intelligent & Fuzzy Systems - Volume 36, issue 2

Authors: Tarek, Zahraa | AL-Rahmawy, Mohammed | Tolba, Ahmed

Article Type: Research Article

Abstract:  Traffic congestion is a big problem that influences the traffic flow in big cities, so better control of the traffic signals is always searched to solve this type of traffic problems. Fog computing is one of the most efficient paradigms for traffic system control as it enables connecting and analyzing big traffic data to help the control of traffic signals in the appropriate time. There are different optimization methods, which can be used to control traffic signal; one of these is Particle Swarm Optimization (PSO ) algorithm, and there is correlation between PSO parameters (particle velocity, position) and traffic …parameters (vehicle speed and location). Roundabouts with traffic signals is one of the modern roads infrastructures used to reduce traffic jam. Our objective is to minimize the average delay time in order to decrease the traffic congestion. This paper presents a control strategy called COTSD-PSO for optimizing traffic signaling based on PSO combined with three sub-controllers; this strategy depends on traffic control rules. These sub-controllers are PSO-Jump , PSO-Turn and PSO-Mix depend on two parameters; extension time and urgency degree for the different phases in the traffic cycle. PSO algorithm is applied to optimize the control of the traffic signal network for roundabouts model on fog computing environments using real data from Taif streets in KSA country. The PSO simulation results show that the PSO-Mix has the fastest convergence rate for the optimal solution and the best performance in minimizing the average delay time compared with the other combinations. Show more

Keywords: Fog computing, traffic control, particle swarm optimization, roundabout, extension time, urgency degree, delay time

DOI: 10.3233/JIFS-18077

Citation: Journal of Intelligent & Fuzzy Systems, vol. 36, no. 2, pp. 1401-1415, 2019

Authors: Wang, Weizhong | Liu, Xinwang | Qin, Jindong

Article Type: Research Article

Abstract: The Failure mode and effect analysis (FMEA) is an effective risk evaluation approach which has been widely used to assist in risk controlling in various workplaces. However, in practice, the conventional FMEA approach suffers from the drawbacks associated with the risk evaluation and priorization methods. In this paper, a novel risk priorization method for FMEA based on the extended MULTIMOORA (Multi-Objective Optimization by Ratio Analysis plus the Full Multiplicative Form) method is proposed. First, the interval type-2 fuzzy sets are applied to deal with the uncertainty of risk evaluation in FMEA. Second, the distance-based method is used to calculate the …importance weight of each risk factor. Then, an extended MULTIMOORA method is presented to rank risk priority of each failure mode, in which the distance measure for interval type-2 fuzzy number is incorporated. Finally, a practical case in steel company is selected to illustrate the application and feasibility of the proposed approach. A comparative analysis is conducted to demonstrate the effectiveness of the developed risk priorization method. Show more

Keywords: Failure mode and effect analysis, risk prioritization, interval type-2 fuzzy set, MULTIMOORA method

DOI: 10.3233/JIFS-181007

Citation: Journal of Intelligent & Fuzzy Systems, vol. 36, no. 2, pp. 1417-1429, 2019

Authors: Santhi, B. | Brindha, G.R.

Article Type: Research Article

Abstract: The exponential growth of Internet through sharing text content necessitates the analysis to convert them into useful information. The research areas such as Web mining, Opinion mining and Text mining focus on studies namely content mining, statistical analysis, prediction, and classification. Multinomial Naïve Bayes (MNB), the state of art of Bayesian classifier is the fastest and simplest text classifier. The objective of the proposed study is to enhance the classification by substituting the conditional probability of existing MNB with probability based frequency computation. A new combination that consists of Pointwise Mutual Information (PMI) and different normalized Term Frequency (TF) is …used for computing the conditional probability. The new combinations provide weight to the words based on the information gain carried by the words related to the document that belongs to a class. The robustness of Similarity based Enhanced Conditional Probability MNB (SECP-MNB) is reflected in classification accuracy measurement. Show more

Keywords: Text classification, conditional probability, multinomial Naïve Bayes, machine learning, pointwise mutual information

DOI: 10.3233/JIFS-181009

Citation: Journal of Intelligent & Fuzzy Systems, vol. 36, no. 2, pp. 1431-1441, 2019

Authors: Daneshpayeh, Roohallah | Borumand Saeid, Arsham | Mirvakili, Saeed

Article Type: Research Article

Abstract: In this paper, we intend to introduce the notion of the radical of a filter in a pseudo BL-algebra and express its characteristics and properties. We define dense, infinitesimal, nilpotent, and unity elements in a pseudo BL-algebra, and then, investigate the relationship between these elements and the radical in a pseudo BL-algebra. Our study revealed significant results in this regard.

Keywords: Pseudo BL-algebra, (Prime, Maximal) filter, Radical, (Dense, Infinitesimal, Nilpotent, Unity) element

DOI: 10.3233/JIFS-181039

Citation: Journal of Intelligent & Fuzzy Systems, vol. 36, no. 2, pp. 1443-1454, 2019

Authors: Yuguang, Zhong | Fan, Yang | Feng, Liu

Article Type: Research Article

Abstract: A new artificial bee colony algorithm called modified artificial bee colony algorithm (MABC) is presented to solve the multi-objective fuzzy flexible job-shop scheduling problem (MFFJSP) in this paper. The objectives of MFFJSP are to minimize the maximum fuzzy completion time (fuzzy makespan), maximize the weighted agreement index and minimize the maximum fuzzy machine workload. The three-point satisfaction-degree model is adopted to calculate the agreement index and this model can indicate the degree of satisfaction between the due date and the processing time. An effective local search operator based on variable neighborhood search (VNS) and crossover operator are embedded in this …algorithm for obtaining good searching performance. In order to make the novel algorithm valid, we texted it, five benchmark instances and a practical case for the sake of effectiveness. Then, the performance of the proposed MABC has been compared with other existing algorithms to prove the superiority of this algorithm. In the end, the Taguchi method is used to investigate the impact of three key parameters from the MABC. Show more

Keywords: Artificial bee colony algorithm, agreement index, variable neighborhood search, multi-objective fuzzy flexible job-shop scheduling problem

DOI: 10.3233/JIFS-181152

Citation: Journal of Intelligent & Fuzzy Systems, vol. 36, no. 2, pp. 1455-1473, 2019

Authors: Wang, Pei | Huang, Dan | Li, Zhaowen

Article Type: Research Article

Abstract: An information system as a database that represents relationships between objects and attributes is an important model in the field of artificial intelligence. A three-source information system of this paper is an information system where there exist three data: categorical, boolean and set-valued data. This paper explores uncertainty measurement for this kind of information system. The concept of a three-source information system is first described by means of set matrices. Then, information structures in a three-source information system are presented and relationships between information structures are studied from the two aspects of dependence and separation. Next, properties of information structures …in a three-source information system are given by using inclusion degree. Finally, as an application for information structures, uncertainty measurement for a three-source information system are investigated by means of its information structures. These results will be helpful for understanding the essence of uncertainty in a three-source information system. Show more

Keywords: Three-source information system, information structure, dependence, inclusion degree, entropy, uncertainty, measurement

DOI: 10.3233/JIFS-181199

Citation: Journal of Intelligent & Fuzzy Systems, vol. 36, no. 2, pp. 1475-1490, 2019

Authors: Karaşan, Ali | Boltürk, Eda | Kahraman, Cengiz

Article Type: Research Article

Abstract: Combinative Distance-based Assessment (CODAS) method aims at selecting the best alternative having the largest distance to the negative-ideal point based on the Euclidean distance as the primary and the Taxicab distance as the secondary measure. Uncertainty is generally an unavoidable issue in real life problems, which can be tackled by various approaches that may be stochastic or fuzzy. Neutrosophic sets theory is an ultimate extension of ordinary fuzzy sets and neutrosophic sets are the superset of intuitionistic fuzzy sets. This paper develops a novel interval-valued neutrosophic CODAS method and presents comparative analyses with crisp and ordinary fuzzy CODAS methods. Together …with comparative analyses, a sensitivity analysis is also given for the selection problem among wind energy plant locations. Show more

Keywords: CODAS, interval-valued neutrosophic fuzzy, renewable energy, decision making, location selection

DOI: 10.3233/JIFS-181255

Citation: Journal of Intelligent & Fuzzy Systems, vol. 36, no. 2, pp. 1491-1504, 2019

Authors: Zhang, Leibao | Fan, Yanli | Zhang, Wenyu | Zhang, Shuai | Yu, Dejian | Zhang, Shuai

Article Type: Research Article

Abstract:  Quantitative methods for determining the quality of scientific publications evolved gradually from popularity methods to prestige methods. However, existing methods have some drawbacks, such as inability to account for important factors and mutual reinforcement between different entities, and limitation of using novel information techniques like artificial intelligence (AI) methods. This study proposes an intelligent time-aware mutual reinforcement ranking (TAMRR) model that accounts for mutual reinforcement, and temporal factors, such as the time of citation, to measure the prestige of scientific papers. The method also considers the distribution of the co-authors’ contributions, which indicates the credit allocation of citations. Moreover, mutual …reinforcement which indicates interactive impact between different entities by means of the extension of an AI algorithm, i.e., Hyperlink-Induced Topics Search (HITS) algorithm, is adopted to further explore the interactions of papers, journals and authors. Another AI algorithm, i.e., PageRank, is also enhanced to measure the prestige of papers, journals, and authors in citation networks, which are then used as the inputs to the modified HITS. Experiments on temporal factors and heterogeneous networks reveal that these factors are likely to be informative in prestige measurements. Analysis of correlations suggests that our proposed intelligent ranking method is reasonable. This study offers an intelligent method for researchers, authors, and entrepreneurs to quantify the importance of scientific papers and the conclusions are likely to be of importance for researchers in both the academic and enterprise domains. Show more

Keywords: Scientific prestige of papers, artificial intelligence, citation networks, time-aware, PageRank, HITS, mutual reinforcement

DOI: 10.3233/JIFS-181438

Citation: Journal of Intelligent & Fuzzy Systems, vol. 36, no. 2, pp. 1505-1519, 2019

Authors: Ji, Jinchao | Chen, Yongbing | Feng, Guozhong | Zhao, Xiaowei | He, Fei

Article Type: Research Article

Abstract: Data objects with both numeric and categorical attributes are prevalent in many real-world applications. However, most of the partitional clustering algorithms dealing with such data may trap into local optima. To further promote the performance, a novel clustering algorithm, called ABC-K-Prototypes (Artificial Bee Colony clustering based on K-Prototypes), is presented on the basis of the K-Prototypes algorithm, the search strategy of the artificial bee colony, and the chaos theory. In the presented approach, the one-step k-prototypes procedure is first given, and then this procedure is combined with the search strategy of the artificial bee colony to address the mixed numeric …and categorical data. In the search process of scout bees, the chaotic map is utilized to generate chaotic sequences for substituting the random numbers. To accelerate the convergence of the ABC-K-Prototypes algorithm, the multi-source search is adopted in the search process of scout bees. Finally, the performance of the ABC-K-Prototypes algorithm is demonstrated by a series of experiments on mixed numeric and categorical data in comparison with that of the other popular algorithms. Show more

Keywords: Clustering, numeric attribute, categorical attribute, mixed data, artificial bee colony

DOI: 10.3233/JIFS-18146

Citation: Journal of Intelligent & Fuzzy Systems, vol. 36, no. 2, pp. 1521-1530, 2019

Authors: Kanwal, Shazia | Azam, Akbar

Article Type: Research Article

Abstract: The main focus of the present paper is to establish a common coincidence point theorem for a pair of L -fuzzy mappings and a non-fuzzy mapping under a generalized φ -contractive condition on a metric space in association with the Hausdorff distance on a class of L -fuzzy sets. A generalized common coincidence point theorem with the d L ∞ metric on 1- cuts of L -fuzzy sets is also obtained, which generalizes many recent results in literature. As applications, an analogous coincidence point theorem for crisp mappings is achieved to study some existence …theorems of solution for a class of nonlinear integral equations. Even as direct application of coincidence of L - fuzzy mappings, an implicit function theorem is established which can be used to find an explicit restriction of a given implicit relation. For verification and elaboration of our results some interesting and non-trivial examples are presented as well. Show more

Keywords: Coincidence point, implicit function theorem, L-fuzzy mapping, integral equation

DOI: 10.3233/JIFS-181754

Citation: Journal of Intelligent & Fuzzy Systems, vol. 36, no. 2, pp. 1531-1545, 2019