Journal of Intelligent & Fuzzy Systems - Volume 34, issue 4

Authors: Beheshti, Maedeh | Ashapure, Akash | Rahnemoonfar, Maryam | Faichney, Jolon

Article Type: Research Article

Abstract: Accurate segmentation of fluorescence images has become increasingly important for recognizing cell nucleus that have the phenotype of interest in biomedical applications. In this study an ensemble based method is proposed for the segmentation of cell cancer microscopy images. The ensemble is constructed and compared using Bayes graph-cut algorithm, binary graph-cut algorithm, spatial fuzzy C-means, and fuzzy level set algorithm, which were chosen for their accuracy and efficiency in the segmentation area. We investigate the performance of each method separately and finally compare the results with the ensemble method. Experiments are conducted over two datasets with different cell types. At …95% confidence level, the ensemble based method represents the best among all the implemented algorithms. Also ensemble method depicts better results in comparison with other state-of-the-art segmentation methods. Show more

Keywords: Bayes graph-cut models, image segmentation, ensemble methods, fluorescence microscopy images, spatial fuzzy c-means

DOI: 10.3233/JIFS-17466

Citation: Journal of Intelligent & Fuzzy Systems, vol. 34, no. 4, pp. 2563-2578, 2018

Authors: Ju, Dawei | Ju, Yanbing | Wang, Aihua

Article Type: Research Article

Abstract: Maclaurin symmetric mean (MSM) operator is a powerful tool to integrate multiple input arguments, which has the characteristic of considering the interrelationships among the input arguments. In this paper, we extend the traditional MSM operator to the single-valued neutrosophic interval 2-tuple linguistic environment, propose some novel aggregation operators, and develop a novel method to solve multiple attribute group decision making (MAGDM) problems. Firstly, we put forward the concept of single-valued neutrosophic interval 2-tuple linguistic sets (SVN-ITLSs) by combining the definitions of single-valued neutrosophic sets and interval 2-tuple. Secondly, the Maclaurin symmetric mean is extended to the single-valued neutrosophic interval 2-tuple …linguistic environment and three new aggregation operators are proposed, such as the single-valued neutrosophic interval 2-tuple linguistic Maclaurin symmetric mean (SVN-ITLMSM) operator, the single-valued neutrosophic interval 2-tuple linguistic weighted average (SVN-ITLWA) operator and the single-valued neutrosophic interval 2-tuple linguistic weighted Maclaurin symmetric mean (SVN-ITLWMSM) operator. Some desirable properties of the proposed SVN-ITLMSM operator are investigated. Thirdly, an approach to solve MAGDM problem is developed based on the proposed operators. Finally, a numerical example is given to illustrate the application and the effectiveness of the proposed method. Show more

Keywords: Multiple attribute group decision making, single-valued neutrosophic interval 2-tuple linguistic sets, single-valued neutrosophic interval 2-tuple linguistic Maclaurin symmetric mean (SVN-ITLMSM) operator, single-valued neutrosophic interval 2-tuple linguistic weighted Maclaurin symmetric mean (SVN-ITLWMSM) operator

DOI: 10.3233/JIFS-17496

Citation: Journal of Intelligent & Fuzzy Systems, vol. 34, no. 4, pp. 2579-2595, 2018

Authors: Onar, Serkan | Yavuz, Sanem | Ersoy, Bayram Ali | Hila, Kostaq

Article Type: Research Article

Abstract: In this paper, the study of vague soft structures of modules is initiated by introducing the concepts of vague soft module, vague soft module homomorphism and vague soft exactness. In the meantime, some of their properties and structural characteristics are investigated and discussed. Thereafter, several illustrative examples are given.

Keywords: Soft set, vague set, vague soft set, soft module, vague soft module, vague soft module homomorphism, vague soft exactness

DOI: 10.3233/JIFS-17497

Citation: Journal of Intelligent & Fuzzy Systems, vol. 34, no. 4, pp. 2597-2609, 2018

Authors: Tan, Chunqiao | Yi, Wentao | Chen, Xiaohong

Article Type: Research Article

Abstract: Players are often assumed to be perfect rational in Bertrand game. However, the decision-making of players is influenced by their behavioral characteristic, psychology preferences and other uncertain factors. Therefore, this paper focuses on investigating the price strategies of players with risk aversion in a Bertrand game under a fuzzy environment. Based on the credibility theory, a fuzzy Bertrand game model with risk aversion is constructed, where optimistic value criterion is applied to model players’ risk aversion. The market demand for each player is assumed as a fuzzy variable. Then, a solution concept of the (α1 , α2 )-optimistic equilibrium price …is defined and investigated. Finally, some numerical studies are applied to analyze how the risk aversion behavior of players (the confidence levels of players) affects the (α1 , α2 )-optimistic equilibrium prices and the profits of the fuzzy Bertrand game. Show more

Keywords: Bertrand game, risk aversion, credibility theory, optimistic value criterion, (α1 , α2)-optimistic equilibrium price

DOI: 10.3233/JIFS-17551

Citation: Journal of Intelligent & Fuzzy Systems, vol. 34, no. 4, pp. 2611-2624, 2018

Authors: Chang, Kuei-Hu | Wen, Ta-Chun | Chung, Hsiang-Yu

Article Type: Research Article

Abstract: Risk assessment is a critical part of reliability engineering and is vital to the success of an enterprise’s performance. Traditionally, risk assessment has used the risk priority number (RPN) to evaluate the risk of failure. Unfortunately, the traditional RPN method has several shortcomings— it loses partially valuable information when some data are missing or nonexistent and does not consider the ordered weight between the severity, occurrence, and detection indicators; further, it does not consider the direct and indirect relationships between failure modes and causes of failure, and it has a high duplication rate. To resolve these issues, this paper integrates …the ordered weighted geometric (OWG) operator and hesitant fuzzy linguistic term sets to increase the effectiveness of failure mode and effects analysis (FMEA), named soft FMEA. An empirical case of extreme low-k (ELK) dielectric integration is used to illustrate the proposed method and demonstrate its value. Our results show that the soft FMEA method is applicable to real-world situations and constitutes a more general FMEA method. Show more

Keywords: Soft failure mode and effects analysis, ordered weighted geometric, decision making trial and evaluation laboratory, extreme low-k dielectric integration, hesitant fuzzy linguistic term sets

DOI: 10.3233/JIFS-17594

Citation: Journal of Intelligent & Fuzzy Systems, vol. 34, no. 4, pp. 2625-2639, 2018

Authors: Wang, Yansheng | Jin, Zhixin | Deng, Cunbao | Wang, Xinyang

Article Type: Research Article

Abstract: In order to make the comprehensive decision-making results more consistent with the actual situation, a fuzzy comprehensive decision-making model with fuzzy combined weighting is developed in this paper. The fuzzy combined weighting method (FCWM) is proposed in the model to determine the weights of decision factors (indexes). The subjective weight and objective weight are combined in the FCWM to reduce the decision error caused by either using subjective weight or objective weight alone. In addition, the fuzziness of combined weights is taken into account in FCWM to make the decision-making results more realistic. The fuzzy structured element is used to …express fuzzy numbers in the model. The analysis algorithm of fuzzy comprehensive decision based on the expression of fuzzy structured element is given to solve the problem of complex operations among fuzzy numbers. The decision model was applied to the order of metal mine gob management. It provides guidance for gob management reasonably and orderly. The research results also provide a new idea for the determination of weights in other fuzzy analysis models. Show more

Keywords: Fuzzy comprehensive decision-making, fuzzy combined weighting, fuzzy structured element theory, order of gob management

DOI: 10.3233/JIFS-17700

Citation: Journal of Intelligent & Fuzzy Systems, vol. 34, no. 4, pp. 2641-2649, 2018

Authors: Marjanian, Ali | Soleymani, Soodabeh

Article Type: Research Article

Abstract: The complexity of power system stability studies, especially voltage stability considering dynamic loading margin based on Hopf bifurcation and reactive loading margin based on limit-induced bifurcation, challenges the conventional methods the effectiveness of which highly depends on the operating point, particularly the load level. The occurrence of reactive limit causes changes in the stability boundaries of power systems and, in some cases, leads to instability. In the current study, an attempt was made to investigate dynamic loading margin (DLM) and reactive loading margin (RLM) as well as their effects on the occurrence of bifurcation points of power systems. Also, the …states in which these bifurcations occur relative to each other are explained. Finally, in accordance with the results, a classification model for the identification of the operating point states of the power system is introduced. The purpose of presenting this classification is to determine the operational condition of power systems based on the mentioned boundaries without solving dynamic algebraic equations. To that end, an approach consisting of the phasor measurement unit (PMU) data acquisition, feature selection, and probabilistic neural network (PNN) is proposed to predict the power system voltage stability state. The effectiveness of the proposed strategy is shown on the New-England test system in normal and contingency states. Show more

Keywords: Hopf bifurcation, dynamic loading margin (DLM), limit induced bifurcation, reactive loading margin (RLM), phasor measurement units (PMUs), probabilistic neural network (PNN)

DOI: 10.3233/JIFS-17763

Citation: Journal of Intelligent & Fuzzy Systems, vol. 34, no. 4, pp. 2651-2666, 2018

Authors: Aghabozorgi, Farshad | Reza Khayyambashi, Mohammad

Article Type: Research Article

Abstract: Link prediction is the problem of inferring future interactions among existing network members based on available knowledge. Computing similarity between a node pair is a known solution for link prediction. This article proposes some new similarity measures. Some of them use nodes’ recency of activities, some weights of edges and some fusion of both in their calculation. A new definition of recency is provided here. A supervised learning method that applies a range of network properties and nodes similarity measures as its features set is developed here for experiments. The results of the experiments indicate that using proposed similarity measures …would improve the performance of the link prediction. Show more

Keywords: Link prediction, supervised learning, recency, similarity measures, social networks

DOI: 10.3233/JIFS-17770

Citation: Journal of Intelligent & Fuzzy Systems, vol. 34, no. 4, pp. 2667-2678, 2018

Authors: Cayir Ervural, Beyzanur | Ervural, Bilal

Article Type: Research Article

Abstract: Optimal energy planning is one of the most significant issues for all over the world, in short, medium and long term strategic projections of countries due to the vagueness and concerns about energy reliability and sustainability in limited resources. The dynamic and chaotic nature of the energy systems requires a well-constructed and multidimensional prediction model to create an urgent energy requirement planning. In this study, grey prediction models based on genetic algorithm (GA) and particle swarm optimization (PSO) are proposed to provide more realistic and quick energy demand forecasting with high accuracy. The grey modelling is a popular approach that …can be used to construct a model with the limited sample of historical data. GA and PSO are used for the tuning of an optimal set of structural parameters of classical grey prediction model to obtain more robust and efficient solutions with minimum prediction errors. A case study using the data of Turkey is presented. Results confirm that the proposed methods demonstrate superior forecasting performance, compared with alternative models. Show more

Keywords: Energy planning, forecasting, grey modelling, genetic algorithm, particle swarm optimization

DOI: 10.3233/JIFS-17794

Citation: Journal of Intelligent & Fuzzy Systems, vol. 34, no. 4, pp. 2679-2688, 2018

Authors: Javed, Muhammad Aslam | Husnine, Syed Muhammad | Ashraf, Samina

Article Type: Research Article

Abstract: In crisp logic every object is similar to itself with degree of reflexivity 1, while the degree of reflexivity in fuzzy logic can be any value in the unit interval, [0, 1]. This behaviour of a fuzzy set is used to enlighten the concept of similarity and inclusion measures. This paper is aimed at discovering the relations between the parameters of the transitive members of a family of cardinality-based fuzzy measure.

Keywords: Cardinality based similarity measures, T-transitivity, fuzzy reflexive measures

DOI: 10.3233/JIFS-17827

Citation: Journal of Intelligent & Fuzzy Systems, vol. 34, no. 4, pp. 2689-2706, 2018