Journal of Intelligent & Fuzzy Systems - Volume 35, issue 1

Authors: Nongmeikapam, Kishorjit | Kumar, Wahengbam Kanan | Khumukcham, Ranita | Singh, Aheibam Dinamani

Article Type: Research Article

Abstract: The traditional Fuzzy C-means (FCM) has been adopted worldwide to perform different kinds of image segmentation. However, owing to the fact that it is very susceptible to noise and other image artifacts, its usage is no longer a priority in the constantly changing real world application. The motivation of this paper is to propose a robust & unsupervised Image Segmentation framework known as GIFMRCM for enhancing the underlying delicate architectures of the human brain with ease. GIFMRCM introduces a new objective function by utilising a degree of mutual connectivity factor between pixels and the center. The manuscript can be broken …up into two major constituents - Image Segmentation using GIFMRCM, and Cluster-wise color space representation of the GIFMRCM image using k-means hard clustering approach in a CIE L*a*b* color space. Experimentation on medical images shows that the proposed algorithm can improve the performance of image segmentation, and remove noise efficiently. The cluster-wise feature extraction procedure proposed in this paper is also able to extract delicate regions of human brain with ease. Show more

Keywords: Image segmentation, GIFMRCM, mutual connectivity, objective function, CIE L*a*b* color space

DOI: 10.3233/JIFS-17968

Citation: Journal of Intelligent & Fuzzy Systems, vol. 35, no. 1, pp. 1147-1160, 2018

Authors: Guo, Xiaobin | Wei, Yuan | Li, Zhouzhou

Article Type: Research Article

Abstract: A numerical procedure for calculating the inverse of LR fuzzy numbers matrix is designed and a sufficient condition for the existence of fuzzy inverse is derived. As a application, the paper considers the solution of fully fuzzy linear systems by the approximate fuzzy inverse. Some examples are given to illustrate the proposed method.

Keywords: LR fuzzy numbers, matrix analysis, fuzzy inverse matrix, fully fuzzy linear systems

DOI: 10.3233/JIFS-18027

Citation: Journal of Intelligent & Fuzzy Systems, vol. 35, no. 1, pp. 1161-1168, 2018

Authors: Samanta, Aniruddha | Basu, Kajla

Article Type: Research Article

Abstract: Reliability optimization and availability optimization are two classes of optimization problems in redundancy allocation problem (RAP). Contrary to reliability optimization, very few researchers have focused on availability optimization to find out the optimal redundancy. This paper proposes a multi-objective optimization problem of availability allocation in a series-parallel system with repairable components. The two objectives are maximizing the system availability and minimizing the total cost of the system. In real life situation, due to complexity of the systems and non-linearity of their behaviour, most of the data are usually uncertain and imprecise. Hence in order to make the model more reliable, …fuzzy theory has been introduced in terms of triangular data for handling the uncertainties. Thus in fuzzy environment a fuzzy multi-objective availability allocation problem is formulated. In order to solve the problem a crisp optimization problem has been reformulated using fuzzy programming technique and finally an attraction based particle swarm optimization (APSO) has been proposed to solve this crisp optimization problem. The proposed APSO is compared with the traditional Particle swarm optimization(PSO) to show the efficiency and consistency of the proposed approach. Based on a numerical example,the statistical analysis of the experimental results establish that the proposed APSO has a better and consistent performance compared to traditional PSO. Show more

Keywords: Series-Parallel System, availability allocation problem, fuzzy programming technique, Attraction based particle swarm optimization (APSO)

DOI: 10.3233/JIFS-18029

Citation: Journal of Intelligent & Fuzzy Systems, vol. 35, no. 1, pp. 1169-1178, 2018

Authors: Liu, Caihui | Pedrycz, Witold | Qian, Jin | Wang, Meizhi

Article Type: Research Article

Abstract: Multigranulation decision-theoretic rough sets (MDTRS) is a model for real-world decision making. In various existing optimistic MDTRS models, the lower and upper approximations are defined based on the strategy seeking commonality while preserving differences , while pessimistic MDTRS models based on the strategy Seeking commonality while eliminating differences in the definitions of approximations. In real-world problems, one may need different strategies in defining lower approximations and upper approximations. This paper proposes two new MDTRS approaches in the frameworks of multi-covering approximation spaces by using different strategy in defining lower and upper approximations, namely, covering-based optimistic-pessimistic multigranulation decision-theoretic rough sets …and covering-based pessimistic-optimistic multigranulation decision-theoretic rough sets, respectively. We explore a number of basic properties of the proposed models. Then, we elaborate on the relationship between the proposed models and the existing ones in the literature. And we also disclose the interrelationships of the proposed models. Finally, we provide a case study to demonstrate the effectiveness of the proposed models. Show more

Keywords: Covering, decision-theoretic rough set, multigranulation, three way decisions

DOI: 10.3233/JIFS-18233

Citation: Journal of Intelligent & Fuzzy Systems, vol. 35, no. 1, pp. 1179-1191, 2018

Authors: Jia, Lifen | Yang, Xiangfeng | Gao, Xin

Article Type: Research Article

Abstract: This paper proposes a new definition of cross entropy for uncertain random variables, and derives a formula. Moreover, this paper introduces generalized cross entropy for uncertain random variables, and discusses its properties. Based on the definition of cross entropy, a cross entropy chance distribution model of degree-constrained minimum spanning tree (DCMST) problem is proposed. An algorithm is designed here to solve the model. Finally, a numerical example is provided to illustrate the effectiveness of the proposed model and algorithm.

Keywords: Cross entropy, uncertain random variable, minimum spanning tree, uncertain random network

DOI: 10.3233/JIFS-18268

Citation: Journal of Intelligent & Fuzzy Systems, vol. 35, no. 1, pp. 1193-1204, 2018