Journal of Intelligent & Fuzzy Systems - Volume 30, issue 1

Authors: Paul, Jaya | John, Sunil Jacob

Article Type: Research Article

Abstract: The purpose of this paper is to introduce the concept of type 2 fuzzy multiset by integrating the type 2 fuzzy set and multiset models. Basic set operations of union, intersection and complement are extended to type 2 fuzzy multisets and made a comparative study on various set theoretic laws satisfied by these operations with set theoretic operations on type 1 and type 2 fuzzy sets. The notion of (α, λ ) cut set is defined and some properties of cut sets are studied. Furthermore, we investigate the decision making based on type 2 fuzzy multisets. By means of (α, …λ ) cut sets, we propose an adjustable approach to type 2 fuzzy multiset based decision making. Moreover, we introduce the weighted type 2 fuzzy multiset and examine its application to decision making. Finally, by means of some illustrative examples we show the validity of type 2 fuzzy multiset, weighted type 2 fuzzy multiset in decision making problems. Show more

Keywords: Type 2 fuzzy multisets, cut fuzzy sets, choice value, weighted type 2 fuzzy multiset

DOI: 10.3233/IFS-151761

Citation: Journal of Intelligent & Fuzzy Systems, vol. 30, no. 1, pp. 359-369, 2016

Authors: Rashmanlou, Hossein | Borzooei, R.A.

Article Type: Research Article

Abstract: A vague graph is a generalized structure of a fuzzy graph that gives more precision, flexibility and compatibility to a system when compared with systems that are designed using fuzzy graphs. In this paper, we defined the notions of product and complete product vague graphs. We investigated some properties of union, join and complement on product vague graphs and introduced the multiplication of the product vague graphs. Finally we give an application of product vague graphs. Product and complete product vague graphs are highly utilized by computer science, geometry, algebra, number theory and operation research. Likewise, these properties will also …be helpful to study large vague graph as a combination of small, vague graphs and to derive its properties from those of the smaller ones. Show more

Keywords: Vague graphs, product vague graphs, multiplication of vague graphs

DOI: 10.3233/IFS-151762

Citation: Journal of Intelligent & Fuzzy Systems, vol. 30, no. 1, pp. 371-382, 2016

Authors: Guodong, Yu | Yu, Yang | Xi, Zhao | Liu-Aijun,

Article Type: Research Article

Abstract: Inevitable perturbations have a significant impact on collaborative production (CP) cause that the complexity are greatly increased. In order to assess the impact accurately enterprises to make precise decisions, it is prerequisite to master the dynamic behaviour of CP when changes occur. Accordingly, in this paper, an evolution model for simulating CP task state to perturbations is proposed. Regard CP tasks as a directed weighted complex network (DWCPTN) firstly, and statistical properties of DWCPTN are analysed. Two perturbation cases and two modifications policies are defined followed. Based on above mentioned, evolution model based on cellular automaton (CA) and SIS (Susceptible-Infected-Susceptible) …is presented to reveal the varying process by three indices (friction of resolved nodes, convergence time and economic behaviour). Finally, analytic results from a case of a chemical product CP network (CPNCP) are used to illustrate the model and method proposed in this paper. Simulation results shows that unplanned perturbations promote a negative role to CP but the improvements of self-healing can decrease the negative effects efficiently. With the analysis, it can provide insight into ways of improving the strategic and operational decision making for enterprises. Show more

Keywords: Collaborative production task network, evolution, unplanned perturbations, cellular automaton, SIS

DOI: 10.3233/IFS-151763

Citation: Journal of Intelligent & Fuzzy Systems, vol. 30, no. 1, pp. 383-396, 2016

Authors: Guodong, Yu | Yu, Yang | Aijun, Liu

Article Type: Research Article

Abstract: Changing customer requirements always poses a great challenge to designers in complex product design. Due to the complicated coupling relations between components, it is difficult to improve the efficiency of product reconfiguration. Therefore, this paper proposes a joint optimization model of complex product variant design responding to customer requirement changes. Based on synthesizing the advantages and deficiencies of “Scaled-based” and “Module-based”, a UB-BU hybrid approach is developed to improve the search efficiency and reduce conflicts. Then, a joint complex product variant design bi-level optimization to maximize customer satisfaction and minimum cost is established. As a solution, the genetic algorithm embedded …double iteration comparison rules (GA-DICR) is developed based on canonical genetic algorithm. Finally, the method and model are proved to be effective in the Clutch variant design. The results can provide way of allowing the decision-makers to respond rapidly to customer rudiments changes request. Show more

Keywords: Complex product variant design, customer requirement changes, joint optimization, bi-level programming, genetic algorithm

DOI: 10.3233/IFS-151764

Citation: Journal of Intelligent & Fuzzy Systems, vol. 30, no. 1, pp. 397-408, 2016

Authors: Shi, Fugui | Li, Erqiang

Article Type: Research Article

Abstract: In this paper, the notion of M -fuzzifying restricted hull operators is introduced and several equivalent characterizations are given. It is shown that there is a one-to-one correspondence between M -fuzzifying restricted hull operators and M -fuzzifying convex structures. As applications, some properties of the cut convex structures of an M -fuzzifying convex structure and of M -fuzzifying convexity preserving functions and of M -fuzzifying convex-to-convex functions are derived. In addition, using M -fuzzifying restricted hull operators, some M -fuzzifying convexities are naturally constructed from M -fuzzy quasi-orders.

Keywords: Convex structure, M-fuzzifying convex structure, M-fuzzifying restricted hull operator, M-fuzzifying betweenness

DOI: 10.3233/IFS-151765

Citation: Journal of Intelligent & Fuzzy Systems, vol. 30, no. 1, pp. 409-421, 2016

Authors: Xu, Changjin | Wu, Yusen

Article Type: Research Article

Abstract: In this paper, cellular neural networks(CNNs) with time-varying leakage delays on time scales are investigated. By applying the existence of the exponential dichotomy of linear dynamic equations on time scales, fixed point theorem and the theory of calculus on time scales, a set of sufficient conditions are obtained for the existence and exponential stability of almost automorphic solutions for the model. An example with its numerical simulations is given to illustrate the feasibility and effectiveness of the obtained results.

Keywords: Cellular neural networks, almost automorphic solution, exponential stability, leakage term, time-varying delay

DOI: 10.3233/IFS-151766

Citation: Journal of Intelligent & Fuzzy Systems, vol. 30, no. 1, pp. 423-436, 2016

Authors: Sambathkumar, B. | Nandakumar, P. | Dheena, P.

Article Type: Research Article

Abstract: In this study, using Yuan and Lee’s definition of fuzzy group based on fuzzy binary operation and Aktas and Cagman definition of fuzzy ring, we give a new kind of definition to (A  : B ). The concept of fuzzy regular and fuzzy left strongly regular are introduced and we create a new study on their basic properties equivalent to those of ordinary rings. We have shown that if (R , G , H ) is strongly regular, then for any a  ∈ R , left annihilator of “a ” is an ideal.

Keywords: Ring theory, regular rings, ideals, fuzzy algebraic structures

DOI: 10.3233/IFS-151767

Citation: Journal of Intelligent & Fuzzy Systems, vol. 30, no. 1, pp. 437-442, 2016

Authors: Wang, Guanjin | Choi, Kup-Sze | Deng, Zhaohong

Article Type: Research Article

Abstract: Fast Reduced set density estimator (FRSDE) is an important technique to realize the fast kernel density estimation based on the fast minimal enclosing ball (MEB) approximation technique. However, its performance on the running time is severely affected by the approximation parameter ɛ used in this algorithm, where a smaller value will lead to more accurate approximation but heavy learning burden. In this study, we reveal that the random Gaussian white noise manually added to the data will speed up the learning and accordingly propose a speedup version of FRSDE, i.e., the noise-benefit FRSDE (NB-FRSDE). NB-FRSDE can realize such a …speedup because a larger value of ɛ can be used on the noisy version of the original data to obtain the equivalent approximation performance, which only can be obtained by FRSDE on the original data with a smaller value of ɛ . The distinctive characteristics of NB-FRSDE exist in the following aspects: (1) its implementation is very simple because NB-FRSDE is the same as FRSDE except that there are Gaussian noises manually added to the original data in NB-FRSDE. (2) While most of the existing machine learning methods always try to remove the noise in order to overcome the influence of noise, NB-FRSDE benefits from the manually added noise in the sense of the average running time. The experimental studies on density estimation and its application to image segmentation demonstrate the above advantages. Show more

Keywords: Fast reduced set density estimator, minimal enclosing ball, core set, noise-benefit, NB-FRSDE

DOI: 10.3233/IFS-151768

Citation: Journal of Intelligent & Fuzzy Systems, vol. 30, no. 1, pp. 443-450, 2016

Authors: Huang, Meng-Tze | Lee, Ching-Hung | Lin, Chih-Min

Article Type: Research Article

Abstract: In this study, we present a technique for image encryption problem based on the underdetermined blind source separation (BSS) principle with adaptive learning rates. The encryption process is transferred as the underdetermined BSS problem and is treated by means of the key images to achieve decryption. By properly generating the key images and constructing the underdetermined mixing matrix, the proposed BSS technique can achieve the security. The proposed BSS with adaptive learning rates approach is implemented by the interval type-2 fuzzy cerebellar model articulation controller (T2FCMAC) and particle swarm optimization. The T2FCMAC system is a more generalized system with better …learning ability to provide the adaptive learning rate of the BSS. Besides, the particle swarm optimization is utilized to enhance the performance of convergence. Computer simulation results are shown to illustrate the effectiveness of the proposed approach. Show more

Keywords: Blind source separation, image encryption, fuzzy systems, particle swarm optimization

DOI: 10.3233/IFS-151769

Citation: Journal of Intelligent & Fuzzy Systems, vol. 30, no. 1, pp. 451-460, 2016

Authors: Wang, Junhua | Zhang, Lanfang | Lu, Siwen | Wang, Zhongren

Article Type: Research Article

Abstract: Based on a car following experiment with a synchronized fifth-wheel system, the Adaptive Neuro-Fuzzy Inference System (ANFIS) is utilized to develop a car following model. Wavelet analysis was used to denoise the high frequently collected fluctuating data. Drivers’ reaction time was calculated using Cross Correlation analysis. In the car-following model developed, relative speed, distance headway between leading and following vehicle, and speed of following vehicle are the three input parameters; while acceleration of the following vehicle is the output. Comparing with the traditional General Motor (GM) car-following model, the results show that the ANFIS-based car-following model can better describe the …freeway driving behavior. Show more

Keywords: Car-following, Adaptive Neuro-Fuzzy Inference, driver behavior, reaction time

DOI: 10.3233/IFS-151770

Citation: Journal of Intelligent & Fuzzy Systems, vol. 30, no. 1, pp. 461-466, 2016