Journal of Intelligent & Fuzzy Systems - Volume 29, issue 2

Authors: Hafezalkotob, Ashkan | Ghezavati, Vahid Reza

Article Type: Research Article

Abstract: We develop a distribution network model for a decentralized supply chain to investigate the optimal decisions of participants in an uncertain demand environment. The supply chain consists of one manufacturer and set of independent candidate distributors that distribute products to geographically dispersed markets in a competitive manner. All chain’s participants are assumed risk-sensitive. The stability of a distribution network depends on the fuzzy commitment of its distributors. The novelty of the paper lies in the manufacturer concerns about the preferences of the distributors to ensure stability of his distribution network. Hence, the manufacturer considers criteria of expected profit, variance of …profit, and stability level to evaluate distribution alternatives. A decision-making methodology is presented for evaluation and selection the distribution network design alternatives. The tactical decisions in each distribution alternative are obtained from a Stackelberg game formulated as a bi-level distributed programming problem. We show that the methodology is able to capture a principal trade-off between the preferences of manufacturer and contractor distributors. Managerial insights are obtained through an illustrative example and its sensitivity analyses. Show more

Keywords: Game theory, decentralized supply chain, bi-level distributed programming, distribution network design, demand uncertainty

DOI: 10.3233/IFS-151580

Citation: Journal of Intelligent & Fuzzy Systems, vol. 29, no. 2, pp. 803-815, 2015

Authors: Ashouri, Ahmad | Jalilvand, Abolfazl

Article Type: Research Article

Abstract: Considering the fact that the main part of electrical energy losses is related to the distribution level; therefore, controlling and monitoring of this part of the network is necessary to reduce energy losses which is made possible through distribution automation. Distribution automation systems need decision making regarding the responsibilities being performed by operators. On the other hand, there is the possibility of incorrect decision making by operators due to the large volume of information and decision making time shortage during automation steps which can be created by incorrect information received from the network and consequently causes the incorrect control command …sending to distribution network devices. Also, introducing the Distributed Generations (DGs) in the protection system of distribution network, it is possible for the protective devices to have an incorrect operation which affects the operators’ decisions performed by the automation system. In this paper, a new Petri-Net modeling method is used to make the distribution network monitoring and automation possible and also to help the operator in correct decision making. In addition, the protective devices’ operation is determined more reliably using the attained data from the automation system. Show more

Keywords: Distribution network, automation, Petri Nets, distributed generation, modeling

DOI: 10.3233/IFS-151602

Citation: Journal of Intelligent & Fuzzy Systems, vol. 29, no. 2, pp. 817-829, 2015

Authors: Zhou, Ligang | Zhou, Yuanyuan | Liu, Xi | Chen, Huayou

Article Type: Research Article

Abstract: The aim of this paper is to present some cases of the induced linguistic ordered weighted averaging (ILOWA) operator which are very suitable to deal with group decision making (GDM) problems with additive linguistic preference relations. We propose the relative consensus degree ILOWA (RCD-ILOWA) operator which uses the relative consensus degree (RCD) variable as the order inducing variable, and the compatibility index ILOWA (CI-ILOWA) operator which uses the compatibility index (CI) variable as the order inducing variable. We also investigate some desired properties of RCD-ILOWA operator and the CI-ILOWA operator which provide theoretic basis for the application of the additive …linguistic preference relations in GDM. A general formulation and a nonlinear model to determine experts’ weights and two approaches based on the RCD-ILOWA operator and the CI-ILOWA operator for GDM involving additive linguistic preference relations are developed respectively. A numerical example for comprehensive evaluation is given to illustrate the applications of the new operators. Show more

Keywords: Group decision making, additive linguistic preference relation, ILOWA operator, consistency, compatibility

DOI: 10.3233/IFS-151603

Citation: Journal of Intelligent & Fuzzy Systems, vol. 29, no. 2, pp. 831-843, 2015

Authors: Gómez-Acevedo, Horacio

Article Type: Research Article

Abstract: Separation of convex sets by hyperplanes has been extensively studied on crisp sets. In a seminal paper from L. A. Zadeh [1 ] separability and convexity are investigated, however there is a flaw on the definition of degree of separation. We revisited separation on convex fuzzy sets that have level-wise (crisp) disjointness with non-empty interior at certain level and introduced the concept of minimal level of separation for such fuzzy sets. On this context, the smallest level in which a separation by a hyperplane occurs coincides with the maximal degree of the (fuzzy) intersection. Moreover, this property suggests an algorithm …for finding the maximal grade of a (fuzzy) intersection based on hyperplane separability level-wise of fuzzy sets. Show more

Keywords: Basic concepts, fuzzy convexity, separation of convex fuzzy sets

DOI: 10.3233/IFS-151613

Citation: Journal of Intelligent & Fuzzy Systems, vol. 29, no. 2, pp. 845-849, 2015

Authors: Abbasi, F | Allahviranloo, T | Abbasbandy, S

Article Type: Research Article

Abstract: In this paper, we shall embark on the study of the algebraic object known as a fuzzy ring which serves as one of the fundamental building blocks for the subject which is called fuzzy abstract algebra. The acceptable definition of fuzzy ring and field are presented with binary operations and on the basis of the specified parameter, called ambiguity rank, which fulfils the basic requirements. The properties of these fuzzy rings and their fundamental qualities are discussed. We should like to stress that these fuzzy algebraic systems and their axioms, must come from the experience of looking at many examples. …Namely, they should be rich in meaningful results. Hence, the several illustrative examples are given. The future prospect of this paper is a new attitude to fuzzy basic mathematics, which will be referred to in the end. Show more

Keywords: Fuzzy par, fuzzy group, fuzzy field, ambiguity rank, transmission average (TA)

DOI: 10.3233/IFS-151615

Citation: Journal of Intelligent & Fuzzy Systems, vol. 29, no. 2, pp. 851-861, 2015

Authors: Mula, Prasanta | Roy, Sankar Kumar | Li, Deng-Feng

Article Type: Research Article

Abstract: This paper analyzes the bi-matrix games under the light of birough programming. The combination of bi-matrix games and birough programming produces a new form which is defined here as birough bi-matrix games. In birough bi-matrix games, the payoff elements are characterized by birough variables and uncertainty of the birough variable is measured by birough measure which known as Chance (Ch ). Utilizing the Chance measure, we have defined the expected birough Nash equilibrium strategy for the players which depends upon the confidence level and outcome of the birough bi-matrix game. In order to show the applicability and feasibility of our …proposed method, a real-life example on birough bi-matrix game is presented and then solved. Show more

Keywords: Bi-matrix game, birough variable, birough constraint, expected birough nash equilibrium strategy, genetic algorithm

DOI: 10.3233/IFS-151616

Citation: Journal of Intelligent & Fuzzy Systems, vol. 29, no. 2, pp. 863-875, 2015

Authors: Arivazhagan, S | Jebarani, W. Sylvia Lilly | Keerthinathan, S

Article Type: Research Article

Abstract: Data embedding in medical images require perfect reversibility with which the embedding distortions can be completely removed to achieve a high fidelity recovery of the cover images. Adaptive Pixel Pair Matching is a high capacity embedding scheme that allows data embedding in any desired larger notational system still achieving exact reconstruction of secret. The principle behind Extended Adaptive Pixel Pair Matching (EAPPM) is to use a pixel pair as the reference co-ordinate and select a co-ordinate in its neighbourhood set according to the secret digit, as the stego pixel pair using which the extraction function recovers the secret data. The …cover image is then reconstructed using the Look-Up Table (LUT) built with values of modulus distance. This reversibility can lead to multiple layer embedding, but cannot be fully exploited to increase the payloads as the usage of larger notational systems reduces the quality of the image. Hence this paper extends the APPM process to be performed over coefficients of the Transform domain in a repetitive fashion improving embedding capacity still maintaining high image quality as required for medical images. Show more

Keywords: Adaptive Pixel Pair Matching, reversible embedding, Integer Wavelet transform

DOI: 10.3233/IFS-151617

Citation: Journal of Intelligent & Fuzzy Systems, vol. 29, no. 2, pp. 877-883, 2015

Authors: Chatterjee, Rajashi | Majumdar, P | Samanta, SK

Article Type: Research Article

Abstract: In this paper the concept of type-2 soft sets has been introduced for the first time. Various operations are defined on them and their properties are studied. The notion of the image of a type-2 soft set under a mapping has been defined. An application of type-2 soft sets in the form of a decision making problem using the concept of type-2 weighted soft sets has been shown.

Keywords: Type 2 fuzzy set, soft set, weighted soft set, type-2 soft set, image of a type-2 soft set

DOI: 10.3233/IFS-151619

Citation: Journal of Intelligent & Fuzzy Systems, vol. 29, no. 2, pp. 885-898, 2015

Authors: Stańczyk, Urszula

Article Type: Research Article

Abstract: Rule classifiers enhance understanding of data and enable to represent learned knowledge in an explicit structural form. To further improve this understanding and generalisation properties of predictors, the process of selection of decision rules can be executed. The paper presents a post-processing approach to this task. In a proposed research framework there were exploited rankings of attributes the rules refer to, thus transferring the established importance of features to the rules based on them. The attributes were weighted by selected statistical measures and machine learning algorithms. The rule classifiers were constructed in Dominance-Based Rough Set Approach and employed in the …domain of stylometry for the task of authorship attribution. Show more

Keywords: Rule classifier, selection of rules, attribute ranking, stylometry, authorship attribution, DRSA

DOI: 10.3233/IFS-151620

Citation: Journal of Intelligent & Fuzzy Systems, vol. 29, no. 2, pp. 899-915, 2015

Authors: Jiang, Yizhang | Deng, Zhaohong | Choi, Kup-Sze | Qian, Pengjiang | Hu, Wenjun | Wang, Shitong

Article Type: Research Article

Abstract: Group probability classifier learning is an emerging and promising learning technique, especially in privacy-preserving data mining. It is used to train a classifier from a group probability dataset, where the class labels of each sample are unknown while the probabilities of each class in the given data groups of the whole dataset are available. The existing work is mainly based on the inverse calibration (IC) strategy to obtain the estimated labels for data in the group probability dataset and then make use of classical classification algorithms such as support vector machine (SVM) model to train the desired classifier. A critical …challenge of the exiting IC-based methods lies in the difficulty of designing an ideal IC function for label estimation and the methods are sensitive to the adopted IC function. In order to overcome this shortcoming, a novel probability transductive classifier that does not involve IC in the learning procedure is proposed, where the probability values are directly used as the output of the training data for the model training. Particularly, on the training data with the output being continuous real values, the existing classical regression model can be easily adopted to model the group probability classification problem. For a future testing data, the model output of the obtained group probability classification model can present the probability that the testing data belong to the positive class. With a given threshold, the final class label of the testing data can be obtained for the classification task. The experimental results on synthetic datasets and real UCI datasets show that the proposed method is more effective than the existing methods. Show more

Keywords: Privacy preserving, regression model, probability transductive, group probability, classification

DOI: 10.3233/IFS-151621

Citation: Journal of Intelligent & Fuzzy Systems, vol. 29, no. 2, pp. 917-925, 2015