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

Authors: Fu, Xin | Zeng, Xiao-Jun | Wang, Di | Xu, Di | Yang, Longzhi

Article Type: Research Article

Abstract: With the emergence of customisation services, business-to-business price negotiation plays an increasingly important role in economic and management science. Negotiation pricing aims to provide different customers with products/services that perfectly meet their requirements, with the “right" price. In general, pricing managers are responsible for identifying the “right" negotiation price with the goal of maintaining good customer relationship, while maximising profits for companies. However, efficiently and effectively determining the “right" negotiation price boundary is not a simple task; it is often complicated, time-consuming and costly to reach a consensus as the task needs to take a wide variety of pricing factors …into consideration, ranging from operation costs, customers’ needs to negotiation behaviours. This paper proposes a systematic fuzzy system (FS) approach, for the first time, to provide negotiation price boundary by learning from available historical records, with a goal to release the burden of pricing managers. In addition, when the number of involved influencing factors increases, conventional FS approach easily suffers from the curse of dimensionality. To combat this problem, a novel method, simplified FS with single input and single output modules (SFS-SISOM), is also introduced in this paper to handle high-dimensional negotiation pricing problems. The utility and applicability of this research is illustrated by three experimental datasets that vary from both data dimensionality and the number of training records. The experimental results obtained from two approaches have been compared and analysed based on different aspects, including interpretability, accuracy, generality and applicability. Show more

Keywords: Negotiation pricing, decision support system, fuzzy systems, curse of dimensionality

DOI: 10.3233/IFS-141410

Citation: Journal of Intelligent & Fuzzy Systems, vol. 29, no. 2, pp. 685-699, 2015

Authors: Liu, Peide | Teng, Fei

Article Type: Research Article

Abstract: The intuitionistic uncertain linguistic variables are the good tools to express the fuzzy information, and the TODIM (an acronym in Portuguese of Interactive and Multicriteria Decision Making) method can consider the bounded rationality of decision makers based on the prospect theory. However, the classical TODIM method can only process the multiple attribute decision making (MADM) problems where the attribute values take the form of crisp numbers. In this paper, we will extend the TODIM method to the multiple attribute group decision making (MAGDM) with intuitionistic uncertain linguistic information. Firstly, the definition, characteristics, expectation, comparison method and distance of intuitionistic uncertain …linguistic variables are briefly introduced, and the steps of the classical TODIM method for MADM problems are presented. Then, on the basis of the classical TODIM method, the extended TODIM method is proposed to deal with MAGDM problems with intuitionistic uncertain linguistic variables, and its significant characteristic is that it can fully consider the decision makers’ bounded rationality which is a real action in decision making. Finally, an illustrative example is proposed to verify the developed approach. Show more

Keywords: TODIM method, intuitionistic uncertain linguistic information, multiple attribute group decision making, prospect theory

DOI: 10.3233/IFS-141441

Citation: Journal of Intelligent & Fuzzy Systems, vol. 29, no. 2, pp. 701-711, 2015

Authors: Allouche, Moez | Chaabane, Mohamed | Souissi, Mansour | Tadeo, Fernando | Mehdi, Driss

Article Type: Research Article

Abstract: The sensor faults in the induction motor can cause the degradation of the performances of the system and even lead sometimes to the instability. This paper focuses on the design of a state space fuzzy observer that simultaneously estimate descriptor system states and sensor faults. By using the estimates of descriptor states and faults, and the linear matrix inequality (LMI) technique, a fault-tolerant control scheme is worked out. The developed approach takes into account the stability of the closed-loop system and the design of non-linear fuzzy inference systems based on TakagiSugeno (TS) fuzzy models. The TS fuzzy model is employed …to approximate the nonlinear induction motor in the synchronous d-q frame rotating with field-oriented technique. The output fuzzy controller is able to maintain the damaged system at some acceptable level of performance even in the intermittent loss of sensor measurement signal. The gains of the observer and the controller are obtained by solving a set of Linear Matrix Inequalities (LMIs). Finally, simulation and experimental results are given to illustrate the effectiveness of the proposed approach. Show more

Keywords: Induction motor, sensor faults, TakagiSugeno model, descriptor observer, linear matrix inequalities LMIs

DOI: 10.3233/IFS-141447

Citation: Journal of Intelligent & Fuzzy Systems, vol. 29, no. 2, pp. 713-723, 2015

Authors: Liu, Dun-Nan

Article Type: Research Article

Abstract: In this paper, we investigate the multiple attribute decision making problems based on the hesitant fuzzy linguistic sets and Bonferroni mean operator with hesitant fuzzy linguistic information. Then, we have developed some aggregation operators for aggregating hesitant fuzzy linguistic information: hesitant fuzzy linguistic Bonferroni mean (HFLBM) operator and hesitant fuzzy linguistic weighted Bonferroni mean (HFLWBM) operator. Then, we have utilized these operators to develop some approaches to solve the hesitant fuzzy linguistic multiple attribute decision making problems. Finally, a practical example for evaluating the electrical power system safety is given to verify the developed approach.

Keywords: Multiple attribute decision making, hesitant fuzzy linguistic values, hesitant fuzzy linguistic weighted Bonferroni mean (HFLWBM) operator, electrical power system, safety evaluation

DOI: 10.3233/IFS-141462

Citation: Journal of Intelligent & Fuzzy Systems, vol. 29, no. 2, pp. 725-730, 2015

Authors: Su, Zhan | Xu, Zeshui | Liu, Haifeng | Liu, Shousheng

Article Type: Research Article

Abstract: Dual hesitant fuzzy set (DHFS) is a very comprehensive set which includes fuzzy set, intuition fuzzy set and hesitant fuzzy set as its special cases. Distance and similarity measures play great roles in many areas, such as decision making, pattern recognition, etc. In this paper, we introduce some distance and similarity measures for DHFSs based on Hamming distance, Euclidean distance and Hausdorff distance. Two examples are used to illustrate these distance and similarity measures and their applications in pattern recognition. Finally, the comparisons among DHFSs and the corresponding IVIFSs and HFSs are made in detail by utilizing the developed distance …measures. Show more

Keywords: Dual hesitant fuzzy set (DHFS), hesitant fuzzy set (HFS), distance measures, similarity measures, pattern recognition

DOI: 10.3233/IFS-141474

Citation: Journal of Intelligent & Fuzzy Systems, vol. 29, no. 2, pp. 731-745, 2015

Authors: Tao, Zhifu | Liu, Xi | Chen, Huayou | Liu, Jinpei

Article Type: Research Article

Abstract: The aim of this paper is to develop some measures of entropy for linguistic information and uncertain linguistic information. Based on some given functions with required monotonicity and some kinds of distance measures, we propose two groups of entropies of linguistic fuzzy sets and uncertain linguistic fuzzy sets, respectively. Then, as an application of the proposed entropy measures, we put forward two algorithms for obtaining the objective weight vector of attributes in multiple attributes decision making by utilizing the entropy weight approach and the maximum entropy method. Finally, two cases of subjective evaluation of the building environment are illustrated to …show the application of entropies for linguistic information in realworld. Show more

Keywords: Decision making, entropy, linguistic fuzzy sets, uncertain linguistic fuzzy sets, distance measures, subjective evaluation of building environment

DOI: 10.3233/IFS-141487

Citation: Journal of Intelligent & Fuzzy Systems, vol. 29, no. 2, pp. 747-759, 2015

Authors: Nayeem, Sk. Md. Abu

Article Type: Research Article

Abstract: This paper studies a purchasing EOQ inventory model with backordering, where setup cost, purchase cost, holding cost, shortage cost and demand quantity all are considered as independent fuzzy variables. Using a linear combination of possibility and necessity measures, the problem is formulated as a fuzzy expected value model. Then the crisp equivalent is derived when the fuzzy costs and demand are characterized by triangular fuzzy numbers. Finally, a numerical example is given to illustrate the effectiveness of the proposed algorithm.

Keywords: Inventory management, fuzzy cost, fuzzy demand, fuzzy expected value, possibility, necessity

DOI: 10.3233/IFS-141495

Citation: Journal of Intelligent & Fuzzy Systems, vol. 29, no. 2, pp. 761-767, 2015

Authors: Wang, Xia | Dang, Yaoguo

Article Type: Research Article

Abstract: With regard to multi-index decision-making problems, in which the index value of alternatives and weight are three-parameter interval grey number, a multi-index grey-target decision-making approach based on adjustment coefficient is proposed. First, considering that the resolution of index objective weights derived from entropy weighting method is not high, a normalized decision matrix method based on adjusting coefficient was proposed, and the optimizing entropy model was established to determine the index objective weights. Furthermore, the mean area method was applied to convert index subjective weights into real number, and the D-S (Dempster-Shafer) combination rule was utilized to integrate the subjective and …objective weights into comprehensive weights. Finally, the optimizing solution was determined via the size of positive target distance. An example is presented to illustrate the suitability and effectiveness of the obtained methods. Show more

Keywords: Three-parameter interval grey number, adjustment coefficient, grey-target decision-making, D-S theory of evidence

DOI: 10.3233/IFS-141498

Citation: Journal of Intelligent & Fuzzy Systems, vol. 29, no. 2, pp. 769-775, 2015

Authors: Zhen, Shengchao | Huang, Kang | Sun, Hao | Zhao, Han | Chen, Ye-Hwa

Article Type: Research Article

Abstract: A novel and systematic approach for dynamic modeling and approximate constraint-following servo control of constrained mechanical systems under uncertainty is proposed. Fundamental equation of constrained mechanical systems is first obtained based on Udwadia-Kalaba approach which is applicable to holonomic and nonholonomic constrained systems no matter whether they satisfy the D’Alember’s principle. The uncertainty (possibly fast time-varying) in mechanical systems is bounded and the bound is unknown. Fuzzy set theory is used to describe the unknown bound. The performance requirement is modeled as servo constraints in second-order form. A model-based robust control is presented to approximately follow the servo constraints. The …proposed control is deterministic and is not IF-THEN rules-based. The uniform boundedness and uniform ultimate boundedness of the tracking error are guaranteed, regardless of the uncertainty. A performance index (the combined cost, which includes average fuzzy system performance and control effort) is proposed based on the fuzzy information. The optimal design problem associated with the control can then be solved (explicitely or numerically) by minimizing the performance index. The resulting control design is systematic and is able to guarantee the deterministic performance as well as minimizing the cost. Show more

Keywords: Mechanical system, fundamental equation, constraint, robust control, coordinated robot

DOI: 10.3233/IFS-151545

Citation: Journal of Intelligent & Fuzzy Systems, vol. 29, no. 2, pp. 777-789, 2015

Authors: Niknam, Taher | Bagheri, Bahareh | Bonehkhater, Marzieh Mirzaei | Firouzi, Bahman Bahmani

Article Type: Research Article

Abstract: Distribution system state estimation (DSSE) is of vital importance to the monitoring and control of recent active distribution networks. This paper proposes a new teaching-learning-based optimization algorithm (TLBO) for estimating state variables of radial distribution systems. In this method, the state variables are estimated by minimizing the sum of weighted squared errors considering either real or pseudo measurements. TLBO is a successful recently-proposed optimization technique that simulates the educational system in a classroom. In this paper, an effective mutation has been incorporated into original TLBO algorithm to evade trapping in local minima and develop search process. Nevertheless, developing the search …process does not considerably lessen the speed of the algorithm. So the proposed method is an efficient algorithm for DSSE. Finally, the proposed method is studied on three radial distribution test systems. The numerical results have been depicted to demonstrate the efficiency and accuracy of the method for solving DSSE. Show more

Keywords: Distribution system state estimation, teaching-learning-based optimization algorithm (TLBO), single objective optimization algorithm

DOI: 10.3233/IFS-141579

Citation: Journal of Intelligent & Fuzzy Systems, vol. 29, no. 2, pp. 791-801, 2015