Journal of Intelligent & Fuzzy Systems - Volume 24, issue 4

Authors: Huang, Rongqing | Sun, Shiliang

Article Type: Research Article

Abstract: Kernel regression is a popular non-parametric fitting technique. It aims at learning a function which estimates the targets for test inputs as precise as possible. Generally, the function value for a test input is estimated by a weighted average of the surrounding training examples. The weights are typically computed by a distance-based kernel function and they strongly depend on the distances between examples. In this paper, we first review the latest developments of sparse metric learning and kernel regression. Then a novel kernel regression method involving sparse metric learning, which is called kernel regression with sparse metric learning (KR_SML), is …proposed. The sparse kernel regression model is established by enforcing a mixed (2,1)-norm regularization over the metric matrix. It learns a Mahalanobis distance metric by a gradient descent procedure, which can simultaneously conduct dimensionality reduction and lead to good prediction results. Our work is the first to combine kernel regression with sparse metric learning. To verify the effectiveness of the proposed method, it is evaluated on 19 data sets for regression. Furthermore, the new method is also applied to solving practical problems of forecasting short-term traffic flows. In the end, we compare the proposed method with other three related kernel regression methods on all test data sets under two criterions. Experimental results show that the proposed method is much more competitive. Show more

Keywords: Kernel regression, sparse metric learning, mixed norm regularization, gradient descent algorithm, traffic flow forecasting

DOI: 10.3233/IFS-2012-0597

Citation: Journal of Intelligent & Fuzzy Systems, vol. 24, no. 4, pp. 775-787, 2013

Authors: Wei, Guiwu | Zhao, Xiaofei

Article Type: Research Article

Abstract: In this paper, we investigate the multiple attribute decision making (MADM) problems with hesitant interval-valued fuzzy information. We first introduce some operations on hesitant fuzzy sets, such as Einstein sum, Einstein product, Einstein exponentiation, etc., and propose the hesitant interval-valued fuzzy sets. Then, we further develop some new Einstein aggregation operators with hesitant interval-valued fuzzy information, such as the hesitant interval-valued fuzzy Einstein weighted average (HIVFEWA) operator, hesitant interval-valued fuzzy Einstein weighted geometric (HIVFEWG) operator, hesitant interval-valued fuzzy Einstein ordered weighted average (HIVFEOWA) operator, hesitant interval-valued fuzzy Einstein ordered weighted geometric (HIVFEOWG) operator, induced hesitant interval-valued fuzzy Einstein ordered weighted …averaging (I-HIVFEOWA) operator and induced hesitant interval-valued fuzzy Einstein ordered weighted geometric (I-HIVFEOWG) operator. Then, we apply the induced hesitant interval-valued fuzzy Einstein ordered weighted averaging (I-HIVFEOWA) operator and induced hesitant interval-valued fuzzy Einstein ordered weighted geometric (I-HIVFEOWG) operator to deal with multiple attribute decision making under the hesitant interval-valued fuzzy environments. Finally, an illustrative example is given to verify the developed approach and to demonstrate its practicality and effectiveness. Show more

Keywords: Multiple attribute decision making (MADM), hesitant interval-valued fuzzy values, Einstein aggregation operators, induced hesitant interval-valued fuzzy Einstein ordered weighted averaging (I-HIVFEOWA) operator, induced hesitant interval-valued fuzzy Einstein ordered weighted geometric (I-HIVFEOWG) operator

DOI: 10.3233/IFS-2012-0598

Citation: Journal of Intelligent & Fuzzy Systems, vol. 24, no. 4, pp. 789-803, 2013

Authors: Ji, Rui | Yang, Yupu | Zhang, Weidong

Article Type: Research Article

Abstract: This paper establishes a connection between Takagi-Sugeno (TS) fuzzy systems and ε-insensitive smooth support vector regression (ε-SSVR), a smooth strategy for solving ε-SVR. In previous ε-SVR-based fuzzy models, the form of membership functions is restricted by the Mercer condition. The ε-SSVR formulation puts no restrictions on the kernel. Therefore, the proposed ε-SSVR-based TS-fuzzy modeling method relaxes the restriction on membership functions. By applying the reduced kernel technique, the number of fuzzy rules is reduced without scarifying the generalization ability. The computational complexity is also reduced by the reduced kernel technique. The performance of our method is illustrated by extensive experiments …and comparisons. Show more

Keywords: TS-fuzzy systems, smooth support vector regression, reference functions, fuzzy modeling, ε-insensitive learning

DOI: 10.3233/IFS-2012-0599

Citation: Journal of Intelligent & Fuzzy Systems, vol. 24, no. 4, pp. 805-817, 2013

Authors: Mousavi, S. Meysam | Jolai, Fariborz | Tavakkoli-Moghaddam, Reza | Vahdani, Behnam

Article Type: Research Article

Abstract: This paper develops a new Fuzzy Grey Multi-Criteria Group Decision Making (FG-MCGDM) model to solve evaluation and selection problems under uncertainty in real-life situations. The proposed model is based on a hybridization of fuzzy sets theory, Grey Relational Analysis (GRA) and compromise solution method. First, linguistic variables are employed to assess performance ratings of alternatives and weights of criteria represented in trapezoidal fuzzy numbers. Then, a new version of the GRA is introduced to solve group decision making problems with conventional fuzzy information, in which correlations are captured between the reference/aspiration-level criteria and alternatives. Consequently, a new ranking index is …presented based on the concept of the compromise solution to obtain the ranking order of all alternatives. The solution is determined in terms of several conflicting criteria by considering the degree of grey relation to both the positive-ideal and negative-ideal solutions concurrently. Finally, an illustrative example is provided to verify the FG-MCGDM model and to demonstrate its suitability in manufacturing systems. Show more

Keywords: Multi-criteria group decision making, fuzzy sets theory, grey relational analysis, compromise solution, manufacturing systems

DOI: 10.3233/IFS-2012-0600

Citation: Journal of Intelligent & Fuzzy Systems, vol. 24, no. 4, pp. 819-827, 2013

Authors: Çağman, Naim | Karataş, Serkan

Article Type: Research Article

Abstract: In this work, we first defined the intuitionistic fuzzy soft sets (IFS-sets) and their operations. By using them, we then give some results and construct a decision making method. Finally, we give an application which shows that this approach is useful to handle several realistic uncertain problems.

Keywords: Fuzzy set, soft set, intuitionistic fuzzy set, IFS-sets, IFS-decision making

DOI: 10.3233/IFS-2012-0601

Citation: Journal of Intelligent & Fuzzy Systems, vol. 24, no. 4, pp. 829-836, 2013

Authors: Kalyanaraman, R. | Thillaigovindan, N. | Kannadasan, G.

Article Type: Research Article

Abstract: A single server fuzzy queue with modified Bernoulli vacation is analyzed using a technique which is a fusion of Zadeh's extension principle (L.A. Zadeh, Fuzzy sets as a basis for a theory of possibility, Fuzzy Sets and Systems 1 (1978), 3–28), α-cut approach and parametric non-linear programming. Batches of customers arrive at the system according to a compound Poisson process. But all arriving batches are not allowed to enter into the system. The restriction policy depends on availability or otherwise of the server. The system is analyzed in Fuzzy environment. Some special cases are discussed. A numerical study is also …carried out. Show more

Keywords: Bulk queue, Bernoulli vacation, membership function

DOI: 10.3233/IFS-120602

Citation: Journal of Intelligent & Fuzzy Systems, vol. 24, no. 4, pp. 837-845, 2013

Authors: Wan, Shu-Ping | Li, Deng-Feng | Rui, Zhen-Feng

Article Type: Research Article

Abstract: Triangular intuitionistic fuzzy numbers (TIFNs) are a special kind of intuitionistic fuzzy sets (IFSs) on the real number set. TIFNs are useful to deal with ill-known quantities in decision data and decision making problems themselves. How to measure the value and uncertainty of a TIFN is of great importance. In this paper, we introduce the concepts of the weighted possibility mean, variance and covariance of TIFNs. Furthermore, we show that the weighted possibility mean and the weighted possibility variance of linear combination of TIFNs can be computed in a similar manner to those in probability theory. The desirable properties for …the possibility covariance of TIFNs are also investigated. The concepts of the weighted possibility mean, variance and covariance of TIFNs can be considered as a generalization of those of the triangular fuzzy numbers. Show more

Keywords: Triangular intuitionistic fuzzy number, possibility mean, possibility variance, possibility covariance

DOI: 10.3233/IFS-2012-0603

Citation: Journal of Intelligent & Fuzzy Systems, vol. 24, no. 4, pp. 847-858, 2013

Authors: Sandidzadeh, Mohammad Ali | Dehghani, Mehdi

Article Type: Research Article

Abstract: Condition monitoring is a prevalent method to improve the Reliability, Accessibility, Maintainability and Safety level of a system. By using this method, detection and diagnostics of imminence or persistence faults, will be viable. The ability of detecting imminent faults, it will be possible to prevent any breakdowns via preventive maintenance, which leads to improve Reliability and Accessibility and functional lifetime expansion of the system. In recent years, monitoring systems have gained much consideration for boosting the quality of equipment operations in railway systems. In this paper, we employed Neuro-Fuzzy Network (NFN) for fault detection and diagnostics in a typical audio …frequency track circuit, which is a combination of knowledge-based and data-based systems. It has the merits of both fuzzy systems and neural networks. In other words, NFN is capable of interacting with low precision data and has the learning ability of a neural network. For the realization of the method; a typical track circuit has been modeled and simulated. Healthy and faulty data have been used for training the algorithm. When put to work, occurrence of fault modes or their imminence is detected and localized with a good precision by the algorithm. Show more

Keywords: Condition Monitoring, Railway Signaling System, Audio Frequency Track Circuit, Neuro-Fuzzy Network

DOI: 10.3233/IFS-2012-0604

Citation: Journal of Intelligent & Fuzzy Systems, vol. 24, no. 4, pp. 859-869, 2013

Authors: Abbas, M. | Ali, Basit

Article Type: Research Article

Abstract: In this paper, we prove coupled fixed point theorem for multivalued fuzzy contraction mappings in a complete Hausdorff fuzzy metric space. As an application, coupled coincidence and common fixed point theorem is obtained for a hybrid pair of multivalued and single valued mappings. It is worth mentioning that to find coupled coincidence points we do not employ the condition of continuity of any mapping involved therein. Also, coupled coincidence points are obtained without exploiting any type of commutativity condition. Our results extend, improve, and unify some well known results in the literature.

Keywords: Coupled fixed point, t – norm, Coupled coincidence point, n – property

DOI: 10.3233/IFS-2012-0605

Citation: Journal of Intelligent & Fuzzy Systems, vol. 24, no. 4, pp. 871-877, 2013

Authors: Lin, Rui | Zhao, Xiaofei | Wei, Guiwu

Article Type: Research Article

Abstract: In this paper, we investigate the fuzzy number intuitionistic fuzzy multiple attribute decision making (MADM) problems in which the attributes are in different priority level. Motivated by the ideal of prioritized aggregation operators (R.R. Yager, Prioritized aggregation operators, International Journal of Approximate Reasoning 48 (2008) 263–274), in this paper, we propose some fuzzy number intuitionistic fuzzy prioritized aggregation operators: fuzzy number intuitionistic fuzzy prioritized weighted average (FNIFPWA) operator and fuzzy number intuitionistic fuzzy prioritized weighted geometric (FNIFPWG) operator. The prominent characteristic of these proposed operators is that they take into account prioritization among the attributes, and then apply them to …develop some models for fuzzy number intuitionistic fuzzy multiple attribute decision making (MADM) problems in which the attributes are in different priority level. Finally, a practical example about talent introduction is given to verify the developed approaches and to demonstrate its practicality and effectiveness. Show more

Keywords: Multiple attribute decision making (MADM), fuzzy number intuitionistic fuzzy values, prioritized aggregation operators, fuzzy number intuitionistic fuzzy prioritized weighted average (FNIFPWA) operator, fuzzy number intuitionistic fuzzy prioritized weighted geometric (FNIFPWG) operator

DOI: 10.3233/IFS-2012-0606

Citation: Journal of Intelligent & Fuzzy Systems, vol. 24, no. 4, pp. 879-888, 2013

Authors: Cateni, Silvia | Colla, Valentina | Nastasi, Gianluca

Article Type: Research Article

Abstract: The paper presents an application of fuzzy logic to the problem of outliers detection. The overall purpose of the work is to point out anomalous data due different causes through a combination of several traditional methods for outliers detection in multivariate datasets and such combination is achieved through a fuzzy inference system. Moreover, the proposed solutions aims to be automatic and self-adaptive, as some parameters which are required for the combination of the different approaches are automatically evaluated by exploiting the available data, without the need of a-priori assumptions or information on a subset of the available data. The proposed …method therefore belongs to the class of the unsupervised outliers detection methods. In order to demonstrate the effectiveness of the developed method, extensive tests have been performed on both a simple case study and a database coming from a real industrial context, where the data have to be filtered before their exploitation for process control purposes. The achieved numerical results are presented and discussed. Show more

Keywords: Outlier detection, fuzzy inference system

DOI: 10.3233/IFS-2012-0607

Citation: Journal of Intelligent & Fuzzy Systems, vol. 24, no. 4, pp. 889-903, 2013

Authors: Mon, Yi-Jen | Lin, Chih-Min | Yeh, Rong-Guan

Article Type: Research Article

Abstract: An intelligent control methodology for a long-term ecological systems is developed in this paper. This intelligent control methodology is called as robust recurrent fuzzy neural network control (RRFNNC). This control methodology is used to deal with multi-biomass ecological system which is an uncertain nonlinear system subject to unpredictable but bounded disturbances. This RRFNNC system is comprised of a recurrent fuzzy neural network (RFNN) controller and a robust controller. The RFNN controller is used to approximate an ideal controller; and the robust controller is designed to compensate for the approximation error between the RFNN controller and the ideal controller. The proposed …RRFNNC system is applied to keep the multi-biomasses of ecological system within a stay small neighborhood of the unique nontrivial optimal equilibrium state of the undisturbed exploited ecosystem. For the simulation results of accumulative yield of harvest, more harvest can be obtained by applying the proposed RRFNNC system when compared with state feedback control. Show more

Keywords: Ecological systems, intelligent control, recurrent fuzzy neural network

DOI: 10.3233/IFS-2012-0626

Citation: Journal of Intelligent & Fuzzy Systems, vol. 24, no. 4, pp. 905-913, 2013

Article Type: Other

Citation: Journal of Intelligent & Fuzzy Systems, vol. 24, no. 4, pp. 915-919, 2013