Journal of Intelligent & Fuzzy Systems - Volume 26, issue 1

Authors: Zhang, Qiansheng | Xing, Hongyan | Liu, Fuchun | Huang, Yirong

Article Type: Research Article

Abstract: This paper presents an enhanced approach for multiattribute decision making with interval-valued intuitionistic fuzzy assessing values for each alternative. To efficiently deal with the interval-valued intuitionistic fuzzy multiattribute decision making problem with partially or completely unknown weight information, we construct several optimization models based on minimizing the distance between each alternative and positive ideal solution to obtain the optimal weight of each attribute. Also by employing the weighted grey relational coefficient of each alternative with respect to the ideal solution, the full ranking of all the alternatives can be obtained and the most desirable one can be selected.

Keywords: Interval-valued intuitionistic fuzzy number, multiattribute decision, optimization model, grey relational coefficient, ideal solution

DOI: 10.3233/IFS-120740

Citation: Journal of Intelligent & Fuzzy Systems, vol. 26, no. 1, pp. 317-326, 2014

Authors: Kotsiantis, Sotiris

Article Type: Research Article

Abstract: Decision tree techniques have been widely used to build classification models. In this study, we attempted to increase the prediction accuracy of a decision tree model by integrating local application of Naive Bayes classifier. We performed a large-scale comparison with other state-of-the-art algorithms on 30 standard benchmark datasets and the proposed method gave statistical better accuracy in some cases.

Keywords: Decision tree, classification tree, Naive Bayes, hybrid classifier

DOI: 10.3233/IFS-120741

Citation: Journal of Intelligent & Fuzzy Systems, vol. 26, no. 1, pp. 327-336, 2014

Authors: Kumar, Amit | Kaur, Jagdeep

Article Type: Research Article

Abstract: In this paper, a new method is proposed to find the fuzzy optimal solution of fully fuzzy linear programming (FFLP) problems with mixed constraints. By using the proposed method the fuzzy optimal solution of FFLP problems with mixed constraints occurring in real life situations can be easily obtained. To illustrate the proposed method a numerical example is solved. The proposed method can be easily applied to find the fuzzy optimal solution of FFLP problems occurring in real life situations.

Keywords: Fully fuzzy linear programming problems, triangular fuzzy numbers, ranking function

DOI: 10.3233/IFS-120742

Citation: Journal of Intelligent & Fuzzy Systems, vol. 26, no. 1, pp. 337-344, 2014

Authors: Grychowski, Tomasz

Article Type: Research Article

Abstract: One of major threat to underground coal mines and miner's life is a fire hazard. It is important to foresee conditions leading to the fire hazard by proper interpretation of the data from underground coal mine air monitoring stations. The article describes new method for analyzing measured data. The method applies a fuzzy logic and its inference mechanisms to improve reliability in decision making process. The analysis utilizes measured data from information related to changes in composition of gases in underground mine and uncertainty of monitoring sensors. The method was tested in fire simulating setting utilizing underground measurement equipment. Fuzzy …models of fire hazard conditions where design with help of LabVIEW. The correlation between model structure and interpretation of the result is presented. Show more

Keywords: Fire hazard detection, fuzzy logic, expert systems, gas measurements, knowledge based systems, underground fire, exogenous fire assessment

DOI: 10.3233/IFS-120743

Citation: Journal of Intelligent & Fuzzy Systems, vol. 26, no. 1, pp. 345-351, 2014

Authors: Çelebi, Numan | Selvi, İhsan Hakan

Article Type: Research Article

Abstract: Supplier Evaluation and Selection (SES) is one of the most crucial issues for many companies because of its strategic importance. Over the years a number of approaches have been presented to SES problems. SES problems are multi-criteria decision making problem involving both quantitative and qualitative criteria. Decision makers' (DMs) preferences on alternative supplier or on the criteria are often uncertain. So SES problems become more difficult. In order to overcome this difficulty, a Fuzzy-Grey based approach is suggested in this paper. We combined the favorable sides of Grey System Theory's (GST) power of mathematical analysis and Fuzzy Set's (FS) power …of pointing out uncertainty for the sake of processing the uncertainty information. As the empirical study, a practical application proceeded for a leading wagon company in Turkey. A real numerical example is used to clarify the suggested approach and comparison results are presented with conclusion. Show more

Keywords: Supplier selection, fuzzy set, grey system theory

DOI: 10.3233/IFS-120744

Citation: Journal of Intelligent & Fuzzy Systems, vol. 26, no. 1, pp. 353-365, 2014

Authors: Ghomashi, A. | Salahshour, S. | Hakimzadeh, A.

Article Type: Research Article

Abstract: In this paper, we proposed a new method for approximating solutions of fully fuzzy linear systems in the dual form. For this purpose, we solve the original problem in the 1-cut position (we assumed that the 1-cut is a crisp linear system), then some unknown symmetric spreads are allocated to each row of the crisp system, which leads to convert the original problem to 2 * n linear equations in order to find the symmetric spreads. Consequently, we suggested some extensions of the united solution set, the tolerable solution set and the controllable solution set. Simultaneously, we clarify between the …classic hull solution sets and the extended hull solution sets in which finally leads to characterize the inner and outer estimations. Then, a financial example is solved to show the ability of proposed method. Show more

Keywords: Fully fuzzy linear system in the dual form, unites solution set, tolerable solution set, controllable solution set, Inner and outer estimation

DOI: 10.3233/IFS-120745

Citation: Journal of Intelligent & Fuzzy Systems, vol. 26, no. 1, pp. 367-378, 2014

Authors: Amiri, G. Ghodrati | Khorasani, M. | Aghajari, S. | Tabrizian, Z.

Article Type: Research Article

Abstract: Based on Adaptive Neural Network Fuzzy Inference System (ANFIS) networks, this paper presents a novel approach to generate artificial earthquake accelerograms from available data, which are compatible with specified design or response spectra. The proposed procedure uses the learning abilities of ANFIS networks as a powerful tool to develop the knowledge of the inverse mapping from response spectrum to earthquake records. Furthermore, to obtain better simulation results, Wavelet Packet Transform (WPT) and Principle Component Analysis (PCA) are used to convert records and response spectra from real to transformed spaces. Then, ANFISs are trained to relate response spectrum of records to …their wavelet packet coefficients. In this process, the same results of different training levels of ANFIS method are obtained. In order to clarify the efficiency and accuracy of the proposed method, the results have been compared with the outcomes of previous artificial earthquake accelerograms generation methods. Finally, several interpretive examples are provided to demonstrate success of the suggested method. Show more

Keywords: ANFIS, PCA analysis, wavelet packet transforms, transformed space, artificial accelerogram

DOI: 10.3233/IFS-120746

Citation: Journal of Intelligent & Fuzzy Systems, vol. 26, no. 1, pp. 379-391, 2014

Authors: Vahdani, Behnam | Mousavi, S. Meysam | Ebrahimnejad, S.

Article Type: Research Article

Abstract: Multiple Attributes Decision Making (MADM) is the process of finding the best candidate and involves the evaluation and selection among a finite number of potential candidates to solve real-life complex decision problems. In classical MADM methods, the relative importance of the conflicting criteria and performance ratings of candidates are determined precisely. However, in real-world systems related to human resource management, decision making problems are often uncertain or vague, and because of the lack of information, the future state of these systems cannot be known completely. Moreover, if decision makers cannot reach an agreement on the method of defining linguistic variables …based on the traditional fuzzy sets, the Interval-Valued Fuzzy Sets (IVFSs) theory can provide a more accurate and practical modeling. This paper presents an Interval-Valued Fuzzy Preference Selection Index (IVF-PSI) method aiming at solving complex decision making problems, in which the performance ratings of candidates are described by using the concept of the IVFSs. Finally, the executive procedure of the proposed IVF-PSI method is illustrated by applying it to the expatriate selection process from the viewpoint of human resource managers. Show more

Keywords: Multiple attributes decision making, preference selection index, interval-valued fuzzy sets, human resources management

DOI: 10.3233/IFS-120748

Citation: Journal of Intelligent & Fuzzy Systems, vol. 26, no. 1, pp. 393-403, 2014

Authors: Gegov, Alexander | Petrov, Nedyalko | Gegov, Emil

Article Type: Research Article

Abstract: This paper proposes a novel approach for modelling complex interconnected systems by means of fuzzy networks. The nodes in these networks are interconnected rule bases whereby the outputs from some rule bases are fed as inputs to other rule bases. The approach allows any fuzzy network of this type to be presented as an equivalent fuzzy system by linguistic composition of its nodes. The composition process makes use of formal models for fuzzy networks and basic operations in such networks. These models and operations are used for defining several node identification cases in fuzzy networks. In this case, the unknown …nodes are derived by solving Boolean matrix equations in a way that guarantees a pre-specified overall performance of the network. The main advantage of the proposed approach over other approaches is that it has better transparency and facilitates not only the analysis but also the design of complex interconnected systems. Show more

Keywords: Fuzzy modelling, linguistic modelling, fuzzy networks, rule base identification, complex systems

DOI: 10.3233/IFS-130786

Citation: Journal of Intelligent & Fuzzy Systems, vol. 26, no. 1, pp. 405-419, 2014

Authors: Ji, Ai-bing | Chen, Songcan | Hua, Qiang

Article Type: Research Article

Abstract: Support vector machines (SVMs) have been very successful in pattern recognition and function estimation problems. When SVMs are used for classification, the inputs of the training example are real-valued and the outputs are class label y = ±1. However, in practice, the training examples usually belong to a class with certain fuzzy membership, therefore it is important to consider uncertain class label for classification problems. For this purpose, this paper introduces the new concept of fuzzy hyperplane, and constructs the fuzzy classifiers based on fuzzy support vector machines. At the end of the paper, we apply our new methods to …medical diagnosis problems. Show more

Keywords: Support vector machine, possibility measure, fuzzy linear separable example, fuzzy hyperplane, fuzzy classifier

DOI: 10.3233/IFS-130819

Citation: Journal of Intelligent & Fuzzy Systems, vol. 26, no. 1, pp. 421-430, 2014