Journal of Intelligent & Fuzzy Systems - Volume 29, issue 5

Authors: Riahinia, Shahin | Abbaspour, Ali | Fotuhi-Firuzabad, Mahmud | Moeini-Aghtaie, Moein

Article Type: Research Article

Abstract: Operational and planning studies of high-wind penetrated power systems have well come to the light as a major concern of future energy systems. This paper focuses on the procedure of determining required static reserve of the high-wind penetrated power systems which has not been well accompanied by comprehensive analysis and proper modeling tools. To reach this goal, first, a probabilistic algorithm has been proposed to effectively model the variations in output generation of wind turbines. In this algorithm, the fuzzy c-means clustering method (FCM) is exploited as an efficient as well as robust clustering method to find the multi-state model …of wind turbines output generation. Based on this probabilistic analytical model, a stochastic framework is developed to investigate the roles of two important factors, i.e. wind power penetration rate and installed capacity of wind farms on the required static reserve of the system. In this regard, different wind power penetration rates have been defined for generation sector of the IEEE-RTS and the adequacy studies of this test system is performed to show that how variations in wind power penetration rate can affect the required static reserve of the system. In addition, a sensitivity analysis based on an exhaustive search algorithm is conducted on the capacity of installed wind farms to examine the effects of this important factor on the reliability level of power systems. This studies not only emphasize on the necessities of employing stochastic approach to determine the require reserve of a high-wind penetrated power system, but also, proves the applicability of proposed analytical approach. Show more

Keywords: Fuzzy clustering, wind farm, probabilistic model of wind turbine, wind penetration, wind farm installed capacity, static reserve

DOI: 10.3233/IFS-151681

Citation: Journal of Intelligent & Fuzzy Systems, vol. 29, no. 5, pp. 2039-2046, 2015

Authors: Mousavi, S. Meysam | Vahdani, Behnam | Abdollahzade, Majid

Article Type: Research Article

Abstract: Precise cost prediction of new product development (NPD) projects has been a challenge for both academia and practitioners that often requires much effort and experience. In this paper, a combination of particle swarm optimization (PSO), cross validation (CV) and support vector regression (SVR) is proposed to predict the cost of NPD projects. SVR, a novel intelligent technique for time series analysis, can overcome some shortcomings in the conventional approaches; and PSO, a new evolutionary computation technique, is utilized to set the optimal parameters of the SVR. The proposed intelligent model avoids manual selection of these parameters. The PSO solves the …difficulty of setting these parameters appropriately and enhances the efficiency and capability of cost prediction. In addition, the CV is employed to train the SVR and improve the reliability of model performance. Then a real dataset of a home appliances manufacturer is provided to illustrate the proposed model and demonstrate the high performance and applicability to cost prediction of the NPD project. Finally, the effectiveness of the support vector model is compared with well-known techniques including multilayer perceptron networks (MLP), normalized radial basis function (NRBF) neural network, and pure SVR in terms of the accuracy measures. Based on the real world dataset, it is observed that the proposed model outperforms other well-known techniques. Show more

Keywords: New product development, cost prediction, neural networks, support vector regression, cross validation, particle swarm optimization

DOI: 10.3233/IFS-151682

Citation: Journal of Intelligent & Fuzzy Systems, vol. 29, no. 5, pp. 2047-2057, 2015

Authors: Xi, Zhenghao | Tang, Shengchun | Wu, Jianzhen | Zheng, Yang

Article Type: Research Article

Abstract: Persistently tracking multiple objects is very challenging when there exit occlusions. We present a tracking association approach based on the A* algorithm. We first formulate the multiple object tracking as an integer programming problem of the flow network. Under this framework, the integer assumption is relaxed to a standard linear programming problem. Therefore, the global optimal solution can quickly be obtained using the A* algorithm with dynamic weights. The proposed method avoids the difficulties of integer programming and more importantly, it has a lower worst-case complexity than competing methods but a better tracking accuracy and robustness in complex …environments. Experiment results revealed that our proposed method achieved state-of-the-art time costs and can operate in real-time. Show more

Keywords: Multi-object tracking, A* algorithm, flow network model, integer programming

DOI: 10.3233/IFS-151683

Citation: Journal of Intelligent & Fuzzy Systems, vol. 29, no. 5, pp. 2059-2072, 2015

Authors: Gnanaprakasam, CN | Chitra, K

Article Type: Research Article

Abstract: In this paper, a hybrid approach is proposed for detecting and classifying the vibration signal of induction motor. The proposed hybrid technique is the combination of S-transformation algorithm and adaptive neuro fuzzy inference system (ANFIS) method. Here, the proposed hybrid method contains two processes, such as, fault detection and classification process. Initially, the pre-processing is applied in the electric motor vibration signal. In the fault detection process, significant features from vibration signals are extracted through the S-transformation algorithm. Consequently, the ANFIS classification technique is employed to classify the signal into the faulty or the normal. The proposed hybrid technique is …implemented in MATLAB working platform. The performance of the proposed hybrid technique is evaluated with five types of faulty vibration signals. The performance of the proposed hybrid method is compared with the existing method such as S-transform-RBFNN and S-transform-FFBNN. Analyze these methods with the help of statistical measures such as, accuracy, sensitivity and specificity value. Show more

Keywords: Pre-processing, fault classification, S-transformation, RBFNN and ANFIS

DOI: 10.3233/IFS-151684

Citation: Journal of Intelligent & Fuzzy Systems, vol. 29, no. 5, pp. 2073-2085, 2015

Authors: Song, Yafei | Wang, Xiaodan | Yu, Xiaodong | Zhang, Hailin | Lei, Lei

Article Type: Research Article

Abstract: In this paper, we address the problem of how to measure non-specificity for intuitionistic fuzzy sets. This problem is relevant to the construction of intuitionistic fuzzy uncertainty measure. Although there already exist many uncertainty measures for intuitionistic fuzzy sets, few of them can discriminate uncertainty degrees of crisp sets. In order to construct a unified uncertainty measure for intuitionistic fuzzy sets, non-specificity must be taken into account. Starting from the Hartley measure, which is related to the cardinality of a crisp set, we propose a non-specificity measure for intuitionistic fuzzy sets. Properties of the proposed non-specificity measure are also investigated. …Illustrative examples are employed to show its performance. Show more

Keywords: Intuitionistic fuzzy sets, uncertainty measure, non-specificity measure

DOI: 10.3233/IFS-151685

Citation: Journal of Intelligent & Fuzzy Systems, vol. 29, no. 5, pp. 2087-2097, 2015

Authors: Chen, Liuhao | Xu, Zeshui

Article Type: Research Article

Abstract: The Multiple Criteria Decision Aiding (MCDA) has been a fast growing area of operations research and management science during the last decades, while the PROMETHEE (Preference Ranking Organization Method for Enrichment Evaluations) is one of the well-known MCDA methods with ranking the alternatives from the best to the worst. In this paper, we propose a new outranking method called Prioritized PROMETHEE (P-PROMETHEE) method, which is used to deal with the ranking problem of Prioritized Multiple Criteria Decision Making (PMCDM). First, we use the idea of entropy to get the information of each criterion in the same prioritized level, which is …used to get the weight of each criterion. Then, we use the weighted average operator to aggregate all the criteria in the same prioritized level. Moreover, we apply Yager’s prioritized measure-guided aggregation operator to the classical PROMETHEE method to get the P-PROMETHEE method. Finally, we give a practical example to illustrate the effectiveness of the P-PROMETHEE method. Show more

Keywords: Entropy, prioritized measure, PROMETHEE method, weight vector, choquet integral

DOI: 10.3233/IFS-151686

Citation: Journal of Intelligent & Fuzzy Systems, vol. 29, no. 5, pp. 2099-2110, 2015

Authors: Pourbahman, Zahra | Hamzeh, Ali

Article Type: Research Article

Abstract: Evolutionary Algorithm provides a framework that is largely applicable to particular problems including multiobjective optimization problems, basically for the ease of their implementation and their capability to perform efficient parallel search. Indeed, in some cases, expensive multiobjective optimization evaluations might be a challenge to restrict the number of explicit fitness evaluations in multiobjective evolutionary algorithms. Accordingly, this article presents a novel approach that tackles this problem so as to not only decrease the number of fitness evaluations but also to improve the performance. During evolution, our proposed approach selects fit individuals based on the knowledge acquired throughout the search, and …performs explicit fitness evaluations on these individuals. A comprehensive comparative analysis of a wide range of well-established test problems, selected from both traditional and state-of-the-art benchmarks, has been presented. Afterward, the effectiveness of the obtained results is compared with some of the state-of-the-art methods using two well-known metrics- i.e. Hypervolume and Inverted Generational Distance (IGD). The experiments of our implemented approach is performed to illustrate that our proposal seems to be promising and would prove more efficient than other approaches in terms of both the performance and the computational cost. Show more

Keywords: Fitness approximation, multi-objective evolutionary algorithm, fuzzy inference system, hypervolume approximation, hypervolume contribution

DOI: 10.3233/IFS-151687

Citation: Journal of Intelligent & Fuzzy Systems, vol. 29, no. 5, pp. 2111-2131, 2015

Authors: Saeid, Arsham Borumand | Fatemidokht, Hamideh | Flaut, Cristina | Rafsanjani, Marjan Kuchaki

Article Type: Research Article

Abstract: In this paper, we present some new connections between BCK -algebras and binary block codes.

Keywords: BCI/BCK-algebras, binary block codes, partially ordered set

DOI: 10.3233/IFS-151688

Citation: Journal of Intelligent & Fuzzy Systems, vol. 29, no. 5, pp. 2133-2137, 2015

Authors: Zhong, Yi-hua | Jia, Yan-lin | Zhao, Jiao | Lin, Xu-xu | Yang, Yan

Article Type: Research Article

Abstract: The focus of this paper is on solving degenerate fuzzy number linear programming problems. A revised fuzzy simplex method is proposed, which can deal with this issue. First, the degenerate fuzzy number linear programming is defined and a new problem related to the original problem is constructed. Then, combined with the ranking function, some relationships between the optimal solution of the new problem and that of the original problem are given and proved. Furthermore, we propose a revised fuzzy simplex method through improving the method of selecting the leaving basic variable, which can successfully find the optimal solution of the …original degenerate problem. Finally, to compare the existing method and illustrate our method, we solve one numerical example. Show more

Keywords: Fuzzy number linear programming, fuzzy simplex method, degeneracy, ranking function, trapezoidal fuzzy number

DOI: 10.3233/IFS-151689

Citation: Journal of Intelligent & Fuzzy Systems, vol. 29, no. 5, pp. 2139-2146, 2015

Authors: Ahmadi Kamarposhti, Mehrdad | Soleymani, Soodabeh | Mozafari, Seyed Babak | Hosseini, Seyed Mehdi

Article Type: Research Article

Abstract: This paper proposed an approach to determine optimal location of SVC (Static Var Compensator) to improve the voltage profile and maximize system loadability in power networks connected to a doubly-fed induction generator (DFIG)-based wind farm. A variable reactance model for SVC is presented in steady state studies and implemented in the load flow program with embedded Flexible AC Transmission Systems (FACTS) devices. The continuation power flow method is used to determine optimal location of SVC and steady state stability margin, based on closing to point of voltage collapse. As an important result in this paper, we obtained an optimal location …of SVC devices on wind farm by calculating the new indices such as maximum loading point (MLP) and mega watt margin (MWM). A case study and simulation are done on modified IEEE14 bus test system. Show more

Keywords: Continuation power flow, DFIG, voltage stability, wind farm, SVC

DOI: 10.3233/IFS-151690

Citation: Journal of Intelligent & Fuzzy Systems, vol. 29, no. 5, pp. 2147-2157, 2015