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

Authors: Rezai, Hamid Reza | Mohammadi, Sirus | Bagheri, Mahmod Zade | Moghimi, Rohalla

Article Type: Research Article

Abstract: This paper proposes a new stochastic framework to solve the practical economic dispatch (ED) problem considering the penetration of wind turbines (WTs). The proposed stochastic method is constructed based on krill herd (KH) algorithm to search the problem space optimally. Since the output power of WT is neither stable nor continues, point estimate method (PEM) with 2m scheme is used to model the uncertainty effects. In addition to the traditional constraints, the practical ED includes valve-loading effect, multi-fuel option, prohibited operating zone (POZ), ramp rate limit and spinning reserve. According to the high complexity and nonlinearity of the problem, …a new version of KH called Modified Levy Krill Herd (MLKH) is suggested to solve the problem optimally. The satisfying performance of the problem is examined on two standard test systems and is compared with some of the recent well-know methods in the area successfully. Show more

Keywords: Economic dispatch, point estimate method, Levy Krill Herd, practical constraints

DOI: 10.3233/IFS-151691

Citation: Journal of Intelligent & Fuzzy Systems, vol. 29, no. 5, pp. 2159-2167, 2015

Authors: Rafe, Vahid | Paiandeh, Zahra | Nikanjam, Amin

Article Type: Research Article

Abstract: Harmony Search (HS), as a novel optimization algorithm, is interesting for researchers because of its simplicity and appropriate efficiency. This algorithm has been applied to different continuous optimization problems leading to successful results. The parameter setting significantly impacts the performance of Harmony Search, similar to other meta-heuristics. In order to enhance this algorithm and facilitate the task of parameter setting, a hybrid approach is introduced in this paper. The harmony algorithm is improved by combining with the Differential Evolution (DE), as a successful evolutionary optimization algorithm which have been yielded admissible results in solving difficult problems. The new algorithm is …tested on some well-known benchmark functions. The results show that the new hybrid algorithm has superior performance in comparison to the original Harmony Search and a modified version which is called Improved Harmony Search. Show more

Keywords: Continuous optimization, harmony search, differential evolution, hybrid algorithms

DOI: 10.3233/IFS-151692

Citation: Journal of Intelligent & Fuzzy Systems, vol. 29, no. 5, pp. 2169-2176, 2015

Authors: Li, Zhen-Bo | Liu, Hua-Wen

Article Type: Research Article

Abstract: In this paper, two classes of generalized (U , N )-implications derived from commutative semi-uninorms and pseudo-uninorms are investigated. Then some properties of U I ,N operations derived from implications are explored. Last the necessary and sufficient conditions such that a (U CS , N )-operation (or (U P , N )-operation) is an implication are given out.

Keywords: Fuzzy connective, fuzzy implication, (US, N)-implication, commutative semi-uninorm, pseudo-uninorm

DOI: 10.3233/IFS-151693

Citation: Journal of Intelligent & Fuzzy Systems, vol. 29, no. 5, pp. 2177-2184, 2015

Authors: Sedaghati, Reza | Honarmand, Sima | Nemati, Yaser

Article Type: Research Article

Abstract: This paper proposes a new stochastic method based on u-transform (UT) to capture the uncertainties of the reconfiguration in a correlated environment. The proposed stochastic framework makes use of the idea covariance matrix to reach this goal. Also, in order to reach the maximum efficiency of the reconfiguration strategy, reliability indices are considered along with the traditional targets in the multi-objective framework. Therefore, the objective functions to be optimized are System Average Interruption Frequency Index (SAIFI), Average Energy Not Supplied (AENS), total active power losses and the total network costs. Since the problem investigated is a complex, nonlinear optimization problem, …a new optimization method based on krill herd algorithm (KH) is introduced. In addition, a new modification method is proposed for the KH algorithm to improve its total search ability. The feasibility and performance of the proposed method are examined on the IEEE standard test system. Show more

Keywords: U-transform, multi-objective reconfiguration, krill herd algorithm

DOI: 10.3233/IFS-151694

Citation: Journal of Intelligent & Fuzzy Systems, vol. 29, no. 5, pp. 2185-2192, 2015

Authors: Zhao, Xinqiu | Wang, Xi | Sun, Hao | Wang, Liping | Ma, Mingming

Article Type: Research Article

Abstract: Differential evolution algorithm (DE) has yielded promising results for solving nonlinear, non-differentiable and multi-modal optimization issues. Due to its simple structure, fast convergence and strong robustness, DE has received increasing attention and wide application in a variety of fields. We propose a novel differential evolution approach (SE-DE) which uses an external archive for opposition-based learning, by this way, more high quality solutions can be selected for candidate solutions. In addition, the mutation factor (F ) is adaptively controlled based on the success of offspring/trial solutions generated. An optimization factor α is proposed to select the crossover strategy, a combination …of binomial and exponential crossover can effectively balance the exploration and exploitation ability of the algorithm. The performance of SE-DE is compared with the other five DE algorithms including DE, SADE, ODE, NDE and MDE-pBX. The comparison is carried out for a set of 30-, 50- and 100-dimensional test functions from CEC2005. The results show that our algorithm is better than, or at least comparable to, the algorithms from other literature. Show more

Keywords: Differential evolution (DE), self adaptive, external archive, global optimization, unconstrained single objective optimization

DOI: 10.3233/IFS-151695

Citation: Journal of Intelligent & Fuzzy Systems, vol. 29, no. 5, pp. 2193-2204, 2015

Authors: Liu, Zhengmin | Liu, Peide

Article Type: Research Article

Abstract: Normal intuitionistic fuzzy numbers (NIFNs), which express their membership degree and non-membership degree as normal fuzzy numbers, can better character normal distribution phenomena existing in the real world. In this paper, we investigate the multiple attribute decision making problems with normal intuitionistic fuzzy information. Firstly, we introduce some operational laws, score function and accuracy function of NIFNs. Then, motivated by the ideal of Bonferroni mean, which can capture the interrelationship between input arguments, we develop some normal intuitionistic fuzzy aggregation operators, including the normal intuitionistic fuzzy Bonferroni mean (NIFBM) operator, the normal intuitionistic fuzzy weighted Bonferroni mean (NIFWBM) operator, the …normal intuitionistic fuzzy geometric Bonferroni mean (NIFGBM) operator and the normal intuitionistic fuzzy geometric weighted Bonferroni mean (NIFGWBM) operator; and discuss some desirable properties of these operators. Furthermore, based on these operators, we propose a new approach for the multiple attribute group decision making under normal intuitionistic fuzzy environment. Finally, we give a numerical example to illustrate the effectiveness and feasibility of the developedapproach. Show more

Keywords: Multiple attribute group decision making, normal intuitionistic fuzzy numbers, Bonferroni mean, normal intuitionistic fuzzy Bonferroni mean operator, normal intuitionistic fuzzy geometric Bonferroni mean operator

DOI: 10.3233/IFS-151696

Citation: Journal of Intelligent & Fuzzy Systems, vol. 29, no. 5, pp. 2205-2216, 2015

Authors: Wen, Meilin | Qin, Zhongfeng | Kang, Rui | Yang, Yi

Article Type: Research Article

Abstract: Facility location-allocation (FLA) problem has been widely studied by operational researchers due to its many practical applications. In real life, it is usually very hard to present the customers’ demands in a precise way and thus they are regarded to be uncertain. Since the uncertain demands can be estimated from historical data, researchers tried to describe FLA problem under stochastic environment. Although stochastic models can cater for a variety of cases, they are not sufficient to describe many other situations, where the probability distribution of customers’ demands may be unknown or partially known. Instead we have to invite some domain …experts to evaluate their belief degree that each event will occur. This paper will consider the capacitated FLA problem under small sample or no-sample cases and establish an uncertain expected value model based on uncertain measure. In order to solve this model, the simplex algorithm, Monte Carlo simulation and a genetic algorithm are integrated to produce a hybrid intelligent algorithm. Finally, a numerical example is presented to illustrate the uncertain model and the algorithm. Show more

Keywords: Location-allocation problem, uncertainty theory, uncertain measure, uncertain programming, genetic algorithm

DOI: 10.3233/IFS-151697

Citation: Journal of Intelligent & Fuzzy Systems, vol. 29, no. 5, pp. 2217-2226, 2015

Authors: Yadav, Harikesh Bahadur | Yadav, Dilip Kumar

Article Type: Research Article

Abstract: Construction of membership functions from numerical data is very important in various applications of the fuzzy set theory. In last two decade, many methods of membership function generation have been developed. Majority of the methods are application domain dependent and complex. In this paper, a simple method for the construction of membership functions from numerical data is proposed. To validate the proposed method, commonly used and suggested evaluation measures: average error rate, mean magnitude of relative error (MMRE), balanced mean magnitude of relative error (BMMRE), and coefficient of determination (R2 ), have been taken. The validating results show that proposed …method has a higher accuracy than existing methods. The sensitivity analysis has been performed to analyze the impact of input variable on the output variable. Show more

Keywords: Membership function, fuzzy set, fuzzy inference system, k-means clustering, training data

DOI: 10.3233/IFS-151698

Citation: Journal of Intelligent & Fuzzy Systems, vol. 29, no. 5, pp. 2227-2233, 2015

Authors: Zhang, Xin | Liu, Peide | Wang, Yumei

Article Type: Research Article

Abstract: On the basis of Frank operators, the operational rules of intuitionistic fuzzy numbers are redefined, then the intuitionistic fuzzy Frank power average operator (IFFPA), intuitionistic fuzzy Frank power weighted average operator (IFFPWA) and intuitionistic fuzzy Frank power ordered weighted average operator (IFFPOWA) are proposed by combining Frank operations and power aggregation operators. At the same time, some desirable properties of these operators, such as idempotency, commutativity and boundedness, are studied, and some special cases are analyzed. Furthermore, with respect to multiple attribute group decision making (MAGDM) problems in which attribute values take the form of the intuitionistic fuzzy numbers, two …group decision making methods based on IFFPWA and IFFPOWA operators are developed. Finally, an illustrative example is given to verify the proposed methods and to demonstrate their practicality and effectiveness. Show more

Keywords: Intuitionistic fuzzy number, Frank operator, power average operator, multiple attribute group decision making

DOI: 10.3233/IFS-151699

Citation: Journal of Intelligent & Fuzzy Systems, vol. 29, no. 5, pp. 2235-2246, 2015

Authors: Razavi, Seyedeh Fatemeh | Sajedi, Hedieh

Article Type: Research Article

Abstract: The Gravitational Search Algorithm (GSA) has been proposed for solving continues problems based on the law of gravity. In this paper, we propose a Cognitive Discrete GSA (called CDGSA) for solving 0-1 knapsack problem. The GSA has used a function of time to determine the number of the best particles for attracting others in each time, while our main idea is based on attracting each particle with two cognitive and social components. The cognitive component contains the best position of the particles up to now, while the social component contains the particle with the best position in the whole of …the system at the current time and the particles with the best position in the neighborhood. In the other words, the cognitive component is such an appropriate actuator for embedding in the intelligent agents like robots. Such intelligent agent or robot is guided in the right direction with the help of its best previous position. Finally, by introducing discrete version of this idea, the efficiency of the proposed algorithm is measured for 0-1 knapsack problem. Experimental results on some benchmark and high dimensional problems illustrate that the proposed algorithm has gained the better accuracy in comparison of the other similar methods. Show more

Keywords: Cognitive component, discrete gravitational search algorithm (DGSA), knapsack problem, social component

DOI: 10.3233/IFS-151700

Citation: Journal of Intelligent & Fuzzy Systems, vol. 29, no. 5, pp. 2247-2258, 2015

Authors: Georgiou, DN | Karakasidis, TE | Megaritis, AC | Nieto, Juan J. | Torres, A

Article Type: Research Article

Abstract: Bioinformatics is a relatively new discipline where Mathematics are applied in the analysis of genetic sequences. The analysis of the genetic material of living organisms which consist of nucleic acids DNA and RNA is of great importance for diagnosis and taxonomy reasons. In the present paper we propose a new methodology for the representation of genetic sequences as fuzzy sets in the I 12 space which can significantly improve the results of Sadegh-Zadeh and Torres & Nieto. An important characteristic of our proposed methodology is that the location of Amino acids along the genetic sequences play an important …role thus extending in a significant way the computational efficiency advantage of genetic sequence representation. We present some characteristic examples using the new proposed methodology where we calculate the distance and similarity degree of given polynucleotides. Show more

Keywords: DNA, RNA, polynucleotide, fuzzy sets, multi-fuzzy sets, metric spaces

DOI: 10.3233/IFS-151701

Citation: Journal of Intelligent & Fuzzy Systems, vol. 29, no. 5, pp. 2259-2269, 2015

Authors: Liu, Yong Lin | Kim, Hee Sik

Article Type: Research Article

Abstract: Molodtsov introduced the concept of soft set as a new mathematical tool for dealing with uncertainties. Recently, Cagman and Enginoglu [16] provided new definitions and operations on soft set theory. The paper applies new definitions and operations of soft sets to non-commutative residuated lattices. The notion of soft non-commutative residuated lattices is introduced. We give some specific examples to show the existence of soft non-commutative residuated lattices. The union, intersection, ∧-product, ∨-product and difference operations of soft non-commutative residuated lattices are investigated. Finally, we study the homomorphism properties of soft non-commutative residuated lattices. It is pointed out that the soft …non-commutative residuated lattices are so general, all results in this paper also hold in most of soft non-commutative logic algebras and soft logic algebras. Show more

Keywords: Soft set, soft non-commutative residuated lattice, union, intersection, ∧–product, ∨–product

DOI: 10.3233/IFS-151702

Citation: Journal of Intelligent & Fuzzy Systems, vol. 29, no. 5, pp. 2271-2278, 2015

Authors: Bahmani-Firouzi, Bahman | Khorshidi, Reza | Jabbari, Masoud | Nafar, Mehdi

Article Type: Research Article

Abstract: This paper presents a fuzzy PI controller as a power system stabilizer. The fuzzy PI controller has been designed in order to prepare an auxiliary signal for the excitation system of the synchronous generator. The proposed controller utilizes a combination of a fuzzy logic controller (FLC) and a PI controller, which are the most recent researches in the problem at hand. In comparison with the conventional fuzzy controllers, the proposed fuzzy PI controller takes advantage of both FLC and conventional PI controller to overcome all kind of disturbances. The damping of oscillations local modes in a power system will substantially …be controlled by employing this controller as a replacement for conventional PSS. Furthermore, the presented paper considers the conventional PSS and compares its performance with respect to three proposed types of fuzzy PI controller. Correspondingly, the effects of the supplementary signals in damping oscillation have been shown. Finally, to scrutinize the effectiveness of the proposed controller in damping oscillations, a three-phase short circuit condition is studied in order to clarify the application of the developed methodology. The achieved outcomes show that the proposed controller for stabilizing power system can provide very good damping characteristic. Show more

Keywords: Fuzzy control, power system stabilization, operating condition

DOI: 10.3233/IFS-151703

Citation: Journal of Intelligent & Fuzzy Systems, vol. 29, no. 5, pp. 2279-2286, 2015

Authors: Lei, Xia | Wu, Hongjian | Shi, Yan | Shi, Peng

Article Type: Research Article

Abstract: As a new branch of natural computing, membrane computing (MC) has become a hot topic. Based on the combination of nested structure membrane optimization method, genetic algorithm (GA) and the distributed computing method, an efficient parallel genetic membrane computing (PGMC) is proposed. Some rules are proposed to improve the computational performance of PGMC such as communication and transportation rules between homo-core membranes and hetero-core membranes, elementary membrane crossover and division rules, mutation and dissolving rules. An application of PGMC to distribution network reconfiguration is presented. According to the features of radial distribution network operation, object generation of minimum loop and …equal selection of crossover probability are used to further improve the computational efficiency. Finally, a typical example of 33-nodes net is simulated by comparing PGMC with general GA and genetic membrane computing (GMC). The results demonstrate superiority of PGMC on convergence, stability, global searching ability and so on. Show more

Keywords: Membrane computing, distributed computing method, parallel genetic membrane computing, network reconfiguration, minimum loop

DOI: 10.3233/IFS-151704

Citation: Journal of Intelligent & Fuzzy Systems, vol. 29, no. 5, pp. 2287-2298, 2015

Authors: Gu, Guang-Yao | Wei, Fa-Jie | Zhou, Sheng-Han

Article Type: Research Article

Abstract: The aim of this paper is to investigate the hesitant fuzzy linguistic multiple attribute decision making problems based on the hesitant fuzzy linguistic sets and Geometric Bonferroni mean operator. Then, we have proposed two aggregation operators: hesitant fuzzy linguistic geometric Bonferroni mean (HFLGBM) operator and hesitant fuzzy linguistic weighted geometric Bonferroni mean (HFLWGBM) operator. Then, we have utilized HFLWGBM operator to tackle the multiple attribute decision making problems using hesitant fuzzy linguistic information. In the end, a practical example for risk assessment of mass unexpected incident in city is proposed to testify the method in this paper.

Keywords: Multiple attribute decision making, hesitant fuzzy linguistic values, hesitant fuzzy linguistic weighted geometric Bonferroni mean (HFLGWBM) operator, risk assessment, mass unexpected incident

DOI: 10.3233/IFS-151705

Citation: Journal of Intelligent & Fuzzy Systems, vol. 29, no. 5, pp. 2299-2304, 2015

Authors: Jiang, Ping | Dou, Quansheng | Hu, Xiaoying

Article Type: Research Article

Abstract: This paper presents a supervised method for blood vessel segmentation in digital retinal images by a combination of learning and classification. For an image, the method defines and computes pixel strength as primary features for conservatively computing vessel and background pixels as preliminary segmentation, from which the main segmentation selects training data to learn a neutral network (NN) classifier on the fly. Each pixel in the training data set is represented by an 8-D vector composed of intensity descriptor and pixel strength features, and the learned classifier for the image is next applied to classify the undetermined pixels. The segmentation …results are further refined by filtering out the outliers. The method was evaluated on the publicly available DRIVE database, and the results showed better or comparable performance when comparing with other existing solutions in literature. The much better sensitivity and robustness of our approach with different image conditions make it potentially suitable for clinical applications such as automated screening for early diabetic retinopathy detection, and auto- and semi-automatic grading of diabetic retinopathy. Show more

Keywords: Vessel segmentation, learning and classification, pixel strength, neural network

DOI: 10.3233/IFS-151812

Citation: Journal of Intelligent & Fuzzy Systems, vol. 29, no. 5, pp. 2305-2315, 2015