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

Authors: Wang, Dali | Bai, Ying

Article Type: Research Article

Abstract: In this paper, a number of implementation and algorithmic options for fuzzy logic control applications are presented. The emphases are on the analyses of the computational load and memory requirements of all the processing stages of fuzzy logic control algorithms. Comparisons are made among commonly used techniques and recommendations are provided. The results could be used to guide the design of fuzzy logic controllers for an embedded or hardware implementation.

DOI: 10.3233/IFS-2012-0587

Citation: Journal of Intelligent & Fuzzy Systems, vol. 24, no. 4, pp. 677-683, 2013

Authors: El-Dardery, M. | Ramadan, A.A. | Kim, Y.C.

Article Type: Research Article

Abstract: In this paper, we introduce the notions of L-fuzzy topoenous orders and investigate some of properties. We investigate the relationships among L-fuzzy topoenous orders, L-fuzzy topologies and L-fuzzy interior operators.

Keywords: Quantales, L-fuzzy topologies, L-fuzzy topoenous orders, L-fuzzy interior operators

DOI: 10.3233/IFS-2012-0588

Citation: Journal of Intelligent & Fuzzy Systems, vol. 24, no. 4, pp. 685-691, 2013

Authors: Khayat, Omid | Razjouyan, Javad | Rahatabad, Fereidoun Nowshiravan | Nejad, Hadi Chahkandi

Article Type: Research Article

Abstract: In real world dataset, there are often large amount of discrete data that the concern is the interpolation and/or extrapolation by an approximation tool. Therefore, a training process will be actually used for definition and construction of the approximator parameters. Huge amount of data may lead to high computation time and a time consuming training process. To this concern a fast learnt fuzzy neural network as a robust function approximator and predictor is proposed in this paper. The learning procedure and the structure of the network is described in detail. Simplicity and fast learning process are the main features of …the proposing Self-Organizing Fuzzy Neural Network (SOFNN), which automates structure and parameter identification simultaneously based on input-target samples. First, without need of clustering, the initial structure of the network with the specified number of rules is established, and then a training process based on the error of other training samples is applied to obtain a more precision model. After the network structure is identified, an optimization process based on the known error criteria is performed to optimize the obtained parameter set of the premise parts and the consequent parts. At the end, comprehensive comparisons are made with other approaches to demonstrate that the proposed algorithm is superior in term of compact structure, convergence speed, memory usage and learning efficiency. Show more

Keywords: Self-organizing fuzzy neural network, hybrid learning algorithm, function approximation, prediction, chaotic time series

DOI: 10.3233/IFS-2012-0589

Citation: Journal of Intelligent & Fuzzy Systems, vol. 24, no. 4, pp. 693-701, 2013

Authors: Deperlioglu, Omer

Article Type: Research Article

Abstract: The exact modeling of power converter circuit that includes several semiconductor switching devices is not easy due to the non-linear and time varying characteristics of the switching devices. Thus, controlling the system effectively without exact mathematical model is very important. The rule based controller (RBC) can easily be used in the control of any systems when an exact mathematical model of the system cannot be obtained. In this paper, a RBC for DC-DC converter is proposed for output voltage control of DC-DC converter. As compared to conventional fuzzy logic control (FLC), it provides improved performances in terms of overshoot limitation …and sensitivity to load and line voltage variations. Simulation and experimental results of buck converter confirm the validity of proposed control technique. Show more

Keywords: Electronic switching systems, DC-DC power conversion, fuzzy systems, rule based systems

DOI: 10.3233/IFS-2012-0590

Citation: Journal of Intelligent & Fuzzy Systems, vol. 24, no. 4, pp. 703-711, 2013

Authors: Vlachos, Aristidis

Article Type: Research Article

Abstract: The maintenance scheduling problem of thermal generators is a large-scale combinatorial optimization with constraints. In this paper an Ant Colony System (ACS) algorithm, one of the Ant Colony Optimization (ACO) algorithms, is proposed for the maintenance scheduling problem. This ant colony optimization method allows the “agents” of an ant colony to deposit a small amount of pheromone trail to every path that has been explored, thus passing on to the other agents the information concerning the best solution. With the iterations we construct the final solution. This method is called “positive feedback”. The basic optimization routine is reinforced with the …introduction of elitist ants who make the best solution stronger. The algorithm is applied to a real-scale system, and further experimenting leads to results that are commented. Show more

Keywords: Thermal Generator Maintenance Scheduling Problem, Ant Colony Optimization, Ant Colony System

DOI: 10.3233/IFS-2012-0591

Citation: Journal of Intelligent & Fuzzy Systems, vol. 24, no. 4, pp. 713-723, 2013

Authors: Esi, Ayhan | Hazarika, Bipan

Article Type: Research Article

Abstract: An ideal I is a family of subsets of positive integers $\mathbb{N}$ which is closed under taking finite unions and subsets of its elements. In [8], Kostyrko et al., introduced the concept of ideal convergence as a sequence (xk ) of real numbers is said to be I-convergent to a real number $\ell$, if for each ϵ > 0 the set $\{k\in\mathbb{N}:|x_{k}-\ell|\geq\varepsilon\}$ belongs to I. The aim of this paper is to introduce and study the notion of λ-ideal convergence in intuitionistic fuzzy 2-normed space as a variant of the notion of ideal convergence. Also Iλ -limit points and Iλ …-cluster points have been defined and the relation between them has been establish. Furthermore, Cauchy and Iλ -Cauchy sequences are introduced and studied. Show more

Keywords: Ideal convergence, intuitionistic fuzzy normed space, λ-convergence

DOI: 10.3233/IFS-2012-0592

Citation: Journal of Intelligent & Fuzzy Systems, vol. 24, no. 4, pp. 725-732, 2013

Authors: Kamali, Hamid Reza | Shahnazari-Shahrezaei, Parisa | Kazemipoor, Hamed

Article Type: Research Article

Abstract: Nowadays, time series are widely used in forecasting. With the advent of fuzzy sets, a new gate in time series has been opened up as fuzzy time series. Basically, more information of future is being examined in fuzzy time series forecasting. Fuzzy time series methods have been extensively considered in articles and researches, especially in forecasting the historical data of statistics of Alabama University's enrollments. In this paper, two different methods are presented to accurately forecast fuzzy time series and achieve more information. To verify and validate the performance of proposed methods, four different time series including, time series with …cyclic variations, a combination of linear trend and cyclic variations, exponential trend, and real values of statistics of Alabama University's enrollments are considered, too. At the end of this paper, the performance of proposed methods and existing methods in the literature are compared with each other. Show more

Keywords: Fuzzy sets, fuzzy time series, time-variant, forecasting

DOI: 10.3233/IFS-2012-0593

Citation: Journal of Intelligent & Fuzzy Systems, vol. 24, no. 4, pp. 733-741, 2013

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

Article Type: Research Article

Abstract: Triangular intuitionistic fuzzy numbers (TIFNs) are useful to deal with ill-known quantities in decision making problems. The focus of this paper is on multi-attribute decision making (MADM) problems in which the attribute values are expressed with TIFNs and the information on attribute weights is incomplete, which are solved by developing a new decision method based on possibility mean and variance of TIFNs. The notions of possibility mean and variance for TIFNs are introduced as well as the possibility standard deviation. A new ranking approach for TIFNs is developed according to the ratio of the possibility mean to the possibility standard …deviation. Hereby we construct a bi-objective programming model, which maximizes the ratios of the possibility mean to the possibility standard deviation for membership and non-membership functions on alternative's overall attribute values. Using the lexicographic approach, the bi-objective programming model is transformed into two non-linear programming models, which are further transformed into the linear programming models by using the variable transformation. Thus, we can obtain the maximum ratios of the possibility mean to the possibility standard deviation, s are used to rank the alternatives. A numerical example is examined to demonstrate applicability and implementation process of the proposed method. Show more

Keywords: Multi-attribute decision making, triangular intuitionistic fuzzy number, possibility mean, possibility variance

DOI: 10.3233/IFS-2012-0594

Citation: Journal of Intelligent & Fuzzy Systems, vol. 24, no. 4, pp. 743-754, 2013

Authors: Wang, Li-Ling | Li, Deng-Feng | Zhang, Shu-Shen

Article Type: Research Article

Abstract: Interval-valued intuitionistic fuzzy (IVIF) sets are a useful tool to deal with fuzziness inherent in decision data and decision making process. The aim of this paper is to develop a methodology for solving multiattribute decision making (MADM) with both ratings of alternatives on attributes and weights being expressed with IVIF sets. In this methodology, a weighted Euclidean distance between IF sets is defined using weights of IF sets. A pair of nonlinear programming models is constructed based on the concept of the relative closeness coefficients and the distance defined. Two simpler auxiliary nonlinear programming models are further derived to calculate …the relative closeness coefficient intervals of alternatives to the IVIF positive ideal solution, which can be used to generate ranking order of alternatives based on the concept of likelihood of interval numbers. The method proposed in this paper is illustrated with a real example. Show more

Keywords: Intuitionistic fuzzy set, multiattribute decision making, mathematical programming, uncertainty, fuzzy system

DOI: 10.3233/IFS-2012-0595

Citation: Journal of Intelligent & Fuzzy Systems, vol. 24, no. 4, pp. 755-763, 2013

Authors: Verma, Manjit | Kumar, Amit | Singh, Pushpinder | Singh, Yaduvir

Article Type: Research Article

Abstract: A new approach for vague risk analysis based on the ranking of trapezoidal vague sets is proposed. Firstly, a new method for ranking of vague sets is presented. Then, the proposed method is applied to developed a new method for dealing with vague risk analysis problems. This analysis helps us to find out the probability of failure of each components of combustion system, which could be used for managerial decision making and future system maintenance strategy. The proposed method provides a useful way for handling vague risk analysis problems.

Keywords: Ranking function, vague sets, fuzzy sets, vague risk analysis

DOI: 10.3233/IFS-2012-0596

Citation: Journal of Intelligent & Fuzzy Systems, vol. 24, no. 4, pp. 765-773, 2013