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

Authors: Roy, S. | Sen, M.

Article Type: Research Article

Abstract: In this paper using ideal I and Orlicz function M together with a general multiplier double sequence Λ = (λnk ), n, k ∈ N of non-zero real numbers, we introduce some new type of I-convergent fuzzy real-valued double sequence spaces. We have studied different topological properties of these sequence spaces. Also we have characterized the multiplier problem and some inclusion relations involving these classes of sequences are obtained. Further some equivalent statements involving these classes of sequences are established.

Keywords: Multiplier sequence spaces, Orlicz function, I-convergent, solid space, monotone, sequence algebra, convergence free

DOI: 10.3233/IFS-130832

Citation: Journal of Intelligent & Fuzzy Systems, vol. 26, no. 1, pp. 431-437, 2014

Authors: Niknam, Taher | Bavafa, Farhad | Jabbari, Masoud

Article Type: Research Article

Abstract: Charged System Search (CSS) is a new evolutionary algorithm inspired by the interaction between charged particles. This paper presents a modified CSS (SACSS) algorithm, which highly improves the performance of CSS and applies it to solve the unit commitment (UC) problem. In order to achieve better performance and higher speed in solving the UC problem, a self-adaptive reformation technique with tree updated schemes has been implemented. The proposed algorithm has been tested on 10, 20, 40 and 100 unit systems for one-day and scheduling horizon. The results are compared with the solutions obtained from other methods such as Lagrangian Relaxation …(LR), Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Bacterial Foraging (BF) and Shuffled Frog Leaping Algorithm (SFLA). The results show the high performance and convergence speed of SACSS. Show more

Keywords: Charged system search, economic dispatch, generation scheduling, optimization algorithms, unit commitment

DOI: 10.3233/IFS-130855

Citation: Journal of Intelligent & Fuzzy Systems, vol. 26, no. 1, pp. 439-449, 2014

Authors: Gegov, Alexander | Sanders, David | Vatchova, Boriana

Article Type: Research Article

Abstract: This paper proposes a complexity management methodology for fuzzy systems with feedback rule bases. The methodology is based on formal methods for presentation, manipulation and transformation of fuzzy rule bases. First, Boolean matrices are used for formal presentation of rule bases. Then, binary merging operations are used for formal manipulation of rule bases. Finally, repetitive merging operations are used for formal transformation of rule bases. The formal methods facilitate the understanding and modelling of fuzzy systems in terms of interacting subsystems. In particular, the methods reduce the qualitative complexity in fuzzy systems by improving the transparency of the rule bases.

Keywords: Fuzzy systems, complexity management, formal methods, rule bases, fuzzy networks

DOI: 10.3233/IFS-130857

Citation: Journal of Intelligent & Fuzzy Systems, vol. 26, no. 1, pp. 451-464, 2014

Authors: Lee, Ying Loong | El-Saleh, Ayman A. | Ismail, Mahamod

Article Type: Research Article

Abstract: Premature convergence has been recognized as one of the major drawbacks of particle swarm optimization (PSO) algorithms. In particular, the lack of diversity in PSO performance is an essential cause that commonly results in high susceptibility to prematurely converge to local optima especially in complex multimodal problems with high dimensionality. This paper presents a new PSO operational strategy based on gravity concept to address the aforementioned drawback and it is named as gravity-based particle swarm optimizer (GPSO). In addition, GPSO is further modified by adopting the cooperation concept of the conventional cooperative particle swarm optimizer (CPSO) to develop an extended …version of GPSO called cooperative gravity-based particle swarm optimizer (CGPSO). Simulation results manifest that CGPSO performs satisfactorily on unimodal functions while it generally performs better on multimodal functions than GPSO and other conventional PSO variants. Finally, the proposed GPSO and CGPSO are applied into the problem of optimizing the detection performance of soft decision fusion for cooperative spectrum sensing in cognitive radio networks. For this problem, computer simulations show that the proposed CGPSO outperforms all other PSO variants in terms of quality of solutions whereas GPSO is found to be the best when the computational cost is taken into account. Show more

Keywords: Continuous PSO, GPSO, CGPSO, cooperative swarms, optimization

DOI: 10.3233/IFS-130872

Citation: Journal of Intelligent & Fuzzy Systems, vol. 26, no. 1, pp. 465-481, 2014

Authors: Ding, Sibo

Article Type: Research Article

Abstract: The classic newsboy problem assumes the market demand to be a random variable. However, when the decision maker wants to expand the market share, he has to provide a subjective estimate of new market demand distribution due to the lack of historical data. Thus, randomness and uncertainty simultaneously appear in a newsboy problem. The aim of this work is to extend the analysis of the classic newsboy problem to the case when market demand is assumed to be an uncertain random variable. A mathematical model is formulated, and a simple equation is derived for determining the optimal order quantity to …maximize the expected profit. Furthermore, uncertain random newsboy problem is compared with stochastic newsboy problem and uncertain newsboy problem. Three kinds of newsboy problems have the same optimal service level. The latter two newsboy problems are two special cases of uncertain random newsboy problem. Finally, a numerical example has been presented to illustrate the model. Show more

Keywords: Newsboy problem, uncertainty theory, chance theory, uncertain random programming, uncertain random variable

DOI: 10.3233/IFS-130919

Citation: Journal of Intelligent & Fuzzy Systems, vol. 26, no. 1, pp. 483-490, 2014

Authors: Zhang, Shuai | Yu, Dejian

Article Type: Research Article

Abstract: This paper investigates the methods of dealing with the information aggregation problems in the context of intuitionistic fuzzy set and interval-valued intuitionistic fuzzy set respectively. As anything is highly relevant in the real world, it is important and significant for researchers to descript the relationships between any two subjects mathematically. The Choquet integral is a powerful tool to depict the interrelationships between objects. In this paper, we first propose the Einstein based intuitionistic fuzzy Choquet geometric (EIFCG) operator and Einstein based interval-valued intuitionistic fuzzy Choquet geometric (EIIFCG) operator. Then, the relationship between the EIFCG operator and the IFCG operator is …investigated. We also study series of the desirable properties of the EIFCG operator and EIIFCG operator. Furthermore, an intuitionistic fuzzy multi-criteria decision making method based on the EIFCG operator is proposed. We also focus on the correlations with other intuitionistic fuzzy multi-criteria decision making method. Show more

Keywords: Intuitionistic fuzzy set, interval-valued intuitionistic fuzzy set, aggregation operator, Choquet Integral, Einstein operation laws

DOI: 10.3233/IFS-130924

Citation: Journal of Intelligent & Fuzzy Systems, vol. 26, no. 1, pp. 491-500, 2014

Authors: Erguzel, Turker Tekin | Akbay, Erbil

Article Type: Research Article

Abstract: Artificial life uses biological knowledge and techniques to solve different engineering, management, control and computational problems. Natural systems teach us that very simple individual organisms can form systems capable of performing highly complex tasks by dynamically interacting with each other. In this study, artificial life based approaches are handled and incorporated to enable a real-time water level control. The process was first modelled using NARX type Artificial Neural Network. A fuzzy controller was then attached to the model. For a better performance, fuzzy controller membership function boundary values and action values were optimized simultaneously. The optimization process was performed using …genetic algorithm and ant colony optimization algorithm, respectively. Finally, the performance of the controllers was discussed further by considering the system outputs. The developed structure replaces the tedious process of trial-and-error for better combination of fuzzy parameters and can settle the problem of designing fuzzy controller without an expert's experience. Show more

Keywords: Process control, fuzzy controller, ant colony optimization algorithm, genetic algorithm, artificial neural network

DOI: 10.3233/IFS-131003

Citation: Journal of Intelligent & Fuzzy Systems, vol. 26, no. 1, pp. 501-516, 2014

Authors: Kavousi-Fard, Abdollah | Niknam, Taher | Golmaryami, Marjan

Article Type: Research Article

Abstract: Distribution systems as the final link between the production side and the consumers engage the most contributions to the unavailability of electrical services. In fact, in the operation of distribution systems, forecasting the short term load is a precious and critical task. With a more accurate load forecasting, the distribution system operation management would be improved and more economical trade off with the electricity market can be achieved. However, as the result of high nonlinearity and variation of the loads in distribution systems, short term load forecasting in these systems is hard and complex. In this regard, this paper proposes …a new hybrid method based on firefly algorithm (FA) and artificial neural network (ANN) to reach a more reliable and accurate forecasting model. The proposed method makes use of both the learning ability of ANN and the powerful search ability of FA to create a nonlinear mapping between the input and output load pattern data. In contrast to the other evolutionary based on ANN training methods, this work preserves a good balance between ANN traditional training techniques such as back-propagation method and evolutionary random search ability of FA in a hybrid framework. Meanwhile, a new sufficient two-stage modification method is proposed for FA to improve its ability in both the local and global searches. The feasibility and satisfying performance of the proposed method is examined on the practical daily peak load of a part of Shiraz distribution system, Iran. Show more

Keywords: Modified firefly algorithm (MFA), artificial neural network (ANN), short term load forecasting (STLF)

DOI: 10.3233/IFS-131025

Citation: Journal of Intelligent & Fuzzy Systems, vol. 26, no. 1, pp. 517-522, 2014