• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
• /
• v.17 no.5
• /
• pp.118-125
• /
• 2003

This paper presents a scheme for the placement of dispersed generator systems(DGs) based on load model in unbalanced systems. Groups of each individual load model consist of residential, industrial, commercial, official and agricultural load The main idea of solving fuzzy goal programming is to transform the original objective function and constraints into the equivalent multi-objectives functions with fuzzy sets to evaluate their imprecise nature for the criterion of power loss minimization, the number or total capacity of DGs and the bus voltage deviation, and then solve the problem using genetic algorithm The method proposed is applied to IEEE 13 bus unbalanced distribution systems to demonstrate its effectiveness.

• Proceedings of the KIEE Conference
• /
• 2001.11b
• /
• pp.350-353
• /
• 2001

This study proposes a new method for the transmission system expansion planning using the fuzzy integer programming. It presents stepwise cost characteristics analysis which is a practical condition of an actual systems. A branch and bound method which includes the network flow method and the maximum flow-minimum cut set theorem has been used in order to proceed the stepwise cost characteristics analysis. Uncertainties of the permission of the construction cost and not strict reserve rate and load forecasting of expansion planning have been included and also processed using fuzzy set theory in this study. In order to proceed the latter analysis, the solving procedure is illustrated in detail by branch and bound method which includes the network flow method and maximum flow-minimum cut set theorem. Finally, case studies on 21-bus test system show that the algorithm proposed is efficiently applicable to the practical expansion planning of transmission systems in future.

• Journal of Korean Society for Quality Management
• /
• v.21 no.2
• /
• pp.194-214
• /
• 1993

This paper purports to study on interactive fuzzy goal programming model which leads to the compromise solution which the decision maker satisfies through the interactive approach. We also attempted to calculate local proxy preference function from utility function of sum-of-logarithms in connection with marginal rate of substitution and interactive approach for the purpose of applying weight of multiobjective function. In an attempt to grasp compromise solution from fuzzy efficient solution, we decided to take the interactive method and presented stopping rule for this.

• Journal of Electrical Engineering and Technology
• /
• v.4 no.2
• /
• pp.234-239
• /
• 2009

In this article we present the simulation results of induction motor speed regulation by direct torque control with a classic PI regulator. The MATLAB Simulink programming environment is used as a simulation tool. The results obtained, using a fuzzy logic, shows the importance of this method in the improvement of the performance of such regulation.

• Proceedings of the IEEK Conference
• /
• 1999.06a
• /
• pp.788-791
• /
• 1999

In recent years, many studies have been conducted on fuzzy control since it can surpass the conventional control in several respects. In this paper, numerical stability analysis methodology for the singleton-type linguistic fuzzy control systems is proposed. The Proposed stability analysis is not the analytical method but the numerical method using the convex optimization technique of Quadratic Programming (QP) and Linear Matrix Inequalities (LMI).

• International Journal of Fuzzy Logic and Intelligent Systems
• /
• v.2 no.1
• /
• pp.20-25
• /
• 2002

This paper presents a genetic programming based evolutionary strategy for on-line adaptive learnable evolvable hardware. Genetic programming can be useful control method for evolvable hardware for its unique tree structured chromosome. However it is difficult to represent tree structured chromosome on hardware, and it is difficult to use crossover operator on hardware. Therefore, genetic programming is not so popular as genetic algorithms in evolvable hardware community in spite of its possible strength. We propose a chromosome representation methods and a hardware implementation method that can be helpful to this situation. Our method uses context switchable identical block structure to implement genetic tree on evolvable hardware. We composed an evolutionary strategy for evolvable hardware by combining proposed method with other's striking research results. Proposed method is applied to the autonomous mobile robots cooperation problem to verify its usefulness.

• Journal of applied mathematics & informatics
• /
• v.26 no.5_6
• /
• pp.861-876
• /
• 2008

This paper concerns a new method called Fuzzy Supervised Method for error matrix, the method has developed based on Adoptive Neuro- Fuzzy Inference Systems(ANFIS). For the performance point of view initially the new method tested with trial data and then this paper applies the proposed method with real world problems. So that this paper generated 1000 random error matrices in programming language [R] and then it tests the new proposed method for the error matrices. The results of Fuzzy Supervised Method given in terms of Kappa Index and Congalton Accuracy Indexes, and performance of Fuzzy Supervised Method has evaluated by using Pearson's test.

• Proceedings of the Korean Institute of Intelligent Systems Conference
• /
• 1993.06a
• /
• pp.1033-1036
• /
• 1993

Most of the today realized fuzzy logic control applications has been designed using different heuristic approaches for synthesis and implemented with conventional programming languages on general purpose microcontrollers. This paper aims to present a new methodology to design a fuzzy controller. The methodology is based on the Cell-to-Cell approach to extract the control law. A set of fuzzy rules is then found by using a FAM (Fuzzy associative memories) approach. The proposed procedure was implemented to control the rotor position of a DC motor.

• Journal of Korean Association for Spatial Structures
• /
• v.3 no.2 s.8
• /
• pp.77-83
• /
• 2003

This paper presents decision making method of structural multi-objective fuzzy optimum problem. The data and behavior of many engineering systems are not know precisely and the designer is required to design the system in the presence of fuzziness in the multi-goals, constraints and consequences of possible actions. In this paper, in order to find a satisfactory solution, the membership functions are constructed for the fuzzy objectives subject to the fuzzy constraints, and two approaches are presented by using the different types of fuzzy decision making. Thus, multi-objective fuzzy optimum problem can be converted into single objective non-fuzzy optimum problem and satisfactory solution of the multi-objective fuzzy optimum problem can be found with general optimum programming. Illustrative numerical example of the ten bar truss for minimum weight and minimum deflection is provided to demonstrate the process of finding the solution and the results are discussed.

• Industrial Engineering and Management Systems
• /
• v.13 no.1
• /
• pp.29-42
• /
• 2014

Extensive research has been conducted on supplier evaluation and selection as a strategic and crucial component of supply chain management in recent years. However, few articles in the previous literature have been dedicated to the use of fuzzy inference systems as an aid in decision-making. Therefore, this essay attempts to demonstrate the application of this method in evaluating suppliers, based on a comprehensive framework of qualitative and quantitative factors besides the effect of gradual coverage distance. The purpose of this study is to investigate the applicability of the numerous measures and metrics in a multi-objective optimization problem of the supply chain network design with the aim of managing the allocation of orders by coordinating the production lines to satisfy customers' demand. This work presents a dynamic non-linear programming model that examines the important aspects of the strategic planning of the manufacturing in supply chain. The effectiveness of the configured network is illustrated using a sample, following which an exact method is used to solve this multi-objective problem and confirm the validity of the model, and finally the results will be discussed and analyzed.