• Proceedings of the KIEE Conference
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• 1995.11a
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• pp.64-66
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• 1995

This paper presents a new approach to evaluate optimal basic reliability indices of electric distribution systems using genetic algorithm. The use of optimal reliability evaluation is an important aspect of distribution system planning and operation to determine adequacy reliability level of each area. In this paper, the reliability model is based on the analytical method, connecting component failure to load point outage in each section. The proposed method applies genetic algorithm to calculate the optimal values of basic reliability indices, ie. failure rate and repair time, for a load point in the power distribution system, subject to minimizing interruption cost. Test results for the model system are reported in the paper compared with a direct optimization method(gradient projection).

• Journal of applied mathematics & informatics
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• v.29 no.3_4
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• pp.831-846
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• 2011

There are several methods, in the literature, for finding the fuzzy optimal solution of fully fuzzy transportation problems (transportation problems in which all the parameters are represented by fuzzy numbers). In this paper, the shortcomings of some existing methods are pointed out and to overcome these shortcomings, a new method (based on fuzzy linear programming formulation) is proposed to find the fuzzy optimal solution of unbalanced fuzzy transportation problems with a new representation of trapezoidal fuzzy numbers. The advantages of the proposed method over existing method are discussed. Also, it is shown that it is better to use the proposed representation of trapezoidal fuzzy numbers instead of existing representation of trapezoidal fuzzy numbers for finding the fuzzy optimal solution of fuzzy transportation problems. To illustrate the proposed method a fuzzy transportation problem (FTP) is solved by using the proposed method and the obtained results are discussed. The proposed method is easy to understand and to apply for finding the fuzzy optimal solution of fuzzy transportation problems occurring in real life situations.

• Journal of applied mathematics & informatics
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• v.24 no.1_2
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• pp.399-409
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• 2007

In this paper we use iterative dynamic programming in the discrete case to solve a wide range of the nonlinear equations systems. First, by defining an error function, we transform the problem to an optimal control problem in discrete case. In using iterative dynamic programming to solve optimal control problems up to now, we have broken up the problem into a number of stages and assumed that the performance index could always be expressed explicitly in terms of the state variables at the last stage. This provided a scheme where we could proceed backwards in a systematic way, carrying out optimization at each stage. Suppose that the performance index can not be expressed in terms of the variables at the last stage only. In other words, suppose the performance index is also a function of controls and variables at the other stages. Then we have a nonseparable optimal control problem. Furthermore, we obtain the path from the initial point up to the approximate solution.

• Korean Management Science Review
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• v.26 no.3
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• pp.145-156
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• 2009

The probability distribution of the repair process should be determined to choose the optimal spare level of a weapon system with a queueing model. Though most weapon systems have a multi-step repair process, previous studies use the exponential distribution for the multi-step repair process. But the PH distribution is more appropriate for this case. We utilize the PH distribution on a queueing model and solve it with MGM(Matrix Geometric Method). We derive the optimal spare level using the PH distribution and show the difference of results between the PH and exponential distribution.

• Journal of the Korean Operations Research and Management Science Society
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• v.20 no.3
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• pp.105-122
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• 1995

Based on linear models, the inference about the true measurement x$_{f}$ and the optimal designs x (nx1) for the calibration experiments are considered via Baysian statistical decision analysis. The posterior distribution of x$_{f}$ given the observation y$_{f}$ (qxl) and the calibration experiment is obtained with normal priors for x$_{f}$ and for themodel parameters (.alpha., .betha.). This posterior distribution is not in the form of any known distributions, which leads to the use of a numerical integration or an approximation for the calculation of the overall expected loss. The general structure of the expected loss function is characterized in the form of a conjecture. A near-optimal design is obtained through the approximation nof the conditional covariance matrix of the joint distribution of (x$_{f}$ , y$_{f}$ $^{T}$ )$^{T}$ . Numerical results for the univariate case are given to demonstrate the conjecture and to evaluate the approximation.n.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.3 no.1
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• pp.105-111
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• 2003

This paper is researching the storing of 40 different kinds of conditions. Such as, car speed, delay in starting time and the volume of cars in traffic. Through the use of a central nervous networking system or AI, using 10 different intersecting roads. We will improve the green traffic light. And allow more cars to easily flow through the intersections. Now days, with increasing many vehicles on restricted roads, the conventional traffic light creates prove startup-delay time and end-lag-time. The conventional traffic light loses the function of optimal cycle. And so, 30-45% of conventional traffic cycle is not matched to the present traffic cycle. In this paper proposes electro sensitive traffic light using fuzzy look up table method which will reduce the average vehicle waiting time and improve average vehicle speed. Computer simulation results prove that reducing the average vehicle waiting time which proposed considering passing vehicle length for optimal traffic cycle is better than fixed signal method which dosen't consider vehicle length.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2017.05a
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• pp.137-139
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• 2017

Modern manufacturing fields have been changed to use optimal manufacturing volume on the optimal demand prediction. This research is to compare the prediction capability of various prediction methods. And then, it is to suggest a flexible selection of the optimal prediction method according to optimal prediction capability.

• Journal of applied mathematics & informatics
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• v.28 no.5_6
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• pp.1249-1262
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• 2010

An approximate alternating linearization decomposition method, for minimizing the sum of two convex functions with some separable structures, is presented in this paper. It can be viewed as an extension of the method with exact solutions proposed by Kiwiel, Rosa and Ruszczynski(1999). In this paper we use inexact optimal solutions instead of the exact ones that are not easily computed to construct the linear models and get the inexact solutions of both subproblems, and also we prove that the inexact optimal solution tends to proximal point, i.e., the inexact optimal solution tends to optimal solution.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.60 no.3
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• pp.517-523
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• 2011

A lot of DSM (Demand Side Management) programs have been implemented to promote the effective utilization of resources and the rational development of power industry, and various economic analyses and policy-based studies on DSM have been executed to determine effective subsidy budget. In this paper, a new objective function for deciding an optimal incentive allocation among various programs is presented by introducing the maximization of the total saving power of the programs. For simplicity, the objective function and the constraints is linearized to apply LP(Linear Programming) method. LP program based on Simplex Method was developed by MATLAB. An optimal incentive allocation of 4 DSM programs is presented by the use of the developed MATLAB program.

• Journal of Power Electronics
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• v.4 no.4
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• pp.228-236
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• 2004

This paper describes the optimal current-control of a permanent magnet synchronous motor by the use of robust and simple current controllers, based upon the analytical procedure known as the inverse LQ (ILQ) design method. The ILQ design method is a strategy for finding the optimal gains based on pole assignment without solving the Riccati equation. It is very important to keep the motor in robust servo-lock. By experiments and simulations, we will show that the ILQ optimal servo-system with servo-lock is more insensitive at low speeds to variations in armature inductance than the standard PI servo-system. Variations in armature inductance have the greatest influence on the responses of a servo-system.