• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.20 no.8
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• pp.534-540
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• 2008

In this paper, the optimal bang-bang control problem of an air-conditioning system with slab thermal storage was formulated by gradient method. Furthermore, the numeric solution obtained by gradient method algorithm was compared with the analytic solution obtained on the basis of maximum principle. The control variable is changed uncontinuously at the start time of thermal storage operation in an analytic solution. On the other hand, it is showed as a continuous solution in a numeric solution. The numeric solution reproduces the analytic solution when a tolerance for convergence is applied severely. It is conceivable that gradient method is effective in the analysis of the optimal bang-bang control of the large-scale system like an air-conditioning system with slab thermal storage.

• Journal of the Korean Institute of Intelligent Systems
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• v.13 no.1
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• pp.37-44
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• 2003

In this paper, we investigated the performance of both DNA coding method and Genetic Algorithm(GA) in numeric pattern (from 0 to 9) recognition. The performance of the DNA coding method is compared to the that of the GA. GA searches effectively an optimal solution via the artificial evolution of individual group of binary string using binary coding, while DNA coding method uses four-type bases denoted by Adenine(A), Cytosine(C), Guanine(G) and Thymine(T). To compare the performance of both method, the same genetic operators(crossover and mutation) are applied and the probabilities of crossover and mutation are set the same values. The results show that the DNA coding method has better performance over GA. The reasons for this outstanding performance are multiple candidate solution presentation in one string and variable solution string length.

• Industrial Engineering and Management Systems
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• v.1 no.1
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• pp.29-45
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• 2002

In this study, we consider infinite supply of raw materials and backlogged demands as given two boundary conditions. And we need not make any specific assumptions about the inter-arrival of external demand and service time distributions. We propose a numeric model and an algorithm in order to compute the first two moments of inter-departure process. Entropy enables us to examine the convergence of this process and to derive measurable relations of this process. Also, lower bound on the variance of inter-departure process plays an important role in proving the existence and uniqueness of an optimal solution for a numeric model and deriving the convergence order of augmented Lagrange multipliers method applied to a numeric model. Through these works, we confirm some structural properties and numeric examples how the validity and applicability of our study.

• Coupled systems mechanics
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• v.2 no.2
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• pp.127-146
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• 2013

A closed-form solution for a fluid-structure system is presented in this article. The closed-form is used to evaluate the finite element method results through a numeric example with consideration of high frequencies of excitation. In the example, the structure is modeled as a cantilever beam with rectangular cross-section including only shear deformation and the reservoir is assumed semi-infinite rectangular filled with compressible fluid. It is observed that finite element results deviate from the closed-form in relatively higher frequencies which is the case for the near field earthquakes.

• Research in Mathematical Education
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• v.14 no.1
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• pp.33-50
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• 2010

The mathematical thinking which transforms important mathematical content and developed into mathematical structure is a vital process in building up mathematical ability as mathematical knowledge based on structure. Such process based on students' recognition of mathematical concept. Developing mathematical thinking into mathematical structure happens when different cognitive units are connected and compressed to form schema of solution, which could happen through some guided problems. The effort of arithmetic approach in problem solving did not necessarily provide students the structure schema of solution. The using of equation to solve the problem is based on the schema of building equation, and is not necessary recognizing the structure of the solution, as the recognition of structure may be lost in the process of simplification of algebraic expressions, leaving only the final numeric answer of the problem.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2002.12a
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• pp.383-386
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• 2002

In this paper, we investigated the pattern recognition performance of the numeric patterns (from 0 to 9) using DNA coding method. The pattern recognition performance of the DNA coding method is compared to the that of the GA(Genetic Algorithm). GA searches effectively an optimal solution via the artificial evolution of individual group of binary string using binary coding, while DNA coding method uses four-type bases denoted by A(Adenine), C(Cytosine), G(Guanine) and T(Thymine), The pattern recognition performance of GA and DNA coding method is evaluated by using the same genetic operators(crossover and mutation) and the crossover probability and mutation probability are set the same value to the both methods. The DNA coding method has better characteristics over genetic algorithms (GA). The reasons for this outstanding performance is multiple possible solution presentation in one string and variable solution string length.

• Proceedings of the Korean Institute of IIIuminating and Electrical Installation Engineers Conference
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• 2001.11a
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• pp.17-22
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• 2001

This paper gave a review of form factor computations in the luminous flux transfer method and practical application of DiLaura's recently developed form factor computation. A systematic analysis of how the results of a contour integration solution differ from those of existing numeric solutions were undertaken with a developed computer simulation program. Various situations between sending and receiving surfaces were considered, including the facing, size, and distance between surfaces.

• Journal of the Korean Operations Research and Management Science Society
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• v.27 no.4
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• pp.185-205
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• 2002

In this study, we consider infinite supply of raw materials and backlogged demands as given two boundary conditions. And we need not make any specific assumptions about the inter-arrival of external demand and service time distributions. Under these situations, the ultimate objective of this study is to prove the variability propagation principle in a pull serial line and is to measure it in terms of the first two moments of the inter-departure process subject to number of cards in each cell. Two preparations are required to achieve this objective : The one is to derive a true lower bound of variance of the inter-departure process. The other is to establish a constrained discrete minimax problem for the no backorder (backlogging) probabilities in each cell. We may get some fundamental results necessary to a completion for the proof through the necessary and sufficient conditions for existence of optimal solution of a constrained discrete minimax problem and the implicit function theorem. finally, we propose a numeric model to measure the variability propagation principle. Numeric examples show the validity and applicability of our study.

• Journal of Institute of Control, Robotics and Systems
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• v.12 no.4
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• pp.328-338
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• 2006

A new evolutionary computation technique, called particle swarm optimization(PSO), has been proposed and introduced recently. PSO has been inspired by the social behavior of flocking organisms, such as swarms of birds and fish schools and PSO is an algorithm that follows a collaborative population-based search model. Each particle of swarm flies around in a multidimensional search space looking for the optimal solution. Then, Particles adjust their position according to their own and their neighboring-particles experience. In this paper, characteristics of PSO such as mentioned are reviewed and compared with GA which is based on the evolutionary mechanism in natural selection. Also dimensionalities of PSO and GA are compared throughout numeric experimental studies. The comparative studies demonstrate that PSO is characterized as simple in concept, easy to implement, and computationally efficient and can generate a high-quality solution and stable convergence characteristic than GA.

• Journal of the Korean Institute of Intelligent Systems
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• v.8 no.6
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• pp.78-84
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• 1998

In this paper, a fuzzy traffic controller using genetic algorithms is presented. Conventional fuzzy traffic controllers use membership functions generated by humans. However, this approach does not guarantee the optimal solution to design the fuzzy controller. Genetic algorithm is a good problem solving method requiring domain-specific knowledge that is often heuristic. To find fuzzy membership functions showing good performance, a fitness function must be defined. However it's not easy in traffic control to define such a function as a numeric expression. Thus, we use simulation approach, namely, the fitness value of a solution is determined by use of a performance measure that is obtained by traffic simulator. The proposed method outperforms the conventional fuzzy controllers.