• Journal of Korea Water Resources Association
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• v.41 no.7
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• pp.725-735
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• 2008

Due to recent climate change, flood damages have been increased, but it is difficult to construct large hydraulic structure for flood control such as dam because of environmental, economical and political problems. For this reason, several researches and studies have tried to use washland as an alternative of hydraulic facility. Because sizes of washlands are usually smaller than those of dams or reservoirs, there can be many available locations for washlands in a basin and proper combination of these locations can reduce flood disasters efficiently. However, in case there are many available locations for washland and many combinations to consider, it is very difficult to determine the optimal combination which yields to provide the maximum benefit. For the more, hydraulic approach that used in previous studies to calculate flood reduction effect needs a lot of time for calculation and sometimes can not give the final result. In this study, the flood reduction effect of washland is calculated by hydrologic approach and decision making model for optimal location of washland using genetic algorithm for determination of optimal solution is developed. The developed model has been applied to the Ansung River basin in order to examine the applicability and the application result shows that developed model can be used as decision making model for washland.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.36 no.8
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• pp.921-927
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• 2012

Reliability-based design optimization (RBDO) can be used to determine the reliability of a system by means of probabilistic design criteria, i.e., the possibility of failure considering stochastic features of design variables and input parameters. To assure these criteria, various reliability analysis methods have been developed. Most of these methods assume that distribution functions are continuous. However, in real problems, because real data is often discrete in form, it is important to estimate the distributions for discrete information during reliability analysis. In this study, we employ the Akaike information criterion (AIC) method for reliability analysis to determine the best estimated distribution for discrete information and we suggest an RBDO method using AIC. Mathematical and engineering examples are illustrated to verify the proposed method.

• Journal of Korean Society for Quality Management
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• v.41 no.1
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• pp.109-118
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• 2013

Purpose: Given the several proper models for given mixture components-process variables experimental data, we propose a strategy to find the optimal condition in which the performance of the responses is well-behaved under those models. Methods: Given the mixture experimental data with process variables, first we choose the reasonable starting models among the class of admissible product models based on the model selection criteria and then, search for the candidate models that are the subset models of the starting model by the sequential variable selection method or all possible regressions procedure. Good candidate models are screened by the evaluation of model selection criteria and checking the residual plots for the validity of the model assumption. Results: We propose a strategy to find the optimal condition in which the performance of the responses is well-behaved under those good candidate models by adopting the optimization methods developed in multiple responses surface methodology. Conclusion: A strategy is proposed to find the optimal condition in which the performance of the responses is well-behaved under those proper combined models. This strategy to find the optimal condition is illustrated with the example in this paper.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.45 no.6
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• pp.95-107
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• 2008

In this paper, we propose a fast mode decision method for temporal and spatial scalability to reduce computational complexity of mode decision that used to be computationally one of the most intensive processes of the MPEG-4 AVC|H.264 SE(Scalable Extension) encoding. For temporal scalability, we propose an early skip method and MHM(mode history map) method. The early skip method confines macroblock modes of backward and forward frames within selected a few candidates. The MHM method utilizes stored information of frames inside a GOP of lower levels for the decision of MHM at higher level. For the spatial scalability, we propose the method that uses a candidate mode according to the MHM method and adds the BL_mode as candidates. The proposed scheme reduces the number of candidate modes to reduce computational complexity in mode decision. The proposed scheme reduces total encoding time by about 52% for temporal scalability and 47% for spatial scalability without significant loss of RD performance.

• The KIPS Transactions:PartD
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• v.9D no.4
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• pp.555-560
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• 2002

Subsequence matching, which consists of index searching and post-processing steps, is an operation that finds those subsequences whose changing patterns are similar to that of a given query sequence from a time-series database. This paper discusses optimization of post-processing for subsequence matching. The common problem occurred in post-processing of previous methods is to compare the candidate subsequence with the query sequence for discarding false alarms whenever each candidate subsequence appears during index searching. This makes a sequence containing candidate subsequences to be accessed multiple times from disk, and also have a candidate subsequence to be compared with the query sequence multiple times. These redundancies cause the performance of subsequence matching to degrade seriously. In this paper, we propose a new optimal method for resolving the problem. The proposed method stores ail the candidate subsequences returned by index searching into a binary search tree, and performs post-processing in a batch fashion after finishing the index searching. By this method, we are able to completely eliminate the redundancies mentioned above. For verifying the performance improvement effect of the proposed method, we perform extensive experiments using a real-life stock data set. The results reveal that the proposed method achieves 55 times to 156 times speedup over the previous methods.

• Journal of KIISE:Software and Applications
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• v.30 no.3_4
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• pp.326-338
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• 2003

The objective of a neural network design and model selection is to construct an optimal network with a good generalization performance. However, training data include noises, and the number of training data is not sufficient, which results in the difference between the true probability distribution and the empirical one. The difference makes the teaming parameters to over-fit only to training data and to deviate from the true distribution of data, which is called the overfitting phenomenon. The overfilled neural network shows good approximations for the training data, but gives bad predictions to untrained new data. As the complexity of the neural network increases, this overfitting phenomenon also becomes more severe. In this paper, by taking statistical viewpoint, we proposed an integrative process for neural network design and model selection method in order to improve generalization performance. At first, by using the natural gradient learning with adaptive regularization, we try to obtain optimal parameters that are not overfilled to training data with fast convergence. By adopting the natural pruning to the obtained optimal parameters, we generate several candidates of network model with different sizes. Finally, we select an optimal model among candidate models based on the Bayesian Information Criteria. Through the computer simulation on benchmark problems, we confirm the generalization and structure optimization performance of the proposed integrative process of teaming and model selection.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2003.10a
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• pp.275-279
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• 2003

2002년 현재 서울시는 99.99%에 이르는 높은 상수도 보급율에 비하여 유수율은 선진국의 수준에 이르지 못하고 있는 실정이다. 이는 정수장에서 배수지까지 연결되는 송수관과 배수지에서 각 가정으로 보낼 때 사용되는 배급수관에서의 누수 발생이 주 원인이며, 이는 곧 체계적인 관망 설계 및 운영이 미흡하기 때문인 것으로 지적되고 있다. 상수관로의 누수현상을 해결하고 효과적인 관리를 위한 근본적인 대책으로 노후관로의 교체가 필요하게 된다. 또한 노후관망 교체 등 유사시에 안정적인 상수의 공급을 위해 배수지간을 연결하는 대안 관로를 둘 필요가 있으며, 이러한 관망의 경로를 적절하게 설계해야 하는 것도 주요한 상수 공급 문제 중의 하나이다. 2000년 서울시 수도 정비 기본 계획의 관망 정비계획에 따르면 배수관리를 원활하게 하고 누수를 효율적으로 탐지·방지하기 위한 가장 이상적인 관망구성은 배수지 중심의 블록 시스템으로 보고 있다. 이와 같은 문제점들을 기반으로 하여, 본 연구는 GIS를 이용하여 효과적으로 노후관망을 관리하고, 대안 관망경로를 구축하는 시스템을 제안하였다. 본 연구에서는 배수지를 중심으로 한 블록 단위기반의 관망 노후도를 체계적으로 분석하는 시스템과 함께, 유사시를 대비한 최단/최적의 대안 경로를 산출하는 시스템을 구현하여 이를 서울 일부지역에 적용하여 그 유용성을 점검하였다. 상수도 관망의 설치 계획은 상수도 시설의 규모의 확장과 시설계량에 있어 대규모의 비용과 시간이 요구되는 특성을 가지고 있기 때문에 시설투자에 있어 정확한 예측과 분석을 통해 이루어져야 한다. 본 연구에서는 이러한 예측과 분석의 의사결정을 지원할 수 있는 상수도 배수 블록 노후도 관리 시스템과 최단/최적 연결 경로 산출 시스템을 구현해 봄으로써 다음과 같은 결론을 얻었다. 1. 상수도의 관망 노후도의 분석을 화면상에서 다양한 요소별로 하게 함으로써 넓은 공간에서의 관망의 관리를 효과적으로 할 수 있게 해준다. 2. 또한 이와 함께 대안 관망들을 사용자가 직접 대화식으로 빠르게 설계하고 이들의 경로와 공사비용 등을 산출해 봄으로써, 후보 최적 경로들을 공간적, 정량적으로 비교하는 것이 용이하다.

• Proceedings of the Korean Society of Propulsion Engineers Conference
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• v.y2005m4
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• pp.215-218
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• 2005

An optimal fuel manifold is suggested to improve the cooling performance of injector face plate. The cooling performance at the center area of the injector face plate is to be augmented while the spatial injection uniformity is maintained. The comparison of the cooling performance of 7 candidates gives the conclusion that the dividing plate from 2-3 injector row to 9-10 injector row is an optimal. The maximum face plate temperature decreases by $27\%$ while the injection uniformity is close to that of the original design. The pressure drop in the fuel manifold of the optimal design is also same as the original design.

• Journal of Korea Game Society
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• v.9 no.4
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• pp.81-88
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• 2009

In this paper, I suggested a way for searching a path of the intelligent character in an action game by using a genetic algorithm. This realized the algorithm which enables not only to chose the nearest path but also to search the optimum path by using genetic algorithm. In this case, if the codes of chromosomes are applied as they are, a lot of lethal genes could occur. In order to solve such a problem, I used a splicing method, one of the DNA's behavior characteristics. The intelligent character searched out a optimum pass as well as a shortcut path with one treatment by using the characteristic of a genetic algorithm which generates multiple candidate solutions in the search process.

• Proceedings of the Korean Information Science Society Conference
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• 2003.04c
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• pp.455-457
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• 2003

DNA microarray는 분자생물학에서 널리 사용되고 있는 실험 도구로써 크게 cDNA와 oligonucleotide microarray로 나뉘어진다. DNA microarray는 일련의 DNA 서열로 이루어진 probe들의 집합으로 구성되며 알려지지 않은 서열과의 hybridization 과정을 통해 특정 서열을 인식할 수 있게 된다. O1igonucieotide microarray는 cDNA 방법과는 다르게 probe를 구성하는 서열을 제작자가 임의로 구성할 수 있기 때문에 목표 서열이 가지는 고유한 부분만을 probe 서열로 사용함으로써 비용절감과 실험의 정확도를 높일 수 있다는 장점이 있다. 그러나 현재 목표 유전자 서열에 대해 probe 집합을 생성하는 결정적인 방법은 존재하지 않으며, 따라서 넓은 해 공간에서 효과적으로 최적 해를 찾아 주는 진화 연산이 probe 선택을 위한 좋은 대안으로 사용될 수 있다［1.2］. 그러나 진화연산을 이용한 probe 선택방법에 있어서 인식하고자 하는 목표 서열의 개수가 많아질 경우, 해 공간의 크기가 커짐으로 인해 문제점이 발생할 수 있다. 따라서 본 논문에서는 다수의 목표 유전자 서열을 대상으로 한 probe 선택 방법에 일어서 보다 효율적인 진화연산 접근 방법을 소개한다. 제시된 방법은 인식하고자 하는 목표 서얼의 일부를 선택해 이를 probe 집합의 후보로 사용하며. 유전 연산자를 이용한 진화과정을 통해 최적에 가까운 probe 집합을 찾는다. 본 논문은 GenBank로부터 유전자 서열을 대상으로 제안된 방법을 실험하였으며, 축소된 목표 서열만을 이용해 probe 집합을 선택하더라도 적합한 probe 집합을 찾을 수 있었다.