• 한국정보과학회논문지:정보통신
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• 제32권3호
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• pp.301-309
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• 2005

시스템 호출 감사자료기반 기계학습기법을 사용한 프로그램 행위 학습방법은 효과적인 호스트 기반 침입탐지 방법이며, 규칙 학습, 신경망, 통계적 방법, 은닉 마크로프 모델 등의 방법이 대표적이다. 그 중에서 신경망은 시스템 호출 시퀀스를 학습하는데 있어 적합하다고 알려져 있는데, 실제 문제에 적용하여 좋은 성능을 내기 위해서는 그 구조를 결정하는 것이 중요하다 하지만 보통의 신경망은 그 구조를 찾기 위한 방법이 알려져 있지 않아 침입탐지에 효과적인 구조를 찾기 위해서는 많은 시간이 요구된다. 본 논문에서는 기존 신경망 기반 침입탐지시스템의 단점을 보완하고 성능을 향상시키기 위해 진화신경망을 이용한 방법을 제안한다. 진화 신경망은 신경망의 구조와 가중치를 동시에 학습하기 때문에 일반 신경망보다 빠른 시간에 더 좋은 성능의 신경망을 얻을 수 있다는 장점이 있다. 1999년의 DARPA IDEVAL 자료로 실험한 결과 기존의 연구보다 좋은 탐지율을 보여 진화신경망이 침입탐지에 효과적임을 확인할 수 있었다.

• 대한전기학회논문지:전력기술부문A
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• 제50권7호
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• pp.318-323
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• 2001

This paper proposes an efficient method of On-Line Economic Load Dispatch(ELD) using Evolutionary Programming(EP) technique at KwangYang steel works. The economic operation of steel works is done by experienced engineer. So far, there is no formulation and algorithm of economic operation of steel works. In this paper, we propose the formulation and On-Line algorithm of economic operation of steel works. The EP technique is the kind of Evolutionary Computation(EC), which has become a candidate for many optimization applications due to its flexibility and efficiency. Based on the EP technique, the proposed algorithm is capable of not only solving the economic problem, but also obtaining the global optimal solutions within reasonable execution time. To validate our proposed approach, the algorithm is demonstrated on many sample systems and compared to actual values of steel works.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2000년도 추계학술대회 논문집 학회본부 A
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• pp.116-118
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• 2000

This paper proposes an efficient method of On-Line Economic Load Dispatch(ELD) using Evolutionary Programming(EP) technique at Kwangyang steel works. The economic operation of steel works is done by experienced engineer. So far, there is no formulation and algorithm of economic operation of steel works. In this paper, we propose the formulation and On-Line algorithm of economic operation of steel works. The EP technique is the kind of Evolutionary Computation(EC) which has become a candidate for many optimization applications due to its flexibility and efficiency. Based on the EP technique, the proposed algorithm is capable of not only solving the economic problem, but also obtaining the global optimal solutions within reasonable execution time. To validate our proposed approach, the algorithm is demonstrated on many sample systems and compared to actual values of steel works.

• 산업공학
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• 제17권2호
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• pp.208-217
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• 2004

This paper deals with a process planning problem in the flexible assembly system (FAS). The problem is to assign assembly tasks to stations with limited working space and to determine assembly routing with the objective of minimizing transfer time of the products among stations, while satisfying precedence relations among the tasks and upper-bound workload constraints for each station. In the process planning of FAS, the optimality of assembly routing depends on tasks loading. The integration of tasks loading and assembly routing is therefore important for an efficient utilization of FAS. To solve the integrated problem at the same time, in this paper we propose a new method using an artificial intelligent search technique, named 2-leveled symbiotic evolutionary algorithm. Through computational experiments, the performance of the proposed algorithm is compared with those of a traditional evolutionary algorithm and a symbiotic evolutionary algorithm. The experimental results show that the proposed algorithm outperforms the algorithms compared.

• 대한기계학회논문집A
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• 제26권9호
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• pp.1806-1813
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• 2002

It is well known that a crack has an important effect on the dynamic behavior of a structure. This effect depends mainly on the location and depth of the crack. To identify the location and depth of a crack in a structure, a classical optimization technique was adopted by previous researchers. That technique overcame the difficulty of finding the intersection point of the superposed contours that correspond to the eigenfrequency caused by the crack presence. However, it is hard to select a trial solution initially for optimization because the defined objective function is heavily multimodal. A method is presented in this paper, which uses continuous evolutionary algorithms(CEAs). CEAs are effective for solving inverse problems and implemented on PC clusters to shorten calculation time. With finite element model of the structure to calculate eigenfrequencies, it is possible to formulate the inverse problem in optimization format. CEAs are used to identify the crack location and depth minimizing the difference from the measured frequencies. We have tried this new idea on a simple beam structure and the results are promising with high parallel efficiency over about 94%.

• 한국전산구조공학회:학술대회논문집
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• 한국전산구조공학회 2005년도 춘계 학술발표회 논문집
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• pp.317-324
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• 2005

Korean shipyards have accumulated a great amount of data. But they do not have appropriate tools to utilize the data in practical works. Engineering data contains experts' experience and know-how In its own. It is very useful to extract knowledge or information from the accumulated existing data by using datamining technique. This paper treats an evolutionary computation method based on genetic programming (GP), which can be one of the components to realize datamining.

• 한국전산구조공학회:학술대회논문집
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• 한국전산구조공학회 1996년도 가을 학술발표회 논문집
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• pp.113-120
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• 1996

This study presents the optimization technique to determine the cable areas of the cable-stayed bridge. The optimization method presented in this paper is based on an evolutionary procedure, in which the area of high stressed cable is increased step-by-step until an optimal area of the cable is obtained. A comparison between the maximum values of the present method and those of the cable-stayed bridge that has the same cable area shows the advantages of the present method.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제9권3호
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• pp.172-177
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• 2009

In this paper, a new morphology-based homomorphic filtering technique is presented to enhance features in medical images. The homomorphic filtering is performed based on the morphological sub-bands, in which an image is morphologically decomposed. An evolutionary design is carried to find an optimal gain and structuring element of each sub-band. As a search algorithm, Differential Evolution scheme is utilized. Simulations show that the proposed filter improves the contrast of the interest feature in medical images.

• 제어로봇시스템학회논문지
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• 제7권4호
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• pp.295-303
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• 2001

The demand for steam generators is increasing in industrial systems in which the design strategy should be implemented for safe and efficient operation of steam generators. It is, however, difficult to design a controller by the conventional method because of the nonlinear dynamics of the steam generator and influences by the set value of disturbance. This paper presents an automatic parameter optimization technique for a multivariable fuzzy controller using evolutionary strategy, At first, we use the steady state information such as a steady state gain matrix(SSGM) and a relative gain matrix(RGM). We can obtain much information on the control inputs and the outputs of the boiler-turbine system from the matrices. In order to determine the structure of the controller by using RGM and SSGM, the fuzzy rules are trained by evolutionary strategy. The good performance of the proposed multivariable fuzzy controller is verified through simulations.

• 대한전기학회논문지:전력기술부문A
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• 제48권8호
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• pp.917-923
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• 1999

This paper proposes an efficient method of hydro-thermal scheduling in coordination with head variation and hydraulically coupled plants using Evolutionary Programing(EP). Based on the EP technique, the proposed algorithm is capable of determining the global optimal solutions. The constraints such a power balance condition, water available condition and transmission losses are embedded and satisfied throughout the proposed EP approach. The effectiveness of the proposed approach is demonstrated on the test systems and compared to those of other method. The results show that the new approach obtains a more highly optimal solutions than the conventional other methods such as newton-raphson method, Dynamic Programming(DP), LU factorization.