• Journal of Ship and Ocean Technology
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• 제5권3호
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• pp.27-35
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• 2001

In this research, hybrid method with case-based reasoning and rule-based reasoning is applied. Using case-based reasoning, design experts'experience and know-how are effectively represented in order to obtain a proper configuration of midship section in the initial ship design stage. Since there is not sufficient domain knowledge available to us, traditional case-adaptation algorithms cannot be applied to our problem, i.e., creating the configuration of midship section. Thus, new case-adaptation algorithms not requiring any domain knowledge are developed antral applied to our problem. Using the knowledge representation of DnV rules, rule-based reasoning can perform deductive inference in order to obtain the scantling of midship section efficiently. The results from the case-based reasoning and the rule-based reasoning are examined by comparing the results with various conventional methods. And the reasonability of our results is verified by comparing the results wish actual values from parent ship.

• Journal of the Korean Institute of Landscape Architecture International Edition
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• 제1호
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• pp.26-27
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• 2001

The materials that are involved in urban landscaping include plants and the associated animals, soil, water, and other environmental elements. And biodiversity is the substantial base for human beings. The conservation of biodiversity is of great importance in the sustainable development of the society and should not be neglected in the development of sustainable urban landscape. The conservation of biodiversity should be included in the urban landscape planning. The conservation of biodiversity should be emphasized in the construction of urban green space. Every possible opportunity should be used to conserve the species diversity, genetic diversity and ecological diversity. The assessment of biodiversity conservation should be introduced into modern landscape planning.

• 소프트웨어공학소사이어티 논문지
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• 제25권3호
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• pp.59-62
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• 2012

본 연구에서는 소프트웨어 아키텍처 복원을 위한 계층적 클러스터링(Clustering) 결과를 정량적으로 평가 할 수 있는 비교 메트릭(Metric)을 제시한다. 소프트웨어 클러스터링의 정량적 평가는 소프트웨어의 구조적 변화에 대한 이해를 돕는 척도를 제시하는 연구이다. 이를 위해 생물정보학에서 상호유전 형질 분석에 사용하는 분기점(Split) 개념을 소프트웨어 아키텍처 분석에 적용한다.

• 한국산학기술학회:학술대회논문집
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• 한국산학기술학회 2007년도 춘계학술발표논문집
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• pp.147-149
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• 2007

"Dynamic Neural Unit"(DNU) based upon the topology of a reverberating circuit in a neuronal pool of the central nervous system. In this thesis, we present a genetic DNU-control scheme for unknown nonlinear systems. Our methodis different from those using supervised learning algorithms, such as the backpropagation (BP) algorithm, that needs training information in each step. The contributions of this thesis are the new approach to constructing neural network architecture and its trainin.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2002년도 ICCAS
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• pp.102.1-102
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• 2002

In this paper, we propose Self-organizing neurofuzzy networks(SONFN) and discuss their comprehensive design methodology. The proposed SONFN is generated from the mutually combined structure of both neurofuzzy networks (NFN) and polynomial neural networks(PNN) for model identification of complex and nonlinear systems. NFN contributes to the formation of the premise part of the SONFN. The consequence part of the SONFN is designed using PNN. The parameters of the membership functions, learning rates and momentum coefficients are adjusted with the use of genetic optimization. We discuss two kinds of SONFN architectures and propose a comprehensive learning algorithm. It is shown that this network...

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1999년도 제14차 학술회의논문집
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• pp.214-217
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• 1999

In this paper, genetic algorithm (GA) is implemented to search for the optimal structures (i.e. the kind of neural networks, the number of inputs and hidden neurons) of neural networks which are used approximating a given nonlinear function. Two kinds of neural networks, i.e. the multilayer feedforward [1] and time delay neural networks (TDNN) [2] are involved in this paper. The synapse weights of each neural network in each generation are obtained by associated training algorithms. The simulation results of nonlinear function approximation are given out and some improvements in the future are outlined.

• 한국산학기술학회:학술대회논문집
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• 한국산학기술학회 2011년도 춘계학술논문집 1부
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• pp.379-381
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• 2011

Dynamic Neural Unit(DNU) based upon the topology of a reverberating circuit in a neuronal pool of the central nervous system. In this thesis, we present a genetic DNU-control scheme for unknown nonlinear systems. Our methodis different from those using supervised learning algorithms, such as the backpropagation (BP) algorithm, that needs training information in each step. The contributions of this thesis are the new approach to constructing neural network architecture and its trainin.

• KIEE International Transactions on Power Engineering
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• 제2A권4호
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• pp.145-152
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• 2002

This paper illustrates applications of the Component Object Model (COM) for power system software developments. As an integral part of Microsoft's component services, COM has gained increased popularity for developing enterprise applications. This paper illustrates the concepts of COM and the latest developments as well as the available tools for developing COM components. Possible COM applications for developing power system software, such as sparse matrix manipulation, fault location, genetic algorithm applications, and so on. are presented. Advantages and promises brought about by COM are manifested through these examples.

• 한국산학기술학회:학술대회논문집
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• 한국산학기술학회 2006년도 추계학술발표논문집
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• pp.186-190
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• 2006

"Dynamic Neural Unit"(DNU) based upon the topology of a reverberating circuit in a neuronal pool of the central nervous system. In this thesis, we present a genetic DNU-control scheme for unknown nonlinear systems. Our methodis different from those using supervised learning algorithms, such as the backpropagation (BP) algorithm, that needs training information in each step. The contributions of this thesis are the new approach to constructing neural network architecture and its trainin.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2007년도 제38회 하계학술대회
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• pp.1574-1575
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• 2007

"Dynamic Neural Unit"(DNU) based upon the topology of a reverberating circuit in a neuronal pool of the central nervous system. In this thesis, we present a genetic DNU-control scheme for unknown nonlinear systems. Our methodis different from those using supervised learning algorithms, such as the backpropagation (BP) algorithm, that needs training information in each step. The contributions of this thesis are the new approach to constructing neural network architecture and its trainin.