• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.06a
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• pp.347-351
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• 1998

Dynamic programming is applicable to any situation where items from several groups must be combined to form an entity, such as a composite investment or a transportation route connecting several districts. The most desirable entity is constructed in stages by forming sub-entities that are candidates for inclusion in the most desirable entity are retained, and all other sub-entities are discarded. In the paper, the fuzzy dynamic programming is applied to the situation where each investment in the set has the following characteristics : the amount to be invested has several possible values, and the rte of return varies with the amount invested. Each sum that may be invested represents a distinct level of investment , and the investment therefore has multiple levels. A numeric example constructing a combination of multilevel investments is given in the paper.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.09b
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• pp.35-38
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• 2003

최근 컴퓨터 게임의 확산과 함께 보다 나은 가상환경 생성을 위한 기술에 대한 필요성이 증가하고 있다 다양한 환경에서 지능적으로 행동하는 인공 캐릭터의 설계를 위해 다양한 인공지능 기술이 적용되고 있다. 하지만 게임의 캐릭터 설계에 적용된 휴리스틱이나 규칙기반 시스템 등의 기존 인공지능 기술은 게임 개발자에 의존적이기 때문에 플레이어가 쉽게 캐릭터의 행동패턴을 파악하여 게임의 흥미를 저하시키는 단점이 있다 따라서 진화연산이나 신경망 등의 학습기반 인공지능 기술의 게임에의 적용이 모색되고 있다 특히 진화를 이용한 지능기술은 자연계의 복잡성과 의외성을 모방하여 최적화된 지능보다는 속임수/의외성 등의 창의적인 지능행동의 생성을 가능하게 하며 새로운 게임전략의 생성, 게임 캐릭터의 성격형성 및 다양한 행동 생성 등에 매우 유용하다. 본 논문에서는 진화기술의 게임에의 효과적인 적용을 위해 진화엔진을 설계 및 제작하고 인공지능 시뮬레이터에 적용하여 그 유용성을 확인하였다.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.09b
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• pp.41-44
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• 2003

인공생명 기법의 대표적인 응용분야 중 하나인 창발적인 개체의 생성에서 유전자를 표현하는 방법으로 크게 방향성 그래프와 L-system의 두 가지 방법이 사용되고 있다. 두 가지 방법 모두 각기 좋은 특성이 있지만 L-system은 사용자에 의해 내부적인 파라메터로 정의되기 때문에 전체적인 실제 모양을 구조적으로 정의하기 어렵다 본 논문에서는 이런 단점을 극복하고자 실제 모양을 표현하는데 적절한 구조적 방향성 그래프를 도입하여 개체의 유전자를 구조적으로 표현함으로써 실제 개체와 유사한 모양을 창발적으로 생성하고, 이를 클러스터 대화형 유전자 알고리즘에 적용하여 사용자가 생성하고자 하는 실제 모양의 캐릭터를 자동으로 생성하게 하였다. 실험을 통해 2차원에서의 의자모양과 꽃 모양을 생성함으로써 다양한 구조의 창발적인 캐릭터를 생성할 수 있는 가능성을 제시했다.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2005.11a
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• pp.440-443
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• 2005

In this paper, we introduce about a new class to analysis of partial discharge signal based on Fuzzy model. We can early diagnose life of power cable through detection of partial discharge signal. However, partial discharge signal detector is difficult because of partial discharge signal is very non-linear. Also, it is very difficult work that separate partial discharge signal from noise. We constructed partial discharge accumulation detection system that use Labview for detection of non-linear partial discharge signal. And analyzed partial discharge signal that is detected by Labview system utilizing Fuzzy model.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.7 no.4
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• pp.221-227
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• 2007

This paper introduces an on-line particle-filtering-based framework for failure prognosis in nonlinear, non-Gaussian systems. This framework uses a nonlinear state-space model of the plant(with unknown time-varying parameters) and a particle filtering(PF) algorithm to estimate the probability density function(pdf) of the state in real-time. The state pdf estimate is then used to predict the evolution in time of the fault indicator, obtaining as a result the pdf of the remaining useful life(RUL) for the faulty subsystem. This approach provides information about the precision and accuracy of long-term predictions, RUL expectations, and 95% confidence intervals for the condition under study. Data from a seeded fault test for a UH-60 planetary carrier plate are used to validate the proposed methodology.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2001.01a
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• pp.156-163
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• 2001

Business forecasting is vital to the success of business. There has been an increasing demand for building business forecasting software system to assist human being to do forecasting. However, the uncertain and complex nature makes is a challenging work to analyze, design and implement software solutions for business forecasting. Traditional forecasting systems in which their models are trained based on small collection of historical data could not meet such challenges at the information explosion over the Internet. This paper presents an agent oriented business forecasting approach for building intelligent business forecasting software systems with high reusability. Although agents have been applied successfully to many application domains. little work has been reported to use the emerging agent oriented technology of this paper is that it explores how agent can be used to help human to manage various business forecasting processes in the whole business forecasting life cycle.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2001.12a
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• pp.69-73
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• 2001

The dynamic characteristics of turning processes are complex, non-linear and time-varying. Consequently, the conventional techniques based on crisp mathematical model may not guarantee surface roughness regulation. This paper presents a fuzzy controller which can regulate surface roughness in milling process using end-mill under varying cutting condition. The fuzzy control rules are established from operator experience and expert knowledge about the process dynamics. regulation which increases productivity and tool life is achieved by adjusting feed-rate according to the variation of cutting conditions. The performance of the proposed controller is evaluated by cutting experiments in the converted CNC milling machine. The result of experiments show that the proposed fuzzy controller has a good surface roughness regulation capability in spite of the variation of cutting conditions.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1997.10a
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• pp.331-337
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• 1997

In this paper we will discuss a type of inductive learning called learning from examples, whose task is to induce general descriptions of concepts from specific instances of these concepts. In many real life situations however new instances can be added to the set of instances. It is first proposed within the framework of rough set theory, for such cases, an algorithm to find minimal set of rules for decision tables without recalculation for overall set of instances. The method of learning presented here is based on a rough set concept proposed by Pawlak[2]. It is shown an algorithm to fund minimal set of rules using reduct change theorems giving criteria for minimum recalculation and an illustrative example.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1997.10a
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• pp.391-394
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• 1997

인터넷의 웹은 여러 곳에 분산되어 있을 뿐만 아니라 끊임없이 동적으로 변화하는 특성이 있기 때문에, 보통의 인덱스를 통한 정보검색 방법에는 한계가 있다. 이러한 웹의 특성을 적절히 살리면서 원하는 정보를 신속하게 검색하기 위하여, 본 논문에서는 여러 개의 에이전트가 인공생명 기법에 의해 조직되어 정보를 검색하는 온라인 에이전트를 소개한다. 이것은 각각의 에이전트에 의하여 검색된 문서가 얼마나 질의에 가까운가에 따라서 해당 에이전트를 만이 살아 남아 문서를 가져오도록 함으로써, 불필요한 문서를 검색하지 않게 되어 단위 시간에 원하는 문서를 많이 얻어올 수 있는 장점이 있다. 실제 웹 환경에서 실험한 결과 종래의 폭우선 검색이나 랜덤검색에 비하여 좋은 결과를 내는 것을 볼 수 있었다.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.05a
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• pp.129-133
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• 2003

The work described in this paper deals with the proposed application of an Artificial Neural Network Model for the Advanced Pressurized Water Reactor APR-1400 transient identification. The approach adopted for testing the network take note of the expectation which should be fulfilled by a network for real-time application, like testing with data in on-line mode and use of actual or real-life patterns for training. The recall test performed demonstrates that use of neural network for transient identification is indeed an attractive preposition.