Proceedings of the Korea Inteligent Information System Society Conference (한국지능정보시스템학회:학술대회논문집)
- 1999.03a
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- Pages.145-154
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- 1999
The Hybrid Knowledge Integration Using the Fuzzy Genetic Algorithm
- Kim, Myoung-Jong (Graduate School of Management, Korea Advanced Institute of Science & Technology) ;
- Ingoo Han (Graduate School of Management, Korea Advanced Institute of Science & Technology) ;
- Lee, Kun-Chang (School of Business Administration, Sungkyunkwan University, Seoul)
- Published : 1999.03.01
Abstract
An intelligent system embedded with multiple sources of knowledge may provide more robust intelligence with highly ill structured problems than the system with a single source of knowledge. This paper proposes th hybrid knowledge integration mechanism that yields the cooperated knowledge by integrating expert, user, and machine knowledge within the fuzzy logic-driven framework, and then refines it with a genetic algorithm (GA) to enhance the reasoning performance. The proposed knowledge integration mechanism is applied for the prediction of Korea stock price index (KOSPI). Empirical results show that the proposed mechanism can make an intelligent system with the more adaptable and robust intelligence.
Keywords
- Hybrid knowledge integration;
- Fuzzy genetic algorithm;
- Human knowledge;
- Machine knowledge;
- The cooperated knowledge