The Integrated framework for the Prediction of Stock Price Index

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Integration of machine and human knowledge is more effective rather than a single kind of knowledge in solving unstructured problems. This paper proposes the integrated framework to achieve a better reasoning performance and comprehensive understanding on the stock price index prediction problem. Fuzzy neural network and the evaluation by expert respectively serve as the useful tools for generating the machine and human knowledge about the stock price index of next week. The machine and human knowledge are integrated by fuzzy logic-driven framework to generate the integrated knowledge. The conflicts among the integrated knowledge are solved by fuzzy rule base. The experimental results show that the proposed knowledge are solved by rule base. The experimental results show that the proposed knowledge integration significantly improves the reasoning performance.
Description
금융전문대학원
Publisher
The Korea Society of Management Information Systems
Issue Date
1998
Language
English
Citation

한국경영정보학회 국제추계학술대회, pp.485-494

URI
http://hdl.handle.net/10203/22151
Appears in Collection
NE-Conference Papers(학술회의논문)

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