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The Integration of Machine and Human Knowledge by Fuzzy Logic for the Prediction of Stock Price Index

机译:机器和人类知识的模糊逻辑集成预测股票价格指数

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摘要

Integration of machine and human knowledge is more effective rather than a single kind of knowledge in solving unstructured problems. This paper proposes the knowledge integration of machine and human knowledge to achieve a better reasoning performance in the stock price index prediction problem. Causal model and the evaluation by experts generate the machine and human knowledge about the stock price index of next month, respectively. 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 integration significantly improves the reasoning performance.
机译:在解决非结构化问题中,机器知识和人类知识的集成比单种知识更有效。本文提出了机器知识与人类知识的融合,以在股票价格指数预测问题中实现更好的推理性能。因果模型和专家评估分别产生了有关下个月股价指数的机器和人类知识。机器知识和人类知识通过模糊逻辑驱动的框架集成在一起,生成集成的知识。通过模糊规则库解决了集成知识之间的矛盾。实验结果表明,所提出的知识整合显着提高了推理性能。

著录项

  • 来源
  • 会议地点 Singapore(SG);Singapore(SG)
  • 作者单位

    Graduate School of Management, Korea Advanced Institute of Science Technology, P.O.Box 201, Cheongryang, Seoul, 130-650, Korea;

    Graduate School of Management, Korea Advanced Institute of Science Technology, P.O.Box 201, Cheongryang, Seoul, 130-650, Korea;

    School of Business Administration, Sung Kyun Kwan University, Seoul 110-745, Korea;

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  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 自动化系统理论;
  • 关键词

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