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  • 标题:A Technique to Generate Essential Qualitative Explanations of Derived Causal Relations Based on a Functional Model
  • 本地全文:下载
  • 作者:Yaoyang Zheng ; Akio Gofuku
  • 期刊名称:人工知能学会論文誌
  • 印刷版ISSN:1346-0714
  • 电子版ISSN:1346-8030
  • 出版年度:2005
  • 卷号:20
  • 期号:6
  • 页码:356-369
  • DOI:10.1527/tjsai.20.356
  • 出版社:The Japanese Society for Artificial Intelligence
  • 摘要:This study investigates a technique to generate essential explanation for the reasoning process derived by the qualitative reasoning based on a functional model, in order to realize a mutual cooperation between a team of operators and an operator support system in an anomalous plant situation. This study applies a technique called function flow simplification to simplify a microscopic functional model into a macroscopic one. Then, this paper proposes a technique composed of the function flow simplification, simplification of functional model considering the purpose of a component and mapping the simplified functional model by the function flow simplification to a corresponding structure model to generate essential qualitative explanations. The applicability of the proposed technique is demonstrated by the explanation generation for effect propagations of counter actions for an anomaly in an oil refinery plant.
  • 关键词:function flow simplification ; essential explanation ; causal relation ; multi-level flow modelling
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