Scientific Discovery of Dynamic Models Based on Scale-type Constraints

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概要

• 論文の詳細を見る

• This paper proposes a novel approach to discover dynamic laws and models represented by simultaneous time differential equations including hidden states from time series data measured in an objective process. This task has not been addressed in the past work though it is essentially important in scientific discovery since any behaviors of objective processes emerge in time evolution. The promising performance of the proposed approach is demonstrated through the analysis of synthetic data.

• 一般社団法人 情報処理学会の論文

著者

• Motoda Hiroshi

  The Institute Of Scientific And Industrial Research Osaka University

• Washio Takashi

  The Institute Of Scientific And Industrial Research Osaka University

• Adachi Fuminori

  The Institute Of Scientific And Industrial Research Osaka University

• Adachi Fuminori

  The Institute of Scientific and Industrial Research, Osaka University

関連論文

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• Scientific Discovery of Dynamic Models Based on Scale-type Constraints
• Scientific Discovery of Dynamic Models Based on Scale-type Constraints
• Scientific Discovery of Dynamic Hidden States and Differential Law Equations (Joint Workshop of Vietnamese Society of AI, SIGKBS-JSAI, ICS-IPSJ and IEICE-SIGAI on Active Mining) -- (Session 9: Scientific Data Mining)
• Scientific Discovery of Dynamic Hidden States and Differential Law Equations(Scientific Data Mining)
• Scientific Discovery of Dynamic Hidden States and Differential Law Equations(Scientific Data Mining)(Joint Workshop of Vietnamese Society of AI, SIGKBS-JSAI, ICS-IPSJ, and IEICE-SIGAI on Active Mining)
• Scientific Discovery of Dynamic Models Based on Scale-type Constraints

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