期刊
CHAOS
卷 29, 期 9, 页码 -出版社
AIP Publishing
DOI: 10.1063/1.5120778
关键词
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资金
- JSPS KAKENHI [JP15H05707]
- National Science Foundation of China (NSFC) [11771010]
- Tang Scholarship in Soochow University
Inspired by the decision tree algorithm in machine learning, a novel causal network reconstruction framework is proposed with the name Importance Causal Analysis (ICA). The ICA framework is designed in a network level and fills the gap between traditional mutual causality detection methods and the reconstruction of causal networks. The potential of the method to identify the true causal relations in complex networks is validated by both benchmark systems and real-world data sets.
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