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Detection of Cause-Effect Relations Based on Information Granulation and Transfer Entropy
Causality inference is a process to infer Cause-Effect relations between variables in, typically, complex systems, and it is commonly used for root cause analysis in large-scale process industries. Transfer entropy (TE), as a non-parametric causality inference method, is an effective method to detec...
| Autores principales: | , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
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MDPI
2022
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8871421/ https://www.ncbi.nlm.nih.gov/pubmed/35205507 http://dx.doi.org/10.3390/e24020212 |