Complex system risk evolution analysis based on multi-resolution modeling and Bayesian networks
| Autor: | Jing Yang, Jianwei Lv, Zongren Xie, Yifan Xu |
|---|---|
| Rok vydání: | 2017 |
| Předmět: |
0209 industrial biotechnology
Relation (database) business.industry Computer science Complex system Bayesian network 02 engineering and technology Resolution (logic) Machine learning computer.software_genre 020901 industrial engineering & automation Multi resolution 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing Artificial intelligence business computer |
| Zdroj: | 2017 Second International Conference on Reliability Systems Engineering (ICRSE). |
| DOI: | 10.1109/icrse.2017.8030804 |
| Popis: | Complex system development contains processes full of comprehensive integration, complicated iteration and highly coupling, and ultimately come into being hierarchical networks of risk evolution. This paper presents a new approach on risk evolution analysis by multi-resolution modeling describing complex system and Bayesian network learning risk relation networks. By simulation experiments, risk evolution networks and their comparative analysis on different resolution models are presented. The proposed approach is verified to provide the more credible assessment and avoid risk evolution networks just only determined by subjective judgment. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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