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参与贝叶斯网络用于发现战略环境风险管理中的反射未知数
Annukka Lehikoinen1, Tapio Reinekoski2, Nina Janasik3
1Kotka Maritime Research Centre, Salakuljettajantie 4, 48100, Kotka, Finland; University of Helsinki, Viikinkaari 1 (PB 65), 00014, Helsinki, Finland.
Journal of environmental management
|May 4, 2025
概括
本研究引入了使用贝叶斯网络 (BN) 的参与式建模方法,通过共同生产知识和识别未知的风险来增强战略环境规划,以提高弹性.
科学领域:
- 环境科学 环境科学
- 风险管理 风险管理
- 人工智能的人工智能
背景情况:
- 战略环境规划需要处理不确定性和复杂性的方法.
- 现有的方法可能无法充分捕捉新出现的风险或有效地整合各种利益相关者的知识.
研究的目的:
- 引入一种参与式建模 (PM) 方法,使用贝叶斯网络 (BN) 共同生产知识和战略规划.
- 在不完整的知识下加强系统情景开发,分析和弹性建设.
主要方法:
- 开发了一个结构化的BN模型,以整合不同参与者的观点和专业知识.
- 翻译参与者对因果路径分析的概率依赖关系的见解.
- 将方法应用于城市环境中化学运输事故的案例研究.
主要成果:
- 参与式的BN方法促进了因果路径的共同想象和构建.
- 该方法成功地确定了以前未知的威胁,称为"反射未知",例如有毒降雨.
- 该过程促进了集体反思,并为社会环境弹性产生了新的见解.
结论:
- 使用贝叶斯网络进行参与式建模为战略环境风险管理提供了强大的框架.
- 这种方法有效地揭示了"反射未知"并通过整合多样化的知识和促进协作前,增强了弹性建设.
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