| 基于加权贝叶斯网络的海洋灾害风险评估 |
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| 引用本文： | 李明,张韧,洪梅.基于加权贝叶斯网络的海洋灾害风险评估[J].海洋通报,2018(2):121-128. |
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| 作者姓名： | 李明 张韧 洪梅 |
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| 作者单位： | 国防科技大学气象海洋学院 |
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| 基金项目： | 国家自然科学基金面上项目（41375002）；江苏省自然科学基金面上项目（BK20161461） |
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| 摘 要： | 全球气候变化背景下,海洋灾害的群发性、难以预见性和灾害链效应日显突出,造成的损失逐年上升,开展海洋灾害的风险评估工作至关重要。针对海洋灾害评估中的不确定问题,本文首先基于风险理论剖析了海洋灾害风险的不确定性特征,构建了灾害评估指标体系;然后基于贝叶斯网络模型,提出针对不确定性灾害评估的风险贝叶斯网络,进而基于主客观定权,构建了加权贝叶斯网络评估模型;最后对我国沿海地区海洋灾害开展评估研究。实验表明,该评估模型有效实现海洋灾害的风险评估,具有实际可操作性。
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| 关 键 词： | 海洋灾害 贝叶斯网络 不确定性 风险评估 |
| 收稿时间： | 2017/3/26 0:00:00 |
| 修稿时间： | 2017/7/7 0:00:00 |
Marine disaster risk assessment based on weighted Bayesian Network |
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| LI Ming,ZHANG Ren and HONG Mei.Marine disaster risk assessment based on weighted Bayesian Network[J].Marine Science Bulletin,2018(2):121-128. |
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| Authors: | LI Ming ZHANG Ren and HONG Mei |
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| Institution: | Institute of Meteorology and Oceanography, National University of Defense Technology, Nanjing 211101, China,Institute of Meteorology and Oceanography, National University of Defense Technology, Nanjing 211101, China and Institute of Meteorology and Oceanography, National University of Defense Technology, Nanjing 211101, China |
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| Abstract: | Under the global climate change, the massive, unpredictable and disaster-chain effects of marine disasters are becoming more and more prominent, and the losses have increased year by year. So it is important to carry out the risk assessment of marine disasters. Aiming at the uncertainties in marine disaster assessment, this paper firstly analyzed the uncertainties of marine disaster risk based on risk theory and constructed the disaster assessment index system. Then, a Bayesian network for uncertain disaster assessment was proposed based on the Bayesian Network model, and a weighted Bayesian network assessment model was constructed based on subjective and objective weights. Finally, the assessment of marine disaster risk in coastal areas of China was carried out. Experiments show that the evaluation model effectively achieves the risk assessment of marine disasters and has practical operability. |
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| Keywords: | marine disaster Bayesian Network uncertainty risk assessment |
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