| 船舶区域溢油风险程度甄别的人工神经网络方法 |
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| 引用本文： | 肖井坤,殷佩海,林建国,任福安.船舶区域溢油风险程度甄别的人工神经网络方法[J].海洋环境科学,2002,21(4):42-45. |
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| 作者姓名： | 肖井坤 殷佩海 林建国 任福安 |
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| 作者单位： | 1. 大连海事大学环境科学与工程学院,辽宁,大连,116026
2. 大连海事大学轮机工程学院,辽宁,大连,116026 |
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| 基金项目： | 交通部重点项目资助(95040601) |
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| 摘 要： | 利用误差反向传播 (BP)人工神经网络 ,建立了海域船舶溢油风险程度甄别的评价模型。该模型能够反映出研究海域各区域发生船舶溢油事件的风险等级差别 ,具有一定的客观性和实用性。
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| 关 键 词： | BP算法 人工神经网络 溢油 风险程度 |
| 文章编号： | 1007-6336(2002)04-0042-04 |
| 修稿时间： | 2001年1月3日 |
Identification of ship's oil spill risk degree of sea area by using B-P artificial network |
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| XIAO Jing kun ,YIN Pei hai ,LIN Jian guo ,REN Fu an.Identification of ship''''s oil spill risk degree of sea area by using B-P artificial network[J].Marine Environmental Science,2002,21(4):42-45. |
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| Authors: | XIAO Jing kun YIN Pei hai LIN Jian guo REN Fu an |
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| Institution: | XIAO Jing kun 1,YIN Pei hai 2,LIN Jian guo 1,REN Fu an 2 |
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| Abstract: | An artificial neural network is made to identify the oil spill risk degree of the different sub-areas of a sea area being interested. The resilient back propagation algorithm is adopted to the training of the network and the calculation example shows the method has preferable objectivity and practicability. |
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| Keywords: | BP algorithms artificial neural network oil spill risk |
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