Waterlogging risk assessment based on self-organizing map (SOM) artificial neural networks: a case study of an urban stormin Beijing
文献类型：期刊论文
| 作者 | LAI Wen-li; WANG Hong-rui; WANG Cheng; ZHANG Jie; ZHAO Yong |
| 刊名 | Journal of Mountain Science
 |
| 出版日期 | 2017-05 |
| 卷号 | 14期号:5页码:898-905 |
| 关键词 | Waterlogging Risk Assessment Self-organizing Map (Som) Neural Network Urban Storm |
| ISSN号 | 1672-6316 |
| DOI | 10.1007/s11629-016-4035-y |
| 通讯作者 | WANG Hong-rui |
| 文献子类 | 期刊论文 |
| 英文摘要 | Due to rapid urbanization, waterlogging induced by torrential rainfall has become a global concern and a potential risk affecting urban habitant's safety. Widespread waterlogging disasters have occurred almost annually in the urban area of Beijing, the capital of China. Based on a self-organizing map (SOM) artificial neural network (ANN), a graded waterlogging risk assessment was conducted on 56 low-lying points in Beijing, China. Social risk factors, such as Gross domestic product (GDP), population density, and traffic congestion, were utilized as input datasets in this study. The results indicate that SOM-ANN is suitable for automatically and quantitatively assessing risks associated with waterlogging. The greatest advantage of SOM-ANN in the assessment of waterlogging risk is that a priori knowledge about classification categories and assessment indicator weights is not needed. As a result, SOM-ANN can effectively overcome interference from subjective factors, producing classification results that are more objective and accurate. In this paper, the risk level of waterlogging in Beijing was divided into five grades. The points that were assigned risk grades of IV or V were located mainly in the districts of Chaoyang, Haidian, Xicheng, and Dongcheng. |
| 语种 | 英语 |
| 源URL | [http://ir.imde.ac.cn/handle/131551/18715]  |
| 专题 | Journal of Mountain Science _Journal of Mountain Science-2017_Vol14 No.5 |
| 推荐引用方式 GB/T 7714 | LAI Wen-li,WANG Hong-rui,WANG Cheng,et al. Waterlogging risk assessment based on self-organizing map (SOM) artificial neural networks: a case study of an urban stormin Beijing[J]. Journal of Mountain Science,2017,14(5):898-905. |
| APA | LAI Wen-li,WANG Hong-rui,WANG Cheng,ZHANG Jie,&ZHAO Yong.(2017).Waterlogging risk assessment based on self-organizing map (SOM) artificial neural networks: a case study of an urban stormin Beijing.Journal of Mountain Science,14(5),898-905. |
| MLA | LAI Wen-li,et al."Waterlogging risk assessment based on self-organizing map (SOM) artificial neural networks: a case study of an urban stormin Beijing".Journal of Mountain Science 14.5(2017):898-905. |
入库方式： OAI收割
来源：成都山地灾害与环境研究所
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