Assessment of tropical cyclone disaster loss in Guangdong Province based on combined model
文献类型：期刊论文
| 作者 | Chen, SH; Tang, DL; Liu, XQ; Hu, CH |
| 刊名 | GEOMATICS NATURAL HAZARDS & RISK
 |
| 出版日期 | 2018 |
| 卷号 | 9期号:1页码:431-441 |
| 关键词 | TC disaster loss assessment GA-Elman SVR GRNN combined model Guangdong province |
| 通讯作者 | 200911837@oamail.gdufs.edu.cn |
| 英文摘要 | Tropical cyclone (TC) disaster loss assessment is an important and difficult problem in TC prevention and disaster mitigation. Few studies have focused on combined model in this area. This study introduced a new combination model method to predict TC disaster loss, taking Guangdong province as an example. We analysed and collected 67 TC data from 1993 to 2009, which had impact on Guangdong province, in which 60 were randomly for training data and another 7 were for testing data. We conducted three models - GA-Elman neural networks, support vector regression (SVR) and generalized regression neural networks (GRNN), and the root mean square error (RMSE) value we got are 5.05, 7.85 and 3.82, respectively. Then the three models are combined into a comprehensive evaluation model by model combination method. The RMSE of the test results is 3.30. The results show that the combined model is superior to one individual model and it is a more accurate and stable method. |
| 学科主题 | Geology; Meteorology & Atmospheric Sciences; Water Resources |
| 源URL | [http://ir.scsio.ac.cn/handle/344004/17105]  |
| 专题 | 南海海洋研究所_热带海洋环境国家重点实验室(LTO) |
| 推荐引用方式 GB/T 7714 | Chen, SH,Tang, DL,Liu, XQ,et al. Assessment of tropical cyclone disaster loss in Guangdong Province based on combined model[J]. GEOMATICS NATURAL HAZARDS & RISK,2018,9(1):431-441. |
| APA | Chen, SH,Tang, DL,Liu, XQ,&Hu, CH.(2018).Assessment of tropical cyclone disaster loss in Guangdong Province based on combined model.GEOMATICS NATURAL HAZARDS & RISK,9(1),431-441. |
| MLA | Chen, SH,et al."Assessment of tropical cyclone disaster loss in Guangdong Province based on combined model".GEOMATICS NATURAL HAZARDS & RISK 9.1(2018):431-441. |
入库方式： OAI收割
来源：南海海洋研究所
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