[1]冯快乐,周建中,江焱生,等.基于BP神经网络的湖北省山洪灾害危险性评价[J].自然灾害学报,2018,(01):148-154.[doi:10.13577/j.jnd.2018.0118]
 FENG Kuaile,ZHOU Jianzhong,JIANG Yansheng,et al.Assessment on the hazard of flash flood disaster in Hubei Province based on BP neural network[J].,2018,(01):148-154.[doi:10.13577/j.jnd.2018.0118]
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基于BP神经网络的湖北省山洪灾害危险性评价
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《自然灾害学报》[ISSN:/CN:23-1324/X]

卷:
期数:
2018年01期
页码:
148-154
栏目:
出版日期:
2018-02-28

文章信息/Info

Title:
Assessment on the hazard of flash flood disaster in Hubei Province based on BP neural network
作者:
冯快乐12 周建中12 江焱生3 孙怀卫12 李薇12 蔡佳明12
1. 华中科技大学 水电与数字化工程学院, 湖北 武汉 430074;
2. 数字流域科学与技术湖北省重点实验室, 华中科技大学, 湖北 武汉 430074;
3. 湖北省防汛抗旱指挥部办公室, 湖北 武汉 430071
Author(s):
FENG Kuaile12 ZHOU Jianzhong12 JIANG Yansheng3 SUN Huaiwei12 LI Wei12 CAI Jiaming12
1. School of Hydropower and Information Engineering, Huazhong University of Science and Technology, Wuhan 430074, China;
2. Hubei Key Laboratory of Digital Valley Science and Technology, Huazhong University of Science and Technology, Wuhan 430074, China;
3. Flood Control Drought Relief Office of Hubei Province, Wuhan 430071, China
关键词:
山洪灾害危险性评价BP神经网络RBF神经网络
Keywords:
flash flood disasterhazardBP neural networkRBF neural network
分类号:
P429;X43;X9
DOI:
10.13577/j.jnd.2018.0118
摘要:
湖北省是山洪灾害多发地,每年因山洪灾害造成的损失十分严重,山洪灾害危险性评价对于防灾减灾具有重要意义。构建了湖北省山洪灾害危险性评价指标体系,根据山洪灾害危险性与历史山洪灾害的相关性,采用RBF(Radial Basis Function,径向基函数)神经网络对小样本调查数据进行拟合、扩展,形成可靠的数据集,使用扩展数据集对BP(Back Propagation)神经网络进行训练,建立山洪灾害危险性评价模型,通过建立的评价模型分析了湖北省山洪灾害危险性的分布特征。研究结果表明,湖北省山洪灾害危险性最高的区域分布在西南部的建始县、巴东县、鹤峰县和中部的钟祥市、孝感市,总面积为1.47万km2;湖北省中等危险区分布在全省各地,面积达到12.48万km2;湖北省低危险区主要分布在西北部的房县、东部的黄陂区、嘉鱼县、黄冈市市辖区,总面积0.84万km2
Abstract:
Hubei Province is a hotspot of flash flood disaster, and the loss caused by flash flood disaster is serious every year. Assessment on the hazard of flash flood disaster has great significance for disaster prevention and mitigation. This paper proposed an index system of assessment on the hazard of flash flood disaster in Hubei Province. The assessment model on the hazard of flash flood was established, according to the correlation of flash flood hazard and historical flood disasters, using RBF (Radial Basis Function) neural network fitting and expanding the small observed data, forming a reliable data set, and training BP (Back Propagation) neural network with the data set. This paper analyzed distribution characteristics of the hazard of flash flood disaster of Hubei Province by established assessment model. The results showed that the high-hazard areas of flash flood disaster distributed in Jianshi County, Badong County and Hefeng County, the southwest of Hubei Province, and Zhongxiang City, Xiaogan City, the middle part of Hubei Province, a total area is of 14 700 km2. The medium-hazard areas in Hubei Province reached 124 800 km2. The low-hazard areas distributed in Fang County, the northwest, Huangpi District, Jiayu County, Huanggang City, the east of Hubei Province, total area is of 8, 400 km2.

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备注/Memo

备注/Memo:
收稿日期:2017-02-17;改回日期:2017-06-13。
基金项目:国家自然科学基金重大研究计划重点项目(91547208);国家自然科学基金面上项目(51579107);国家自然科学基金重点项目(51239004)
作者简介:冯快乐(1993-),男,博士研究生,主要从事水文水资源管理研究.E-mail:1060600894@qq.com
通讯作者:周建中(1959-),男,教授,博导,主要从事水电能源及其复杂系统分析的先进理论与方法研究.E-mail:jz.zhou@mail.hust.edu.cn
更新日期/Last Update: 1900-01-01