Research on Natural Disaster Risk Assessment Model Based on Support Vector Machine and Its Application

被引:0
作者
Chen, Junfei [1 ]
Zhao, Shihao [1 ]
Liao, Weihao [1 ]
Weng, Yuan [1 ]
机构
[1] Hohai Univ, Sch Business, State Key Lab Hydrol Water Resources & Hydraul En, Nanjing, Peoples R China
来源
NEURAL INFORMATION PROCESSING, PT 2, PROCEEDINGS | 2009年 / 5864卷
关键词
Support Vector Machine; Natural Disasters; Risk Assessment;
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
The natural disaster risk assessment model based on support vector machine (SVM) is put forward according to the features of natural disaster risk assessment. The indicator system which includes the collapse of houses, the affected areas, the number of casualties, direct economic losses is established by China's actual situation of the regional meteorological disaster. A case for assessing the natural disasters risk of Chinese regions is studied using the established model. The evaluation results show that the evaluation model established is simple and effective. It has good generalization ability in the case of small samples. The results of research in this paper have important reference for natural disaster risk management and decision-making.
引用
收藏
页码:762 / 769
页数:8
相关论文
共 50 条
  • [21] Flood disaster loss comprehensive evaluation model based on optimization support vector machine
    Huang, Zhiwei
    Zhou, Jianzhong
    Song, Lixiang
    Lu, Youlin
    Zhang, Yongchuan
    EXPERT SYSTEMS WITH APPLICATIONS, 2010, 37 (05) : 3810 - 3814
  • [22] Disaster prediction model based on support vector machine for regression and improved differential evolution
    Xiaobing Yu
    Natural Hazards, 2017, 85 : 959 - 976
  • [23] Flood disaster evaluation model based on kernel dual optimization support vector machine
    Deng, Weiping
    Zhou, Jianzhong
    Zou, Qiang
    Xiao, Jian
    Zhang, Yongchuan
    Hua, Weihua
    Information Technology Journal, 2013, 12 (12) : 2412 - 2418
  • [24] Disaster prediction model based on support vector machine for regression and improved differential evolution
    Yu, Xiaobing
    NATURAL HAZARDS, 2017, 85 (02) : 959 - 976
  • [25] Flash flood vulnerability assessment of roads in China based on support vector machine
    He, Yufeng
    Ma, Deying
    Xiong, Junnan
    Cheng, Weiming
    Jia, Hongliang
    Wang, Nan
    Guo, Liang
    Duan, Yu
    Liu, Jun
    Yang, Gang
    GEOCARTO INTERNATIONAL, 2022, 37 (21) : 6141 - 6164
  • [26] Research on Application Evaluation of Support Vector Machine Prediction Model in Slope Engineering
    Zhen, Wang
    Ang, Li
    2019 2ND INTERNATIONAL CONFERENCE ON MECHANICAL ENGINEERING, INDUSTRIAL MATERIALS AND INDUSTRIAL ELECTRONICS (MEIMIE 2019), 2019, : 16 - 20
  • [27] A Technological Innovation Risk Evaluation Model Based on Support Vector Machine
    Ting, Wang
    Hui, Zhang
    PROCEEDINGS OF THE 2ND INTERNATIONAL CONFERENCE ON RISK MANAGEMENT & ENGINEERING MANAGEMENT, VOLS 1 AND 2, 2008, : 9 - 12
  • [28] Preference risk assessment method based on grey multi index kernel support vector machine model
    Zhang, Zhengyang
    Mi, Zengyu
    CLUSTER COMPUTING-THE JOURNAL OF NETWORKS SOFTWARE TOOLS AND APPLICATIONS, 2019, 22 (02): : S4323 - S4329
  • [29] Preference risk assessment method based on grey multi index kernel support vector machine model
    Zhengyang Zhang
    Zengyu Mi
    Cluster Computing, 2019, 22 : 4323 - 4329
  • [30] Research on railway disaster monitoring and warning system based on disaster risk assessment model
    Wu, Y., 1600, Chinese Academy of Railway Sciences (33): : 121 - 125