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《Mathematics in Practice and Theory》 2013-16
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Tropical Cyclone Disaster Evaluation in Guangdong Province Based on Elman Neural Network model

LIU Xiao-qing;TANG Dan-ling;SUI Guang-jun;CHEN Shi-hong;Department of Computer Science and Technology,Guangdong University of Finance;State Key Laboratory of Tropical Oceanography,South China Sea Institute of Oceanology,Chinese Academy of Sciences;School of International Trade and Economics,Guangdong University of Foreign Studies;Cisco School of Information,Guangdong University of Foreign Studies;  
Estimating of tropical cyclone disaster loss is an important part of the preventing and mitigating disaster work.The paper introduces the basic principle of Elman neural network and the applications of Elman neural network in estimation of tropical cyclone disaster loss in Guangdong Province.In total 14 evaluation factors and 36 typhoons data of Guangdong were chosen to process the reduction of dimensionality,using the method of principal component analysis.The study establishes two kinds of tropical cyclone disaster loss estimating models,including the Elman neural network model and the BP neural network model.The comparative analysis shows that,the testing result of Elman neural network model,the mean square error of which is 0.953 and the mean error rate of which is 17.76%,is better than that of BP neural network.This estimating model can be used in estimation of tropical cyclone disaster loss in Guangdong Province,and provide important information to typhoon disaster reduction and decision support work.
【Fund】: 国家自然科学基金委员会与财团法人李国鼎科技发展基金会联合资助两岸合作研究项目;; “台风灾害对南海北部浮游植物和渔业资源的影响”(31061160190);; 广东省科技计划重点项目(重大台风灾害及城市火灾应急响应集成系统研制 2010B031900041);; 广东省哲学社会科学规划项目(广东省台风灾情预测研究 GD11YGL03);; 广东高校优秀青年创新人才培养计划项目(台风灾情预测和灾级评估模型研究:基于广东省台风灾害的实证分析 LYM11062)
【CateGory Index】: P429;X43
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