The Typhoon Disaster Prediction And The System Design Of Disaster Prevention And Reduction

Typhoon is one of the most serious disasters which influence our country. And because of it, both economic and life safety have received hit badly every year, especially in the coastal areas. Thus evaluating typhoon disaster’ mitigation capacity and predicting disaster loss are very necessary. For the sake of studying typhoon disasters accurately and effectively, this paper analyzes the following aspects:For the cities and countries, the ability of resisting and reducing the typhoon disaster is an important self-protection ability indicator when facing the typhoon disaster. Analyzing the urban’s or regional’s ability of resisting and reducing the typhoon disaster scientifically and reasonably and improving the weakness directly have a good effect on achieving the resisting and reducing typhoon disaster work. In this paper, we use factor analysis method to extract the public factors from many indicators, use the regression method and entropy weight method to obtain comprehensive ranking after verification. Finally, we achieve the Zhejiang ability evaluation of resisting and reducing the typhoon disaster. After analyzing the actual typhoon cases, the results can objectively reflect the integrated situation of city’s ability of resisting and reducing the typhoon disaster. At the same time, they can put forward some concrete measures directly to improve the ability.Typhoon disasters can bring about huge loss. Causing disasters ability, exposure degree and resisting disasters ability are the important factors influencing the disaster loss. This paper uses an objective method to complete assessment of each ability index and disaster loss index, and studies the potential relationship between them. The tests get good effect with the model of multivariate nonlinear regression, and they will guide new directions for future research work.Just for the typhoon disaster loss assessment can not meet the need of modern natural disaster research. This article forecasts the typhoon disaster loss with the neural network trained by particle swarm optimization. Finally, it obtains the objective and correct forecast results of typhoon disaster loss by compared with traditional BP neural network results. The results show that the neural network trained by particle swarm optimization can reduce the prediction error, obtain higher precision data, and provide more reliable countermeasures and suggestions for typhoon prevention and mitigation work. Finally, we develop a platform based on WebGIS, which can prevent and reduce typhoon disaster. The platform has several function modules, including information querying, data processing, sand table simulation and countermeasures providing. In the system development process, it is based on the geographic information system platform, supported by database technology. System has algorithm models as the theoretical reasons and the goal is to guide typhoon disaster prevention and mitigation work.