|Title:||Designing intelligent disaster prediction models and systems for debris-flow disasters in Taiwan||Authors:||Hsu-Yang Kung
|Keywords:||Debris-flow prediction models;Disaster prevention;Back-propagation network;Decision support system;Mobile multimedia communications||Issue Date:||Apr-2012||Journal Volume:||39||Journal Issue:||5||Start page/Pages:||5838-5856||Abstract:||
Effective disaster prediction relies on using correct disaster decision model to predict the disaster occurrence accurately. This study proposes three effective debris-flow prediction models and an inference engine to predict and decide the debris-flow occurrence in Taiwan. The proposed prediction models are based on linear regression, multivariate analysis, and back-propagation networks. To create a practical simulation environment, the decision database is the pre-analyzed 181 potential debris-flows in Taiwan. According to the simulation results, the prediction model based on back-propagation networks predicted the debris flow most accurately. Moreover, a Real-time Mobile Debris Flow Disaster Forecast System (RM(DF)2) was implemented as a three-tier architecture consisting of mobile appliances, intelligent situation-aware agents and decision support servers based on the wireless/mobile Internet communications. The RM(DF)2 system provides real-time communication between the disaster area and the rescue-control center, and effectively prevents and manages debris-flow disasters.
|Appears in Collections:||食品安全與風險管理研究所|
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