BP神经网络预警在旅游安全预警信息系统中的应用

Application of BP Neural Network in Travel Security Early Warning Information System

将BP神经网络预警技术应用于旅游安全预警信息系统的开发实践,研究建立了一个基于BP神经网络的旅游安全预警模型。该模型有4个子系统构成,即预警知识提取子系统、预警信息库、报警系统和人机互动设备,分析总结了包含旅游地灾害频度、出游设施安全度和旅游地区域安全度三大类10个子因子为内容的旅游安全预警影响因素。在旅游安全预警的影响因素和安全预警的报警判别模式的基础上,进行了旅游安全预警应用的实验设计。实验结果显示,该模型应用效果良好。

This thesis applied the BP neural network technology in the travel security early warning information system. It established a travel security early warning model based on the BP neural network. This model had four subsystems constitutions： Namely tile early warning knowledge withdraws the subsystem, the early warning database, the alarm system and the man - machine interaction equipment. And the analysis summarized conmined the traveling disaster frequency, to go to travel the facility degree of security and the traveling region degree of security , three big kinds of 10 stature factors reports to the police in the distinction pattern foundation for the content traveling safe early warning influence factor. Traveling safe early warning influence factor and the safe early warning and analyzed the influence factors and differentiate model about travel security early warning. Based on it, this research carried on an experimental design employed in travel security prewaming model. Its result revealed this model application effect to be good.