旅游危机预警的BP神经网络模型及应用

Application of BP Neural Network Model in Tourism Crisis Early Warning System

从分析影响旅游业发展的因素出发,选择了对旅游业发展影响最大的危机预警指标,并结合相关数据样本,应用BP神经网络技术,研究建立一种基于BP神经网络模型的旅游危机预警系统,借助MATLAB中的神经网络工具箱进行仿真训练和检测,训练结果表明模型性能良好,预警准确率高,能够很好的用来对旅游危机进行预警、检测和分析研究。

The development of tourism faces many crises, such as war, disease and natural disasters. This thesis analyzed the factors that affect tourism development, selected the early warning indicators which gave tourism the most profound influence, combined with the date sample of related indexes, applied the BP neural network technology and established a warning system based on the BP neural network model. With the neural network toolbox in the MATLAB for early warning simulation experiment and detection, it proved that the model had a good training performance and high early warning accuracy, which is useful for tourism crisis early warning, detection and analysis in China.