Quantitative Analysis of Tourism Resources in Beijing Based on Multiple Neural Network Fuzzy Comprehensive Evaluation under the Background of Normalization of Epidemic Prevention and Control

Abstract

The 2019-nCoV epidemic has a great impact on the tourism industry. The traditional quantitative analysis method of tourism resources can't comprehensively consider the uncertainty of the weight of each variable change on the impact of sudden events on tourism resources, which leads to the low accuracy of the prediction data. Using neural network to determine the weight value of fuzzy comprehensive evaluation can make the weight value more in line with the actual situation. This paper studies the quantitative analysis of Beijing tourism resources based on multiple neural network fuzzy comprehensive evaluation method under the background of prevention and control normalization. In this paper, the improved back propagation algorithm is used to train the network, and the connection weights of the network are gradually modified. This method can make the weight value of fuzzy comprehensive evaluation index gradually close to the actual situation, and get better training efficiency and effect. The basic resistance surface based on land type assignment is modified by using night light data of VIIRS / DNB, and the minimum cumulative resistance model is used to identify the tourist corridor. Based on the current situation of ecological security pattern, this paper studies the optimization strategy of security pattern under the goal of green eco-tourism. Finally, the method proposed in this paper is used to simulate and evaluate the quantitative analysis of Beijing tourism resources, and the correctness of the method is verified.