Big Data Security Early Warning Visualization Model for Smart Tourism Oriented Rural Ecological Scenic Spots

Authors

  • Su Zhang

Abstract

The safety of scenic spots is the basis of the healthy and sustainable development of scenic spots. How to establish an effective and feasible early warning mechanism is the key to resolve the security emergencies. Tourism big data is a new model construction method based on data prediction and data mining. Based on tourism big data, the construction of a scenic spot safety early warning mechanism can realize the interconnection between the scenic spot and the outside. The mechanism can predict the hot degree and tourist saturation of scenic spots in advance, and expand the space of safety warning mechanism. Based on the design of BP neural network technology, this paper designs a model of the tourist attractions safety early warning system. The model early warning impact indicators include personnel indicators, administrative indicators and environmental indicators, a total of nine. Based on the model, a model experiment is carried out with R as the implementation language. The experimental results show that the accuracy of the model is good. This method can construct the safety emergency mechanism, rescue mechanism and guarantee mechanism of scenic spots, so as to realize the safe and normal operation of scenic spots.

Published

2020-04-30

Issue

Section

Articles