Yuyang Ma1, Yifei Song2, Ruiyu Zhang2
1Tourism School, Xi’an International Studies University, Xi'an, Shaanxi, 710128, China
2Business School, Xi’an International Studies University, Xi'an, Shaanxi, 710128, China
Light pollution is a new type of environmental pollution, long-term exposure to light pollution not only harms human health, but also restricts urban development and even threatens biodiversity . In order to evaluate the risk level of light pollution in different regions, this paper first selects 9 indicators leading to light pollution risk, takes 10,000 regions in the world as samples, constructs a neural network model, and the output of the network is the probability value of the light pollution risk level in the region. To improve the accuracy of the output, the parameters are then updated by back propagation to constrain the predicted regional risk level to be close to the actual risk level. Finally, four real areas are selected, and the indicator data brought into the area is used to obtain the risk level.
light pollution risk level, neural network model, back propagation algorithm
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