Research on the north polar tourism resources evaluation model based on BP neural network algorithm

Abstract

Polar tourism resources have unique properties. The Polar resource evaluation is comprehensive and multi-angle based on communication value, cultural value, economic value, educational value and so on. A scientific and reasonable evaluation model can provide the basis for the exploitation and utilization of polar tourism resources. The purpose of this paper is to apply BP neural network algorithm to self-learning intelligent evaluation, especially those not fully explored polar tourism resources. The subjective random factors are avoided to objectively evaluate polar tourism resources.