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The Frontiers of Society, Science and Technology, 2019, 1(6); doi: 10.25236/FSST.2019.010617.

Construction and Application of Forecast Model for Eco-Tourism Market Demand Based on BP Neural Network


Huize Chen

Corresponding Author:
Huize Chen

Xi'an Aeronautical University, Xi'an Shanxi 710077, China


Now, analysis of the tourism market in the future period of time usually uses time series prediction and causal model prediction. However, due to the complicated tourism market environment, the small change of factor will affect the final result. Therefore, these methods can’t predict the future market conditions of tourism very accurately. Since BP neural network is a mathematical algorithm for simulating the structure of the brain's neural network, it has a very good processing capability for such non-linear relationship problems, can sort out complicated and various factors and finish the model building systematically, and finally get the effective forecast result. Prediction of the tourism market is a typical multi-factor impact, and there are a lot of unknown factors of nonlinear relationship, so BP neural network is very suitable for analysis and processing of tourism market.


Eco-tourism market; BP neural network; Demand forecasting model

Cite This Paper

Huize Chen. Construction and Application of Forecast Model for Eco-Tourism Market Demand Based on BP Neural Network. The Frontiers of Society, Science and Technology (2019) Vol. 1 Issue 6: 87-95. https://doi.org/10.25236/FSST.2019.010617.


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