Application of Radial Basis Neural Networks to National Travel Revenue Forecasting

With the continuous upgrading of the demand for mass tourism, revenue forecasting of the tourism market is of great reference significance for the future development of the tourism industry. In this paper, a radial basis neural network prediction model is established by using the travel income data of China during 20 years, and the model is used to predict the travel income from 1995 to 2015. The experimental data show that the model has a smaller error and uses less time than the BP neural network model. It can better respond to the trend of national travel income with the seven elements, which provides an important reference for the development of the tourism industry.