Due to the lack of macro and systematic data, the target cost of high-star hotel project cannot meet the characteristics and needs of the hotel project itself. Therefore, the establishment of star hotel development scale prediction is urgent. In the scale development strategy, based on the previous studies, combined with the development characteristics of regional high-star hotels in a city, this paper constructs the index system of influencing factors of the development scale of high-star hotels and extracts the main influencing factors of hotel development scale by principal component analysis and partial relationship analysis, which are mainly urban development, economic development, tourism development, tourism development exhibition industry development, business development, and transportation development. The BP artificial neural network prediction method is used to establish a prediction model for the development scale of high-star hotels, by adopting the above key extraction factors as input of BP neural network. Through the input and output of the scale influence index data, the development scale of star hotels is accurately predicted. The simulation results verify the effectiveness and reliability of the star hotel development scale prediction strategy based on BP neural network, in terms of accuracy and model superiority.
Prediction of Surface Water Quality by Artificial Neural Network Model Using Probabilistic Weather Forecasting
