The Forecast of the Temperature in Subway Station Based on RVFL Neural Network
Yuan Zhang, Bo Li, Yanping Wang, Qing Tian · 2018
In recent years, people in big cities tend to take the subway. In the morning and evening, the carrying capacity of the subway is very large, and the quality of the early thermal environment will be seriously reduced. Therefore, it is important to analyze the factors affecting the thermal environment of the subway station and predict the temperature. In this paper, a model based on Random Vector Functional Link Neural Network (RVFLNN) is proposed. The study results show that the temperature forecast model can effectively and quickly predict the temperature in subway station.