Short-term Forecasting For High-speed Railway Passenger Demands And The Train Scheduling Research

With the development of China’s economy, China’s high-speed railway undertakings constant development since the Beijing-Tianjin Intercity Railway opened from August1st,2008, China has entered the era of high-speed railway. With the Wuhan-Guangzhou high-speed railway, Beijing-Shanghai high-speed rail and other high-speed railway line, it brings our country into the hall of the high-speed railway. As its own security and high-speed, the high-speed railway attract many passengers, more and more travelers choose to take the high-speed rail. For the railway authorities, the passenger prediction and rational trains scheduling are the problem. This article focused on the current China’s high-speed rail passenger flow forecast and train scheduling problem to make related research. The short-term passenger forecast is based on the historical traffic data, Short-term passenger flow forecast based on historical traffic data, the input data required to determine the model by analyzing the characteristics of the Wuhan-Guangzhou high-speed passenger railway. Based on the advantage of wavelet neural network model in the previous literature, we build the GA-Wavelet neural network model, then compared with the Gray neural network model and Wavelet neural network model. Through three forecast model’s errors, we find the GA-wavelet neural network’s predictions are better. The GA-wavelet neural network’s passenger prediction can give the staff the information of coordinate the passenger organization work. Short-term forecast passenger can also provide the basic data for the railway authorities to dispatch the trains.Based on the GA-wavelet neural network’s prediction, we establish the high-speed railway scheduling model. According to it, we can calculate the desired number of trains, and avoid the excessive waste of transportation resources vehicles. It can provide a reference for railway operations. Take full account of the train lines in the limits on the amount invested, the capacity of the vehicle, carriage capacity and the railway fares. Train vehicle carrying capacity as decision variables, the objective is maximizing economic benefits. By solving the model, we obtain various paths optimal number of trains and maximum profit of railway operator. The results show that the train scheduling can ease the pressure of passenger transportation, Railway operators can make more effective use of transportation resources and avoid the waste of railway transport resources, and improve the railway’s economic and social benefits.