Journal of Intelligent Systems 27 (2):291-302 (2018)

Railway freight transportation is an important part of the national economy. Accurate forecast of railway freight volume is significant to the planning, construction, operation, and decision making of railways. After analyzing the application status of generalized regression neural network in the prediction method of railway freight volume, this paper improves the performance of this model by using improved neural network. In the improved method, genetic algorithm is adopted to search the optimal spread, which is the only factor of GRNN, and then the optimal spread is used for forecasting in GRNN. In the process of railway freight volume forecasting, through this method, the increments of data are taken in the calculation process and the goal values are obtained after calculation as the forecasted results. Compared with the results of GRNN, a higher prediction accuracy is obtained through the GA-improved GRNN. Finally, the railway freight volumes in the next 2 years are forecasted based on this method.
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DOI 10.1515/jisys-2016-0172
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