关键词: 灰色预测, 变异粒子群算法, 编组站, 解编作业量

Abstract: In order to scientifically and accurately forecast decoding amount of railway, this paper puts forward a kind of grey particle swarm combination model for accurately forecasting decoding amount of railway based on mutation particle swarm optimization algorithm and grey prediction method, where this algorithm is able to optimize the parameters and this method is able to accurately predict the system with the uncertainty factors. This paper also uses examples to analyze the prediction precision and feasibility of the grey particle swarm combination forecast model and compare with the traditional grey forecast model, the results show that this model obviously is better than the traditional grey forecasting model. Using this model to forecast railway future amount of railway is able to reasonably prepare the railway marshalling station and inspect the plan of operation, thus it provides a theory basis for marshalling yards planning and designing.

Key words: grey forecasting, mutation particle swarm optimization algorithm, marshalling station, decoding amount