关键词: 一维T-S-C-Y模型, 云理论, 货运量, 径向基函数（RBF）, 神经网络

Abstract: A new uncertainty reasoning model based on cloud theory is firstly proposed after deeply analyzing the various freight transportation forecasting model，and then the relationship between freight transportation and related factors and the grey order of factors affecting freight transportation are analyzed and determined based on the theory of grey correlation.In addition，the freight transportation of Henan during 1997~2002 is predicted by a model based on one-dimension T-S-C-Y model and RBF neural network.The forecast model can not only integrate the fuzziness and randomness of a linguistic concept but also has the capacities of self-learning，self-organization，adaptation and strong fault-tolerant，and the output of the prediction model is the confidence interval which can well adapt the highly uncertain change of the freight transportation.The simulation results show that the outputs of T-S-C-Y model are in accord with the real ones，and the prediction model is more scientific and rational.

Key words: one-dimension T-S-C-Y model, cloud theory, freight transportation, Radial Basis Function（RBF）, neural network