【摘要】 提高中国粮食生产量的预测精度与效率是人们关注的一个重要问题.对RBF神经网络的结构、特性和训练算法作了简要的概述.根据粮食产量与其影响因素之间存在的映射关系,应用RBF神经网络建立了多因素非线性时间序列预测模型,并进行了仿真试验.结果表明,用RBF神经网络进行粮食生产预测得到了十分满意的结果.更多还原

【Abstract】 It is an important problem to improve the prediction precision and efficiency of the corn production prediction in China. The structure, the training methods and characteristics of RBF neural network are introduced briefly. A RBF neural network model is established based on the relationship between corn production and its influential factors to predict the multi-relative factors and non-linear time series. A simulation experimental investigation has been done, with satisfying results.更多还原