【摘要】 采用误差反传前向网络（简称BP神经网络）建立汛期（6—8月）降水预测模型,并与采用逐步回归方法建立的模型进行对比试验。结果表明,基于BP神经网络的汛期降水预测模型不仅对历史样本的拟合精度更高,而且其独立样本的预测检验效果也比逐步回归方法更好,是一种具有一定应用前景的汛期降水预测方法。更多还原

【Abstract】 A prediction model for June-August rainfall is established in terms of a neural networkand and a stepwise regression expression is formulated with the. aid of the same factors for comparision. Results show that the model based on BP neural network is superior in fittings and predictions compared to the model stepwise regression, and it is a important and useful model for the actual operational forecasting of rainfall in the rainy season.更多还原