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中文摘要：
总结了BP网络和RBF网络在离心泵能量性能预测中的应用现状,介绍了这两种网络的结构及特点。分别采用BP网络和RBF网络建立了离心泵能量性能预测模型。用57组数据对这两个预测模型进行了训练,并用6组数据对两种网络结构的性能预测模型进行了仿真。研究结果表面：两种网络结果的预测模型预测精度比较接近且预测结果的趋势也相同;Z3;Y3,BP网络预测精度略高于RBF网络;BP网络扬程平均预测误差为3.85%,效率平均预测误差为1.39%,RBF网络扬程平均预测误差为4.79%,效率平均预测误差为3.43%;RBF网络预测所需时间仅为BP网络预测所需时间的一半。
英文摘要：
The application of the BP and RBF artificial neural networks in energy characteristics prediction of centrifugal pumps was summarized.The structure and characteristics of the two artificial neural networks were introduced in detail.The models of BP and RBF artificial neural network were established respectively to predict the centrifugal pump energy characteristics.The characteristics data of 57 centrifugal pumps were used to train the two models,and the data of the other 6 centrifugal pumps were used to test the two models.The study shows that the prediction results of the two networks are closer and the trends of prediction results are the same for the two networks.The precision of BP network is a little higher than that of RBF network.The head average prediction discrepancy for BP network is 3.85% and the efficiency average discrepancy is 1.39% points.The head average prediction discrepancy for RBF network is 4.79% and the efficiency average discrepancy is 3.43% points.The prediction time of RBF network is only half the time of BP network.
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