Study on the appraisal analysis and forecasting model of diesel engine performance based on modular neural network
基于组合式神经网络的柴油机性能评估预测模型

By analyzing the relationship between technical states and performance parameters of diesel engine, an appraisal model based on modular neural networks is proposed. Firstly, the original samples are divided into several groups by applying the dynamic clustering method. Then each group is used to train a separate seed neural networks. During the appraisal phase, pattern recognition is employed to activate the corresponding seed neural networks for appraisal analysis. Experiment indicates that the model can solve the problem of low learning speed and difficult convergence and improve the accuracy of prediction.