Description

The present study explores the potential of artificial neural network to predict the performance and exhaust emissions of an existing single cylinder four-stroke CRDI engine under varying CNG and EGR strategies. Based on the experimental data an ANN model is developed to predict performance and emission parameters of the experimental engine. The study was carried out with 70% of total experimental data selected for training the neural network, 15% for the network's cross-validation and remaining 15% data has been used for testing the performance of the trained network. The developed ANN models were capable of predicting the performance and emissions of the experimental engine with excellent agreement.

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