Abstract
Optimization of Compression Ignition Engines through advanced artificial neural network is the modern process in mechanization and best utilization of modern technology for better economic scenarios in coming generation. This project deals with the feasibility of using artificial neural networks in combination with genetic algorithms to optimize the diesel engine settings. The engine is operated by using diesel and sunflower oil blends and the output parameters are calculated theoretically with the standard mechanical formulae and those manual experimental calculated values are used for training several neural networks with different various hidden layer [ n x m ] matrix combinations. The output values given by these trained networks are compared with experimental values and out of which the trained error values are taken for all networks.
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