The engine experiments require multiple tests that are hard, time-consuming, and high cost. Therefore, an artificial neural network model was developed in this study to successfully predict the engine performance and exhaust emissions when a port fuel injection spark ignition engine fueled with n-butanol–gasoline blends (0–60 vol.% n-butanol blended with gasoline referred as G100-B60) under various equivalence ratio. In the artificial neural network model, compression ratio, equivalence ratio, blend percentage, and engine load were used as th...
