Emission control in palm oil mills using artificial neural network and genetic algorithm

The present study utilized a combination of artificial neural network (ANN) and genetic algorithms (GA) to optimize the release of emission from the palm oil mill. A model based on ANN is developed from the actual data taken from the palm oil mill. The predicted data agree well with the actual data taken. GA is then employed to find the optimal operating conditions so that the overlimit release of emission is reduced to the allowable limit.