Genetic Programming Applied to Predictive Control in Environmental Engineering

We introduce a new hybrid Genetic Programming (GP) based method for timeseries prediction in predictive control applications. Our method combines existing state-of-the-art analytical models from predictive control with a modern typed graph GP system. The main idea is to pre-structure the GP search space with existing analytical models to improve prediction accuracy. We apply our method to a difficult predictive control problem from the water resource management industry, yielding an improved prediction accuracy, compared with both the best analytical model and with a modern GP method for time series prediction. Even if we focus this first study on predictive control, the automatic optimization of existing models through GP shows a great potential for broader application.