Watershed management using neuroevolution

Neuroevolution refers to evolving neural networks using evolutionary methods. These algorithms have been applied to many problem domains, from game playing to robotics, which motivates this research. The problem of watershed management is addressed here in this research using the most prominent neuroevolution algorithms, i.e. NeuroEvolution of Augmenting Topologies (NEAT), neuro differential evolution and Enforced SubPopulations. The results indicate that neuroevolution is a suitable approach at addressing the watershed management problem, outperforming the other methods of neural network training.