An adaptive RBF network optimised using a genetic algorithm applied to rainfall forecasting

Rainfall prediction is a challenging task, especially in a modern world facing the major environmental problem of global warming. The proposed method uses an adaptive radial basis function neural network mode with a specially designed genetic algorithm (GA) to obtain the optimal model parameters. A significant feature of the adaptive radial basis function network is that it is able create new hidden units and solve the spread factor problem using a genetic algorithm. It is shown that the evolved parameter values improved performance.