Prediction of activated sludge bulking based on a self-organizing RBF neural network

► A self-organizing radial basis function (SORBF) neural network method is utilized to predict the evolution of the sludge volume index (SVI). ► The hidden nodes in the SORBF neural network can be grown or pruned to achieve the appropriate network complexity and maintain overall computational efficiency. ► The input-output selection to calculate the SVI values is also discussed. ► The variables with key relations to the sludge bulking are used as the inputs for the SVI.