Prediction of the bulking phenomenon in wastewater treatment plants

The control and prediction of wastewater treatment plants poses an importan t goal: to avoid breaking the environmental balance by always keeping the s ystem in stable operating conditions. It is known that qualitative informat ion - coming from microscopic examinations and subjective remarks - has a d eep influence on the activated sludge process. In particular, on the total amount of effluent suspended solids, one of the measures of overall plant p erformance. The search for an input-output model of this variable and the p rediction of sudden increases (bulking episodes) is thus a central concern to ensure the fulfillment of current discharge limitations. Unfortunately, the strong interrelation between variables, their heterogeneity and the ver y high amount of missing information makes the use of traditional technique s difficult, or even impossible. Through the combined use of several method s - rough set theory and artificial neural networks, mainly - reasonable pr ediction models are found, which also serve to show the different importanc e of variables and provide insight into the process dynamics. (C) 2000 Else vier Science Ltd. All rights reserved.