KINETIC-MODEL FOR THE EFFECTS OF HEAVY-METALS ON ACTIVATED-SLUDGE PROCESS USING NEURAL NETWORKS

This article demonstrates the application of neural network techniques for kinetic model building of heavy metals inhibition in activated sludge process. Neural network based models were developed in this study for the cases of both unacclimatized and acclimatized microorganisms. The first neural model presented for the unacclimatized sludge in this article was based on our previous experimental observations for the toxic effects of Pb, Cr, Zn, Ni and their mixture on the microbial growth of batch operation. Other models for both unacclimatized and acclimatized cases correspond to the observations concerning the effects of Ni, Cr and substrate concentration (COD) on the batch growth. Case study shows that this emerging approach is capable of describing the complex kinetics patterns commonly observed in wastewater treatment processes with accuracy and robustness.