TY  - JOUR
AU  - Okafor, Ahmed
AU  - Khan, Deepak
AU  - Qureshi, Elena
TI  - Activated Sludge Treatment using Artificial Neural Networks
JO  - Open Access Journal of Engineering Applications
PY  - 2000
VL  - 24
IS  - 2
SP  - 577
EP  - 589
AB  - Traditional analytical treatments of activated sludge treatment rest on simplifying assumptions that the present study seeks to relax. The reliability of the numerical scheme is established through a systematic convergence study. A reduction of nearly 8% in material consumption was achieved without any loss of safety. The results should help engineers make better-informed decisions under conditions of uncertainty.
KW  - activated sludge treatment
KW  - artificial neural networks
KW  - genetic algorithm
KW  - simulated annealing
KW  - wind energy
SN  - 3105-7004
DO  - 10.55555/oajea.2000.2402.030
UR  - https://journal.bsaps.com/article/7747
ER  -