PREDICTION OF SEWAGE TREATMENT PLANT PERFORMANCE IN LUCKNOW CITY BY USING ARTIFICIAL NEURAL NETWORKS
Author(s):
Narendra pal gole, anand patel
Keywords:
Neural networks; Waste water treatment; Model studies; Prediction; Optimization; Biochemical oxygen demand;
Abstract
To predict the performance of a sewage treatment plant (STP), Artificial neural networks (ANN) models were developed based on past information. The data used in this work were obtained from a Bharwara 345 MLD Gomti nagar sewage Treatment Plant Lucknow, with an average flow rate of 345 million lit/day. Daily records of biochemical oxygen demand (BOD) concentrations through various stages of the treatment process over 4 months were obtained from the plant laboratory. Exploratory data analysis was used to detect relationships in the data and evaluate data dependence. ANN-based models for prediction of BOD concentrations in plant effluent are presented. The appropriate architecture of the neural network models was determined through several steps of training and testing of the models. The ANN-based models were found to provide an efficient and a robust tool in predicting WWTP performance.
Article Details
Unique Paper ID: 152613

Publication Volume & Issue: Volume 8, Issue 3

Page(s): 1015 - 1020
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