Research Paper | Civil Engineering | India | Volume 4 Issue 6, June 2015
Artificial Neural Network: An Effective Tool for Predicting Water Quality for Kalyan-Dombivali Municipal Corporation
Rajesh R. Goyal, Hema Patel, S. J. Mane
Abstract: Municipal Corporations often do not prioritize environmental impacts caused in the areas due to pollution. Due to this many cities are facing severe pollution problems which are affecting health of citizens and disturbing overall ecological balance of the cities. Most often the people are not aware of the quality of air and water in the city. Hence there is need to study, analyze and predict the water quality for Kalyan Dombivali Municipal Corporation (KDMC). The present work aims at development of an artificial neural network (ANN) model for predicting water quality in KDMC area. The raw water quality at the intake of treatment plant has been consistently deteriorating and an advanced knowledge of the pollutant load expected at the treatment plant is beneficial to the operator at the treatment plant. This information helps to budget for the chemicals and extend of treatment to be provided. Results of Physico-chemical analysis performed on raw water from the river Ulhas has been tabulated for the following parameters pH, TDS, Turbidity, Hardness and Chloride on a daily basis for the past three years. Predictions about water quality for the next few days and suggestions about minimizing threats will be made by using Artificial Neural Network. The first model has been run and has shown output values of Coefficient of co-relation (R) as high as 0.9992 by using Modular Neural Network.
Keywords: Artificial Neural Network ANN, KDMC, Prediction, Water Quality, Generalized Feed Forward Network, Multilayer Perceptron Network, Modular Neural Network
Edition: Volume 4 Issue 6, June 2015,
Pages: 2863 - 2866
How to Cite this Article?
Rajesh R. Goyal, Hema Patel, S. J. Mane, "Artificial Neural Network: An Effective Tool for Predicting Water Quality for Kalyan-Dombivali Municipal Corporation", International Journal of Science and Research (IJSR), https://www.ijsr.net/get_abstract.php?paper_id=SUB156112, Volume 4 Issue 6, June 2015, 2863 - 2866
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