Abstract
The major objective of the present study is to develop water quality prediction models after evaluation of water quality to predict water pollution of two lakes situated inside Tezpur University. The water quality parameters were analyzed using linear regression analysis and artificial neural network to predict the water quality. Correlation studies suggested a highly positive correlation between TS with turbidity and EC for both lakes. Modeling of TS and BOD by regression analysis suggests a good correlation between actual and predicted TS but a very poor correlation between actual and predicted BOD. Modeling of TS and BOD by ANN shows a very good correlation between the actual and predicted values for both TS and BOD for both the lakes studied. The error between the experimental and estimated ANN model is less than regression model, suggesting suitability of ANN model for prediction of studied parameters.
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Ahamad, K.U., Raj, P., Barbhuiya, N.H., Deep, A. (2019). Surface Water Quality Modeling by Regression Analysis and Artificial Neural Network. In: Kalamdhad, A., Singh, J., Dhamodharan, K. (eds) Advances in Waste Management . Springer, Singapore. https://doi.org/10.1007/978-981-13-0215-2_15
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DOI: https://doi.org/10.1007/978-981-13-0215-2_15
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