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*In International journal of environmental science and technology : IJEST *

**** : *R* ^{2} = 0.75) during lockdown over Streeter Phelps (*R* ^{2} = 0.57). Polynomial regression and Newton's Divided Difference model predicted possible values of water quality parameters till 30th June, 2020 and 07th August, 2020, respectively. It was found that predicted and real values were close to each other. Genetic algorithm was used to optimize hyperparameters of algorithms like Support Vector Regression and Radical Basis Function Neural Network, which were then employed for prediction of all examined water quality metrics. Computed values from ANN model were found close to the experimental ones (*R* ^{2} = 1). Support Vector Regression-Genetic Algorithm Hybrid proved to be very effective for accurate prediction of pH, Biochemical Oxygen Demand, Dissolved Oxygen and Total coliform count during lockdown.

**Supplementary Information** :

*Singh J, Swaroop S, Sharma P, Mishra V*

*2022-Jul-27*

**Artificial neural network, Biochemical oxygen demand, Dissolved oxygen, Modeling, The Ganga, Total Coliform Count, pH**

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