A Statistical Approach to the Prediction of Fluoride in River Water Using the Best Subset Method

Author:

Chintalacheruvu Madhusudana Rao,Modi Prakhar

Publisher

Springer Nature Switzerland

Reference66 articles.

1. Abdelmalik, K. W. (2016). Role of statistical remote sensing for Inland water quality parameters prediction. The Egyptian Journal of RS and Space Sciences, 21,193–200.

2. Abyaneh, H. M. (2014). Evaluation of multivariate linear regression and artificial neural networks in prediction of water quality parameters. Journal of Environmental Health Science & Engineering.

3. Adimalla, N. (2018). Elevated fluoride concentration levels in rural villages of Siddipet Telangana State South India. Data in Brief, 16, 693–769.

4. Adimalla, N., & Li, P. (2018). Occurrence, health risks, and geochemical mechanisms of fluoride and nitrate in groundwater of the rock-dominant semi-arid region, Telangana State, India. Human and Ecological Risk Assessment: An International Journal, 24(8), 2143–2161.

5. Adimalla, N., & Rajitha, S. (2018). Spatial distribution and seasonal variation in fluoride enrichment in groundwater and its associated human health risk assessment in Telangana State, South India. Human and Ecological Risk Assessment: An International Journal, 24(8), 2119–2132.

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