Multiple Linear Regression-Based Prediction Model to Detect Hexavalent Chromium in Drinking Water

  • K. Sri Dhivya Krishnan
  • P. T. V. BhuvaneswariEmail author
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 711)


This paper discusses the dependency between various water quality parameters (WQPs), namely pH, TDS, and conductivity that are determined to estimate the presence of hexavalent chromium compounds in drinking water. Multiple linear regression (MLR)-based prediction model is proposed to estimate the above parameters. The changes in WQPs are analyzed under both instant and stable conditions. The deviation between the measured and the estimated WQP is computed and added as the correction factor in order to improve the detection accuracy.


Water quality parameters Hexavalent chromium Multiple linear regression Correction factor and detection accuracy 


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Copyright information

© Springer Nature Singapore Pte Ltd. 2019

Authors and Affiliations

  • K. Sri Dhivya Krishnan
    • 1
  • P. T. V. Bhuvaneswari
    • 1
    Email author
  1. 1.Department of Electronics EngineeringMadras Institute of Technology, Anna UniversityChennaiIndia

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