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Decision algorithm based on data mining for coagulant type and dosage in water treatment systems.

H Bae1, S Kim, Y J Kim

  • 1School of Electrical and Computer Engineering, Pusan National University, Busan 609-735, South Korea. baehyeon@pusan.ac.kr

Water Science and Technology : a Journal of the International Association on Water Pollution Research
|May 26, 2006
PubMed
Summary

Effective water treatment is crucial due to increasing water scarcity. This study introduces a novel automatic decision algorithm for coagulation, optimizing coagulant selection and dosage using data mining.

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Area of Science:

  • Environmental Science
  • Chemical Engineering
  • Water Resource Management

Background:

  • Rising living standards and increased water utilization exacerbate water shortages.
  • Effective water treatment is essential for maintaining water quality and supply.
  • Coagulation, flocculation, and disinfection are key water treatment processes.

Purpose of the Study:

  • To propose a new automatic decision algorithm for the coagulation process.
  • To determine the optimal coagulant type and dosage using data mining techniques.

Main Methods:

  • Development of an automatic decision algorithm for coagulation.
  • Application of data mining techniques for coagulant selection and dosage determination.

Main Results:

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  • The proposed algorithm effectively determines coagulant type and amount.
  • Demonstrated a novel approach to automated coagulation control.

Conclusions:

  • The developed data mining-based algorithm offers an effective solution for optimizing coagulation in water treatment.
  • This automated approach can improve the efficiency and reliability of water treatment processes.