Application of data mining software to predict the alum dosage in coagulation process: A case study of Vientaine, Lao PDR

Khoumkham Ladsavong, Petchporn Chawakitchareon, Yasushi Kiyoki

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

This paper presents an alum dosage prediction in coagulation process by using Weka Data Mining Software. The data in this research had been collected from Dongmarkkaiy Water Treatment Plant (DWTP), Vientiane capital, Laos PDR from 1 st January 2008 to 31 st October 2016. The total number of collected data were 2,891 records. In this research, we compared the results from multilayer perceptron (MLP), M5Rules, M5P, and REPTree method by using the root mean square error (RMSE) and mean absolute error (MAE) value. Three input independent variables, i.e. turbidity, pH, and alkalinity were used. The dependent variable was alum added for the coagulation process. Our experimental results indicated that the MLP method yielded the highest precision method in order to predict the alum dosage.

Original languageEnglish
Title of host publicationInformation Modelling and Knowledge Bases XXIX
EditorsNaofumi Yoshida, Chawan Koopipat, Yasushi Kiyoki, Petchporn Chawakitchareon, Aran Hansuebsai, Virach Sornlertlamvanich, Bernhard Thalheim, Hannu Jaakkola
PublisherIOS Press
Pages110-124
Number of pages15
ISBN (Electronic)9781614998334
DOIs
Publication statusPublished - 2018 Jan 1
Event27th International Conference on Information Modelling and Knowledge Bases, EJC 2017 - Krabi, Thailand
Duration: 2017 Jun 52017 Jun 9

Publication series

NameFrontiers in Artificial Intelligence and Applications
Volume301
ISSN (Print)0922-6389

Conference

Conference27th International Conference on Information Modelling and Knowledge Bases, EJC 2017
CountryThailand
CityKrabi
Period17/6/517/6/9

Keywords

  • Alum dosage
  • Coagulation process
  • Data mining software
  • Dongmarkkaiy water treatment plant
  • Lao PDR
  • Vientiane
  • Weka

ASJC Scopus subject areas

  • Artificial Intelligence

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  • Cite this

    Ladsavong, K., Chawakitchareon, P., & Kiyoki, Y. (2018). Application of data mining software to predict the alum dosage in coagulation process: A case study of Vientaine, Lao PDR. In N. Yoshida, C. Koopipat, Y. Kiyoki, P. Chawakitchareon, A. Hansuebsai, V. Sornlertlamvanich, B. Thalheim, & H. Jaakkola (Eds.), Information Modelling and Knowledge Bases XXIX (pp. 110-124). (Frontiers in Artificial Intelligence and Applications; Vol. 301). IOS Press. https://doi.org/10.3233/978-1-61499-834-1-110