Neural networks application for water distribution demand-driven decision support system

Cherl Nino M. Locsin and Rosana J. Ferolin
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Cherl Nino M. Locsin: University of San Carlos, Cebu, Philippines
Rosana J. Ferolin: University of San Carlos, Cebu, Philippines

Journal of Advances in Technology and Engineering Research, 2018, vol. 4, issue 4, 160-175

Abstract: Water is a basic necessity in our daily activities. Therefore, there should be enough supply of water to meet with our demands. By average, in Cebu City, Philippines alone, 24 cubic meters per household per month is used [1]. To meet the demand, water has to be properly distributed considering several factors, which are: (1) temperature, (2) precipitation, (3) population, (4) water rates, (5) historical water use, (6) water supply, and (7) socioeconomic proßile. This study developed an Artißicial Neural Network (ANN) water distribution decision support system that was able to predict water demand. The ANN was trained using historical records of the above-mentioned factors, and was able to provide municipal, and barangay water demand predictions with accuracy above 90%.

Keywords: Machine learning; Demand forecasting; Networks (search for similar items in EconPapers)
Date: 2018
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Persistent link: https://EconPapers.repec.org/RePEc:apb:jaterr:2018:p:160-175

DOI: 10.20474/jater-4.4.3

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