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

Author

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  • Cherl Nino M. Locsin

    (University of San Carlos, Cebu, Philippines)

  • Rosana J. Ferolin

    (University of San Carlos, Cebu, Philippines)

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%.

Suggested Citation

  • Cherl Nino M. Locsin & Rosana J. Ferolin, 2018. "Neural networks application for water distribution demand-driven decision support system," Journal of Advances in Technology and Engineering Research, A/Professor Akbar A. Khatibi, vol. 4(4), pages 160-175.
    • Handle: RePEc:apb:jaterr:2018:p:160-175
    DOI: 10.20474/jater-4.4.3
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    References listed on IDEAS

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    1. David, Cristina C. & Inocencio, Arlene B. & Largo, Francisco M. & Walag, Ed L., 1998. "Water in Metro Cebu: The Case for Policy and Institutional Reforms," Discussion Papers DP 1998-38, Philippine Institute for Development Studies.
    2. Reni Suryanita & Harnedi Maizir & Hendra Jingga, 2017. "Prediction of Structural Response Based on Ground Acceleration Using Artificial Neural Networks," International Journal of Technology and Engineering Studies, PROF.IR.DR.Mohid Jailani Mohd Nor, vol. 3(2), pages 74-83.
    3. repec:phd:pjdevt:jpd_1998_vol__xxv_no__2-a is not listed on IDEAS
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