Please use this identifier to cite or link to this item: https://rda.sliit.lk/handle/123456789/1592
Title: Supply and Demand Planning for Water: A Sustainable Water Management System
Authors: Athapaththu, A.M.H.N.
Illeperumarachchi, D.U.S.
Herath, H.M.K.U.
Jayasinghe, H.K.
Rankothge, W.H.
Gamage, N.
Keywords: Sustainable Water Management
Prediction
Recurrent Neural Network (RNN)
Long Short-Term Memory (LSTM)
Genetic Programming (GP)
Issue Date: 10-Dec-2020
Publisher: 2020 2nd International Conference on Advancements in Computing (ICAC), SLIIT
Series/Report no.: Vol.1;
Abstract: Sustainable water management requires maintaining the balance between the demand and supply, specifically addressing water demand in urban, agricultural, and natural systems. Having an insight on water supply forecasting and water consumption forecasting, will be useful to generate an optimal water distribution plan. A platform that targets the sustainable water management concepts for domestic usage and paddy cultivation is proposed in this paper, with the following components: (1) forecasting water levels of reservoirs, (2) forecasting water consumption patterns, and (3) optimizing the water distribution. We have used Recurrent Neural Network (RNN) and, Long Short-Term Memory (LSTM) for forecasting modules and, Genetic Programming (GP) for optimizing water distribution. Our results show that, using our proposed modules, sustainable water management related services can be automated efficiently and effectively.
URI: http://rda.sliit.lk/handle/123456789/1592
ISBN: 978-1-7281-8412-8
Appears in Collections:2nd International Conference on Advancements in Computing (ICAC) | 2020
Department of Information Technology-Scopes
Research Papers - Dept of Computer Systems Engineering
Research Papers - IEEE

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