Supply and Demand Planning for Water: A Sustainable Water Management System

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@InProceedings{Athapaththu:2020:ICAC,

• author = "A. M. H. N Athapaththu and D. U. S Illeperumarachchi and H. M. K. U Herath and H. K Jayasinghe and W. H. Rankothge and Narmadha Gamage",
• title = "Supply and Demand Planning for Water: A Sustainable Water Management System",
• booktitle = "2020 2nd International Conference on Advancements in Computing (ICAC)",
• year = "2020",
• volume = "1",
• pages = "305--310",
• 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.",
• keywords = "genetic algorithms, genetic programming",
• DOI = "doi:10.1109/ICAC51239.2020.9357256",
• month = dec,
• notes = "Also known as \cite{9357256}",

}

Genetic Programming entries for A M H N Athapaththu D U S Illeperumarachchi H M K U Herath H K Jayasinghe Windhya Rankothge Narmadha Gamage

Citations