Supply and Demand Planning for Water: A Sustainable Water Management System
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gp-bibliography.bib Revision:1.8081
- @InProceedings{Athapaththu:2020:ICAC,
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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",
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title = "Supply and Demand Planning for Water: A Sustainable
Water Management System",
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booktitle = "2020 2nd International Conference on Advancements in
Computing (ICAC)",
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year = "2020",
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volume = "1",
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pages = "305--310",
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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.",
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keywords = "genetic algorithms, genetic programming",
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DOI = "doi:10.1109/ICAC51239.2020.9357256",
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month = dec,
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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