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Soft Computing

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14-05-2020 | Methodologies and Application

Water management using genetic algorithm-based machine learning

Authors: S. G. Gino Sophia, V. Ceronmani Sharmila, S. Suchitra, T. Sudalai Muthu, B. Pavithra

Published in: Soft Computing | Issue 22/2020

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Abstract

Water scarcity is the major problem presently being faced globally; it is to be managed in an efficient manner. The water management procedure is one of the techniques to condense necessary water. The objective of water management system is that water supply agency to collect, distribute quality water without any delay and scarcity. An intelligent system is necessary for efficient production, collection and distribution. The proposed intelligent system consists of genetic operations with fitness value and neural network for training. The fitness function is used to make new intelligent members from existing population of water resources for water collection and distribution. The system is applicable for prediction about water consumption, distribution using decision-making algorithms to increase optimization performance by calculation of objective function of various population types. The regression performance of proposed intelligent system is calculated and compared with other algorithms.

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Title: Water management using genetic algorithm-based machine learning
Authors: S. G. Gino Sophia
V. Ceronmani Sharmila
S. Suchitra
T. Sudalai Muthu
B. Pavithra
Publication date: 14-05-2020
Publisher: Springer Berlin Heidelberg
Published in: Soft Computing / Issue 22/2020
Print ISSN: 1432-7643
Electronic ISSN: 1433-7479
DOI: https://doi.org/10.1007/s00500-020-05009-0

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