Proceedings of the 2018 International Conference on Mechanical, Electronic, Control and Automation Engineering (MECAE 2018)

The Optimal Solution to the Development of Water Resources Influencing Factors Based on GRNN and the Genetic Algorithm Model: Case of Tianjing

Authors
Keke Fang
Corresponding Author
Keke Fang
Available Online March 2018.
DOI
10.2991/mecae-18.2018.26How to use a DOI?
Keywords
Optimal solution; GRNN; The Genetic Algorithm
Abstract

According to GRNN ,the paper find the network of the relationship between geographical, economic and environmental factors and its influencing factors .According to the genetic algorithm, we detect four indicators influencing mainly the ability among the 9 indicators. Our plan of intervention aims to reduce the impact of these four factors on ability to develop Water Resource in the future. Finally, according to our plan of intervention, we can get the best conditions of all indicators in the future.

Copyright
© 2018, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Volume Title
Proceedings of the 2018 International Conference on Mechanical, Electronic, Control and Automation Engineering (MECAE 2018)
Series
Advances in Engineering Research
Publication Date
March 2018
ISBN
10.2991/mecae-18.2018.26
ISSN
2352-5401
DOI
10.2991/mecae-18.2018.26How to use a DOI?
Copyright
© 2018, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - Keke Fang
PY  - 2018/03
DA  - 2018/03
TI  - The Optimal Solution to the Development of Water Resources Influencing Factors Based on GRNN and the Genetic Algorithm Model: Case of Tianjing
BT  - Proceedings of the 2018 International Conference on Mechanical, Electronic, Control and Automation Engineering (MECAE 2018)
PB  - Atlantis Press
SP  - 144
EP  - 147
SN  - 2352-5401
UR  - https://doi.org/10.2991/mecae-18.2018.26
DO  - 10.2991/mecae-18.2018.26
ID  - Fang2018/03
ER  -