Evaluation of Ability to Supply Water Based on GRNN Neural Network Model: Case of Beijing

DOI

10.2991/mecae-18.2018.28How to use a DOI?

Keywords

Evaluating system; Ability to supply water; AHP; GRNN neural network.

Abstract

Water supply capacity is an important index for evaluating a city. In this paper, AHP (Analytic Hierarchy Process) is used to establish an index system and evaluation standard of the ability to supply water, and 15 evaluation indicators are put forward from 4 aspects of the relationship of supply and demand, the geographical factors, the economic factors and the environmental factors. Evaluation model for ability to supply water is established by the principle of GRNN (General Regression Neural Network) theory and methods. And then the model is used to comprehensively evaluate the water supply capacity of Beijing in 2005-2015, which is proved that the established GRNN evaluation model and evaluation method are reasonable and feasible.

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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TY  - CONF
AU  - Jiaming Tian
PY  - 2018/03
DA  - 2018/03
TI  - Evaluation of Ability to Supply Water Based on GRNN Neural Network Model: Case of Beijing
BT  - Proceedings of the 2018 International Conference on Mechanical, Electronic, Control and Automation Engineering (MECAE 2018)
PB  - Atlantis Press
SP  - 152
EP  - 155
SN  - 2352-5401
UR  - https://doi.org/10.2991/mecae-18.2018.28
DO  - 10.2991/mecae-18.2018.28
ID  - Tian2018/03
ER  -