Evaluation of Ability to Supply Water Based on GRNN Neural Network Model: Case of Beijing
Available Online March 2018.
- https://doi.org/10.2991/mecae-18.2018.28How to use a DOI?
- Evaluating system; Ability to supply water; AHP; GRNN neural network.
- 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.
- Open Access
- This is an open access article distributed under the CC BY-NC license.
Cite this article
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 - https://doi.org/10.2991/mecae-18.2018.28 ID - Tian2018/03 ER -