DocumentCode
554060
Title
Research on ANN-based assessment model of social renewability of city water resources
Author
Weihua Zeng ; Jingjing Shi ; Jie Zhu
Author_Institution
Sch. of Environ., Beijing Normal Univ., Beijing, China
Volume
2
fYear
2011
fDate
26-28 July 2011
Firstpage
816
Lastpage
820
Abstract
As the social renewability of water resources was rarely considered in city water resources assessment, we proposed a new assessment model: ANN-based assessment model of social renewability of city water resources. And the model was applied to analyze and assess main cities in the Yellow River basin. Each process of social cycle of city water resources considered, the assessment results could well reveal the potential utilization of city water resources, and could indicate the shortcomings of water resources utilization of the target city; thus, the assessment results could play a certain role in assistant decision-making. Furthermore, an assessment model now in common use: grey relational analysis (GRA) method, was selected to validate the established model. The validation results showed good relevance between the two methods. The practice in this paper revealed that the ANN-based assessment model of social renewability of city water resources is vivid, objective, precise and rational, possessing certain versatility and practicability, as well as broad application prospects.
Keywords
decision making; environmental science computing; grey systems; neural nets; rivers; water resources; ANN-based assessment model; Yellow River basin; assistant decision-making; city water resource utilization; city water resources assessment; grey relational analysis method; social cycle; social renewability; Analytical models; Artificial neural networks; Brain modeling; Cities and towns; Humans; Training; Water resources; Artificial Neural Network; Regeneration of water resources; Virtual City; Water resources assessment of city; Water resources renewability; Water resources social renewability;
fLanguage
English
Publisher
ieee
Conference_Titel
Natural Computation (ICNC), 2011 Seventh International Conference on
Conference_Location
Shanghai
ISSN
2157-9555
Print_ISBN
978-1-4244-9950-2
Type
conf
DOI
10.1109/ICNC.2011.6022209
Filename
6022209
Link To Document