The Complex Index System of Water Scarcity Based on the Grey Neural Network Model

DOI

10.2991/i3csee-16.2016.41How to use a DOI?

Keywords

Water Scarcity; Complex Index System; Grey Neural Network

Abstract

This paper attempts to establish mathematical models to evaluate and predicate water problems in the example of Qingdao.We establish a multi-indexical evaluation system of water resources to access regional water capacity and attempt to analyze the corresponding causes. We use Comprehensive Evaluation Index of Regional Water Resources Carrying Capacity (CW) to reflect the level of water scarcity in the target region; the CW value is calculated based on six indexes: water resources system index, social system index, economic system index, ecological system index, comprehensive coordination index, social index. Based on the indexical system, we can calculate the future water supply and demand by using prediction model based on principal component analysis and grey neural network respectively. The results show that by 2025, the CW value in Qingdao will first break 1.00 threshold, reaching “over-exploited” level.

Copyright

© 2016, 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  - Zihao Zheng
AU  - Shuxiao Wang
AU  - Jiarui Xing
PY  - 2016/04
DA  - 2016/04
TI  - The Complex Index System of Water Scarcity Based on the Grey Neural Network Model
BT  - Proceedings of the 2016 International Conference on Civil, Structure and Environmental Engineering
PB  - Atlantis Press
SP  - 210
EP  - 218
SN  - 2352-5401
UR  - https://doi.org/10.2991/i3csee-16.2016.41
DO  - 10.2991/i3csee-16.2016.41
ID  - Zheng2016/04
ER  -