Evaluation of water quality and its driving forces in the Shaying River Basin with the grey relational analysis based on combination weighting

2021 ◽  
Author(s):  
Jie Tao ◽  
Xin-Hao Sun ◽  
Yang Cao ◽  
Min-Hua Ling
Keyword(s):  
Water Quality ◽  
River Basin ◽  
Grey Relational Analysis ◽  
Driving Forces ◽  
Relational Analysis ◽  
Grey Relational

The Grey Relational Analysis of Driving Forces for Water Consumed Structure

2012 ◽  
Vol 490-495 ◽  
pp. 1612-1616 ◽  
Author(s):  
Cui Mei Lv ◽  
Fa Xing Du
Keyword(s):  
Grey Relational Analysis ◽  
Driving Forces ◽  
Water Saving ◽  
Utilization Rate ◽  
Sustainable Utilization ◽  
Urbanization Level ◽  
Relational Analysis ◽  
Grey Relational Degree ◽  
Relational Degree ◽  
Grey Relational

Grey Relational Analysis is a method of analysis and calculates the relational degree of evaluated object, which can characterize the relational degree between object with viral object. In this paper it was used to analyze the driving forces of water consumed structure change, and YiChang city was selected as an example. Adopted grey relational degree analysis, the main factors were found out. The results showed that industry water utilization rate, irrigation area, urbanization level are the main driving forces, and corresponding water-saving measures were put forward. This study can provide reference for the construction of water-saving society and sustainable utilization of water resource.

Assessment of Water Quality Using Grey Relational Analysis and Principal Component Analysis

2011 ◽  
Vol 255-260 ◽  
pp. 2829-2835 ◽  
Author(s):  
Yong Qian Cheng ◽  
Hong Mei Ma ◽  
Qian Wu Song ◽  
Yue Zhang
Keyword(s):  
Water Quality ◽  
Principal Component Analysis ◽  
Grey Relational Analysis ◽  
Principal Component ◽  
Water Quality Assessment ◽  
Component Analysis ◽  
Comprehensive Assessment ◽  
Relative Importance ◽  
Relational Analysis ◽  
Grey Relational

This paper investigates the comprehensive assessment of water quality, which is generally a multi-attribute assessment problem. In this context, the grey relational analysis is adopted to settle the no uniformity problem of water quality attributes. The principal component analysis is applied to calculate the weighting values corresponding to various attributes of water quality so that their relative importance can be properly and objectively described. Results of study reveal that grey relational analysis coupled with principal component analysis can effectively solve the multi-attribute water quality assessment. The method is universal and can be a useful tool to improve the comprehensive assessment of water quality.

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