Prediction analysis model of integrated carrying capacity using set pair analysis

2016 ◽  
Vol 120 ◽  
pp. 39-48 ◽  
Author(s):  
Chao Wei ◽  
Xiaoyan Dai ◽  
Shufeng Ye ◽  
Zhongyang Guo ◽  
Jianping Wu
2012 ◽  
Vol 195-196 ◽  
pp. 764-769 ◽  
Author(s):  
Liang Ma ◽  
Jing Hua Zhao ◽  
Ming Hong ◽  
Liang Liang Chen

In view of the uncertainty of evaluation indicators for water resources carrying capacity the theory of set pair analysis is adopted. The samples are preliminarily classified by calculating the connection degree between the samples and evaluation indicators. Then the samples are further ranked through the identity, difference and antagonism set pair analysis. The weights of evaluation factors in the model are obtained from the avail value of data reflecting the information entropy, by which the weight allocation is more reasonable. The application result of this model to an example is compared with those obtained from integrated evaluating methods and the attribute recognition method. It shows that the proposed method is practical and reasonable.


Author(s):  
Zheng Li ◽  
Juliang Jin ◽  
Yi Cui ◽  
Libing Zhang ◽  
Chengguo Wu ◽  
...  

Abstract In order to describe the micro motion between the connection number components and seek a more applicable evaluation model, quantitatively evaluate and analyze regional water resources carrying capacity (WRCC). Firstly, an evaluation index system and grade standards of regional WRCC were constructed. Then, a method for determining the connection number was proposed, which considered the micro motion between the connection number components in system structure. Finally, built an evaluation model based on set pair analysis (SPA) and partial connection number (PCN) that used subtraction set pair potential (SPP) to identify vulnerability factors, and identification results were compared with total partial connection number (TPCN). The model was applied to Huaibei City, Anhui Province, China. The results showed that: the WRCC grade value was between 2 and 3 that was poor; the support and regulation subsystem grade value was between 2 and 3, and the pressure subsystem grade value was between 1 and 2. SPP identified that the support force and regulation force subsystem were the vulnerable subsystems. Eight indexes such as water resources per capita, rate of ecological water consumption and density of population were the main indicators causing the poor WRCC, which were in good agreement with the local measured data. In addition, the SPP and TPCN are compared to further verify rationality of the connection number determination method and reliability of the identification results. The model established in this paper has strong applicability and can also be used for the dynamic evaluation of other resources, environment and ecological carrying capacity. The results in this study can provide a scientific basis for water resources management and decision-making.


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