Attribute recognition model for risk assessment of water inrush

2017 ◽  
Vol 78 (2) ◽  
pp. 1057-1071 ◽  
Author(s):  
Jing Wang ◽  
Shu-cai Li ◽  
Li-ping Li ◽  
Peng Lin ◽  
Zhen-hao Xu ◽  
...  
Author(s):  
Jian-lin Li ◽  
Shu-wei Wang ◽  
Yan Wang ◽  
Xin-yi Wang ◽  
Xiong-xiong Wang

2010 ◽  
Vol 29-32 ◽  
pp. 2698-2702
Author(s):  
Xian Qi Zhang ◽  
Wen Hong Feng ◽  
Nan Nan Li

It is necessary to take into account synthetically attribute of every index because of independence and incompatibility resulted from single index evaluating outcomes. Through the information entropy theory and attribute recognition model being combined together, attribute recognition model based on entropy weight is constructed and applied to evaluating groundwater quality by a new method, weight coefficient by the law of entropy value is exercised so that it is more objective. The outcome from concrete application indicates that it is suitable to evaluate water quality with reasonable conclusion and simple calculation.


2017 ◽  
Vol 36 (1) ◽  
pp. 317-326 ◽  
Author(s):  
Binbin Zhu ◽  
Li Wu ◽  
Yaxiong Peng ◽  
Weiwen Zhou ◽  
Chunhui Chen
Keyword(s):  

2013 ◽  
Vol 477-478 ◽  
pp. 870-873
Author(s):  
Du Wu ◽  
De Shan Tang ◽  
Xing Wang Lu ◽  
Wen Zhong Yu

Subjective factors could affect the weight distribution of each index in evaluation of reservoir eutrophication, so the example used entropy to deal with the weight distribution of each index. Combined attributes recognition method, the writer selected six indicators to build the entropy weight of attribute recognition model about reservoir eutrophication of ten large reservoirs in Guangdong Province. By comparing the calculated results with the results of matter-element model, the calculation results were basically consistent. So entropy weight of attribute recognition model is applicable to the evaluation of the reservoir eutrophication and it can ensure the fairness and reasonableness of weight distribution.


2020 ◽  
Vol 13 (14) ◽  
Author(s):  
Longqing Shi ◽  
Mei Qiu ◽  
Chao Teng ◽  
Ying Wang ◽  
Tianhao Liu ◽  
...  

2019 ◽  
Vol 38 (3) ◽  
pp. 667-675
Author(s):  
Zhuo Zheng ◽  
Rentai Liu ◽  
Qingsong Zhang

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