Quantitative evaluation method for coordinated development of ecological economy in mountainous areas based on grey clustering analysis

2021 ◽  
Vol 14 (7) ◽  
Author(s):  
Lan Xu
2021 ◽  
pp. 1-18
Author(s):  
Xiaoqing Huang ◽  
Zhilong Wang ◽  
Shihao Liu

In order to solve the problem of health evaluation of CNC machine tools, an evaluation method based on grey clustering analysis and fuzzy comprehensive evaluation was proposed. The health status grade of in-service CNC machine tools was divided, and the performance indicator system of CNC machine tools was constructed. On the above basis, the relative importance of each performance and its indicators were combined, and grey clustering analysis and fuzzy comprehensive evaluation was utilized to evaluate the health status of in-service CNC machine tools to determine their health grade. The proposed health status evaluation method was applied to evaluate the health level of an in-service gantry CNC machine that can be used for the machining propellers, and the results shown that the health status of the whole gantry CNC machine tool is healthy. The proposed evaluation method provides useful references for further in-depth research on the health status analysis and optimization of CNC machine tools.


2018 ◽  
Vol 2018 ◽  
pp. 1-11 ◽  
Author(s):  
Chao Min ◽  
Guoquan Wen ◽  
Binrui Li ◽  
Xiaochan Zhao

Taking the development plans of an offshore oilfield as an example, a new comprehensive evaluation method, the improved Grey Clustering Analysis based on the cloud model (GCAC), is presented in this paper, which takes the ambiguity, randomness, and uncertainty of data into account and overcomes the limits of the general methods, such as subjective prejudice and objective randomness. GCAC converts the data of the oilfield development plans into a cloud, which considers the data of fuzziness, randomness, and the relationship between them. The grey membership degree of each development plan is calculated by this cloud model and an improved grey whitened function is presented in this paper. Then the plans are reordered by their grey membership degrees. In order to make more reasonable consideration of the artificial or unartificial uncertainties, GCAC combines the Grey Entropy Weighting method, Analytical Hierarchy Process (AHP), and Expert Assessment method to determine the weights of each level of indexes, which makes the weights more reasonable and reduces the randomness and the fuzziness of data. GCAC can help obtain a better comparison between the development plans. The reliability of this method is verified by the calculation results.


2021 ◽  
Vol 675 (1) ◽  
pp. 012121
Author(s):  
Pei Du ◽  
Yan Lin ◽  
Weijun Zhang ◽  
Zhixuan Liu ◽  
Fang Lin ◽  
...  

2014 ◽  
Vol 36 (3) ◽  
pp. 247-252 ◽  
Author(s):  
J. H. Ryu ◽  
Y. K. Seo ◽  
Y. C. Boo ◽  
M. Y. Chang ◽  
T. J. Kwak ◽  
...  

Author(s):  
Baoquan Wu

Teaching quality evaluation of physical education usually involves multiple influence factors with grey and uncertain information. This brings about limitations to effective evaluation of teaching quality of physical education in colleges and universities. Thus, this paper draws merits from previous research and proposes a teaching quality evaluation system and model of physical education in colleges and universities. First, based on real situations, grey categories of evaluation state for physical education teaching quality are established. The definite weighted functions of grey category of evaluation state are confirmed. Specific steps of the teaching quality evaluation model based on grey clustering analysis are accounted for. Finally, a case study is introduced to verify the model. This model enlightens a new way to evaluate teaching quality of physical education in colleges and universities.


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