A Case Study on a Combination NDVI Forecasting Model Based on the Entropy Weight Method

2017 ◽  
Vol 31 (11) ◽  
pp. 3667-3681 ◽  
Author(s):  
Shengzhi Huang ◽  
Bo Ming ◽  
Qiang Huang ◽  
Guoyong Leng ◽  
Beibei Hou
2021 ◽  
Author(s):  
Lei Guo ◽  
Xiufen ZHANG

Abstract Partial destructive disassembly (PDD) is essential for end-of-life products to improve their automatic disassembly efficiency and reduce disassembly cost. A feasibility evaluation of the PDD is the key step to evaluate whether the PDD can be implemented. However, it has not been studied previously to our knowledge. To deal with this problem, a multi-granularity feasibility evaluation method is proposed. A multi-granularity feasibility evaluation model of the PDD was constructed based on the complex product’s hierarchical structure, which not only described the evaluation indices from the product level to the component level but also presented methods and rules to quantify them. 1Thus, disassembly entropy was introduced into the target group’s coarse granularity evaluation. The feasibility of the fine-grained index of the PDD for the component layer was constructed based on the product’s failure characteristic. The fine-grained index was calculated by the fuzzy trigonometric function and its weighting was obtained based on the structure entropy weight method. Thus, the results of the evaluation were used as feedback to guide the PDD process. Finally, a Passat engine case study illustrates the feasibility and effectiveness of the method.


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