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分享兴趣,传播快乐,增长见闻,留下美好。
亲爱的您,
这里是LearningYard新学苑!
今天小编给大家带来博士论文解读,
欢迎您的用心访问!
Share interest, spread happiness, increase knowledge, and leave beautiful.
Dear, this is the LearingYard Academy!
Today, the editor brings you the interpretation of articles.
Welcome to visit!
今天小编将为大家带来博士论文《基于多准则决策和三角模糊数的云服务选择方法研究及应用》实验结果与分析内容的解读,接下来我们开始今天的学习吧!
Today, the editor will bring you the interpretation of the experimental results and analysis content of the doctoral thesis "Research and Application of Cloud Service Selection Method Based on Multi criteria Decision Making and Triangular Fuzzy Numbers". Let's start today's learning!
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思维导图
下图是本节内容的思维导图:
The following figure is the mind map of this section:
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精读内容
作者通过三个方面来阐释实验结果。首先是模型有效性验证,根据前文计算出的权重,将两个模型的计算几个绘制成柱状对比图,如下所示。再根据图形进行进一步的分析验证本文所提出的模型的有效性。
The author explains the experimental results from three aspects. Firstly, the validity of the model is verified. Based on the weights calculated in the previous section, the calculated values of the two models are plotted as a bar chart for comparison, as shown below. Further analysis will be conducted based on the graphics to validate the effectiveness of the model proposed in this paper.
其次是一致性比率分析,作者在前文已经做了针对实验过程的判断矩阵的一致性检验,得到成对比较矩阵的不一致程度都在可接受的范围内。接着通过公式计算AHP模型和AUP-BWM模型在第二阶段的成对矩阵和最佳最差偏好向量的一致性比率。计算结果如下:
Secondly, there is the analysis of consistency ratio. The author has already conducted a consistency test on the judgment matrix of the experimental process in the previous text, and found that the degree of inconsistency in the pairwise comparison matrix is within an acceptable range. Then, calculate the consistency ratio between the pairwise matrix and the best worst preference vector of the AHP model and AUP-BWM model in the second stage using formulas. The calculation results are as follows:
最后是总体偏差度分析,指的是权重比率和其对应的成对比较程度值之间的欧几里得距离,根据公式计算结果如下:
Finally, the overall bias analysis refers to the Euclidean distance between the weight ratio and its corresponding pairwise comparison degree value. According to the formula, the calculation result is as follows:
今天的分享就到这里了。
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让我们相约明天,
祝您今天过得开心快乐!
That's all for today's sharing.
If you have a unique idea about the article, please leave us a message, and let us meet tomorrow.
I wish you a nice day!
参考文献:
[1] 陈乾坤. 基于多准则决策和三角模糊数的云服务选择方法研究及应用 [D]. 重庆: 重庆大学, 2022.
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来源:LearningYard学苑