周四学习卡9——累积前景理论+VIKOR+毕达哥拉斯由于模糊数

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小编将继续给大家分享《基于累积前景理论和ＶＩＫＯＲ的毕达哥拉斯犹豫模糊风险型多属性决策方法》，本期将在excel中S1状态为例计算其各属性值的价值前景值，一起来看看吧！

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Xiaobian will continue to share with you the "Pythagorean hesitant fuzzy risk multi-attribute decision-making method based on cumulative prospect theory and VIKOR", this issue will calculate the value prospect value of each attribute value in excel S1 state as an example, let's take a look!

首先输入已经标准化处理后各状态下各方案的属性值。

First enter the attribute values for each scenario in each state after the normalization processing.

接着计算各属性值的得分函数。计算公式如公式栏所示。

It then calculates the score function for each attribute value. The calculation formula is shown in the formula bar.

然后计算各属性值的精确函数，并通过扽分函数和精确函数比较各属性值与参考点的大小。精确函数计算公式如公式栏所示。

The exact function of each attribute value is then calculated, and the size of the attribute value and the reference point are compared by the split function and the exact function. The exact function calculation formula is shown in the formula bar.

下一步计算各属性值相对于参考点的价值函数。计算价值函数之前需要计算出各属性值的不确定度，根据不确定度公式，可以得出不确定度的值即为1-精确函数的平方根。

The next step is to calculate the value function of each attribute value relative to the reference point. Before calculating the value function, the uncertainty of each attribute value needs to be calculated, and according to the uncertainty formula, it can be concluded that the value of the uncertainty is the square root of the 1-exact function.

再计算出各属性值与参考点的距离。

The distance between each attribute value and the reference point is then calculated

最后得到各属性值在各状态下的价值函数：

Finally, the value function of each attribute value in each state is obtained:

本期的分享就到这里，如果您对今天的文章有独特的想法，欢迎给我们留言，让我们相约明天，祝您今天过得开心快乐！

The sharing of this issue is here, if you have a unique idea for today's article, welcome to leave us a message, let us meet tomorrow, I wish you a happy and happy day!

翻译参考来源：Google翻译。

内容参考来源

[1]常娟,杜迎雪,刘卫锋.基于累积前景理论和VIKOR的毕达哥拉斯犹豫模糊风险型多属性决策方法.

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