小源笔记51精读《基于模糊评价信息的多属性决策方法研究》2.3

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今天小编将从思维导图、精读内容、知识补充三个板块为大家带来博士论文《基于模糊评价信息的多属性决策方法研究》2.3 基于 q 阶双犹豫模糊信息的多属性决策方法，接下来我们开始今天的学习吧！

Today's small edition will bring you the doctoral dissertation Research on Multi attribute Decision Making Methods Based on Fuzzy Evaluation Information 2.3 Multi attribute Decision Making Methods Based on Q-order Double hesitant Fuzzy Information from three parts: mind mapping, intensive reading and knowledge supplement. Let's start today's study!

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思维导图

下图是本节内容的思维导图，主要是对提出的 q 阶双犹豫模糊信息集成方法应用于多属性群决策问题中，此类问题的解决步骤进行描述。

The following figure is the mind map of this section, mainly describing the solving steps of the proposed q order double hesitation fuzzy information integration method applied to multi-attribute group decision-making problems.

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精读内容

2.3基于q阶双犹豫模糊信息的多属性决策方法

一个典型的 q 阶双犹豫模糊信息环境下的多属性群决策问题可以描述如下：

A typical multi-attribute group decision making problem under q order double hesitation fuzzy information environment can be described as follows:

步骤如下：

The steps are as follows:

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知识补充

在本节内容中步骤二提到的汉明距离是什么意思呢？

What does the Hanming Distance mentioned in step 2 of this section mean?

汉明距离：汉明距离是使用在数据传输差错控制编码里面的，汉明距离是一个概念，它表示两个（相同长度）字符串对应位置的不同字符的数量，我们以d（x,y）表示两个字x,y之间的汉明距离。对两个字符串进行异或运算，并统计结果为1的个数，那么这个数就是汉明距离。

Hamming distance: Hamming distance is used in data transmission error control coding. Hamming distance is a concept, which represents the number of different characters at the corresponding positions of two (same length) strings. We use d (x, y) to represent the Hamming distance between two words x, y. Perform XOR operation on two strings, and count the number of 1, then this number is the Hamming distance.

汉明距离是以理查德·卫斯里·汉明的名字命名的。在信息论中，两个等长字符串之间的汉明距离是两个字符串对应位置的不同字符的个数。换句话说，它就是将一个字符串变换成另外一个字符串所需要替换的字符个数。例如：

Hamming Distance is named after Richard Wesley Hamming. In information theory, the Hamming distance between two equal length strings is the number of different characters at the corresponding positions of two strings. In other words, it is the number of characters that need to be replaced to convert one string to another. For example:

1011101 与 1001001 之间的汉明距离是 2。

2143896 与 2233796 之间的汉明距离是 3。

"toned" 与 "roses" 之间的汉明距离是 3。

The Hamming distance between 1011101 and 1001001 is 2.

The Hanming distance between 2143896 and 2233796 is 3.

The Hamming distance between "toned" and "rose" is 3.

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参考资料：谷歌翻译

参考文献：[1]赵红梅. 基于模糊评价信息的多属性决策方法研究 [D]. 北京交通大学, 2021.

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