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上期小编已经给大家介绍了三角模糊数中效益型指标通过MATLAB实现标准化，本期内容将带大家学习成本型指标标准化在MATLAB中的实现。

成本型指标的代码实现与效益型基本一样，仅转化规则不同。

成本型指标的转化规则为：

【实例分析】

案例背景：某风险投资企业致力于寻求合适的设备风险投资项目,现有4个备选方案,考虑的准则主要有预期收益C1、成长性C2、社会效益C3 、 环境影响C4。第四个准则为成本型准则，其他均为效益型准则，其决策矩阵见下表。

上一期已经标记好成本型指标开始的列以及矩阵的尺寸，本期不再重复。直接把它们每个隶属度（成本型）单独提出来：

由于是(end+1)的向量形式，因此再把它们编码成矩阵：

得到矩阵结果：

通过公式编写效益型指标标准化代码：

之后将行向量转化为矩阵：

将三角模糊数的各个隶属度进行合并，生成cell元胞数组：

将行向量形式的元胞数组变为cell矩阵形式：

得到4×1的元胞数组即为效益型指标标准化后的结果：

最后将效益性指标矩阵与成本型指标矩阵进行合并，得到标准化后的矩阵：

【英文学习】

The conversion rules for cost indicators are:

Case Analysis:

Case background: A venture capital company is committed to seeking suitable equipment venture capital projects. There are currently 4 alternatives. The main consideration criteria are expected return C1, growth C2, social benefit C3, and environmental impact C4. The fourth criterion is a cost criterion, and the others are benefit criterion. The decision matrix is shown in the table below.

In the previous issue, the starting column of the cost indicator and the size of the matrix have been marked, so I won’t repeat it in this issue. Directly put forward each of them separately (cost type):

Since it is a vector form of (end+1), encode them into a matrix:

Get the matrix result:

Compile the standardization code of the benefit index through the formula:

Then convert the row vector to a matrix:

Combine the membership degrees of the triangular fuzzy numbers to generate a cell array:

Change the cell array in row vector form to cell matrix form:

Obtaining a 4×1 cell array is the normalized result of the benefit index:

Finally, the efficiency index matrix and the cost index matrix are combined to obtain a standardized matrix:

翻译：谷歌翻译

参考资料：

[1]周师兄学习文档

[2]江文奇.一种三角模糊数型多准则决策的拓展VIKOR方法

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