VIKOR——AISM联合求解

权重的计算及结果


归一化方法


D-ANP方法的占比


极限超矩阵如下


$$limit W=\begin{array}{c|c|c|c|c|c|c}{M_{16 \times16}} &故事性 &传承性 &寓意性 &情感性 &沟通性 &思考体验 &行为体验 &关联体验 &教育功能 &实用功能 &品质功能 &原创性 &独一性 &美感性 &时尚性 &多样性\\ \hline 故事性 &0.0752 &0.0752 &0.0752 &0.0752 &0.0752 &0.0752 &0.0752 &0.0752 &0.0752 &0.0752 &0.0752 &0.0752 &0.0752 &0.0752 &0.0752 &0.0752\\ \hline 传承性 &0.0644 &0.0644 &0.0644 &0.0644 &0.0644 &0.0644 &0.0644 &0.0644 &0.0644 &0.0644 &0.0644 &0.0644 &0.0644 &0.0644 &0.0644 &0.0644\\ \hline 寓意性 &0.0578 &0.0578 &0.0578 &0.0578 &0.0578 &0.0578 &0.0578 &0.0578 &0.0578 &0.0578 &0.0578 &0.0578 &0.0578 &0.0578 &0.0578 &0.0578\\ \hline 情感性 &0.0615 &0.0615 &0.0615 &0.0615 &0.0615 &0.0615 &0.0615 &0.0615 &0.0615 &0.0615 &0.0615 &0.0615 &0.0615 &0.0615 &0.0615 &0.0615\\ \hline 沟通性 &0.0731 &0.0731 &0.0731 &0.0731 &0.0731 &0.0731 &0.0731 &0.0731 &0.0731 &0.0731 &0.0731 &0.0731 &0.0731 &0.0731 &0.0731 &0.0731\\ \hline 思考体验 &0.0555 &0.0555 &0.0555 &0.0555 &0.0555 &0.0555 &0.0555 &0.0555 &0.0555 &0.0555 &0.0555 &0.0555 &0.0555 &0.0555 &0.0555 &0.0555\\ \hline 行为体验 &0.0706 &0.0706 &0.0706 &0.0706 &0.0706 &0.0706 &0.0706 &0.0706 &0.0706 &0.0706 &0.0706 &0.0706 &0.0706 &0.0706 &0.0706 &0.0706\\ \hline 关联体验 &0.0597 &0.0597 &0.0597 &0.0597 &0.0597 &0.0597 &0.0597 &0.0597 &0.0597 &0.0597 &0.0597 &0.0597 &0.0597 &0.0597 &0.0597 &0.0597\\ \hline 教育功能 &0.0679 &0.0679 &0.0679 &0.0679 &0.0679 &0.0679 &0.0679 &0.0679 &0.0679 &0.0679 &0.0679 &0.0679 &0.0679 &0.0679 &0.0679 &0.0679\\ \hline 实用功能 &0.0324 &0.0324 &0.0324 &0.0324 &0.0324 &0.0324 &0.0324 &0.0324 &0.0324 &0.0324 &0.0324 &0.0324 &0.0324 &0.0324 &0.0324 &0.0324\\ \hline 品质功能 &0.0578 &0.0578 &0.0578 &0.0578 &0.0578 &0.0578 &0.0578 &0.0578 &0.0578 &0.0578 &0.0578 &0.0578 &0.0578 &0.0578 &0.0578 &0.0578\\ \hline 原创性 &0.065 &0.065 &0.065 &0.065 &0.065 &0.065 &0.065 &0.065 &0.065 &0.065 &0.065 &0.065 &0.065 &0.065 &0.065 &0.065\\ \hline 独一性 &0.0653 &0.0653 &0.0653 &0.0653 &0.0653 &0.0653 &0.0653 &0.0653 &0.0653 &0.0653 &0.0653 &0.0653 &0.0653 &0.0653 &0.0653 &0.0653\\ \hline 美感性 &0.0609 &0.0609 &0.0609 &0.0609 &0.0609 &0.0609 &0.0609 &0.0609 &0.0609 &0.0609 &0.0609 &0.0609 &0.0609 &0.0609 &0.0609 &0.0609\\ \hline 时尚性 &0.0714 &0.0714 &0.0714 &0.0714 &0.0714 &0.0714 &0.0714 &0.0714 &0.0714 &0.0714 &0.0714 &0.0714 &0.0714 &0.0714 &0.0714 &0.0714\\ \hline 多样性 &0.0615 &0.0615 &0.0615 &0.0615 &0.0615 &0.0615 &0.0615 &0.0615 &0.0615 &0.0615 &0.0615 &0.0615 &0.0615 &0.0615 &0.0615 &0.0615\\ \hline \end{array} $$

指标要素权重如下


$$\omega=\begin{array}{c|c|c|c|c|c|c}{M_{16 \times1}} &D-ANP权重\\ \hline 故事性 &0.07521\\ \hline 传承性 &0.06439\\ \hline 寓意性 &0.0578\\ \hline 情感性 &0.06154\\ \hline 沟通性 &0.07311\\ \hline 思考体验 &0.05554\\ \hline 行为体验 &0.07062\\ \hline 关联体验 &0.05969\\ \hline 教育功能 &0.0679\\ \hline 实用功能 &0.03237\\ \hline 品质功能 &0.05784\\ \hline 原创性 &0.065\\ \hline 独一性 &0.06529\\ \hline 美感性 &0.06087\\ \hline 时尚性 &0.07136\\ \hline 多样性 &0.06146\\ \hline \end{array} $$$$\omega=\begin{array}{c|c|c|c|c|c|c}{M_{1 \times16}} &故事性 &传承性 &寓意性 &情感性 &沟通性 &思考体验 &行为体验 &关联体验 &教育功能 &实用功能 &品质功能 &原创性 &独一性 &美感性 &时尚性 &多样性\\ \hline D-ANP权重 &0.07521 &0.06439 &0.0578 &0.06154 &0.07311 &0.05554 &0.07062 &0.05969 &0.0679 &0.03237 &0.05784 &0.065 &0.06529 &0.06087 &0.07136 &0.06146\\ \hline \end{array} $$

原始矩阵


$$ \begin{array}{c|c|c|c|c|c|c}{M_{8 \times16}} &C1 &C2 &C3 &C4 &C5 &E1 &E2 &E3 &F1 &F2 &F3 &U1 &U2 &D1 &D2 &D3\\ \hline P1 &0.779 &0.782 &0.701 &0.724 &0.712 &0.756 &0.639 &0.713 &0.838 &0.758 &0.699 &0.71 &0.702 &0.705 &0.754 &0.712\\ \hline P2 &0.791 &0.751 &0.709 &0.768 &0.732 &0.762 &0.653 &0.702 &0.73 &0.716 &0.595 &0.694 &0.641 &0.701 &0.667 &0.702\\ \hline P3 &0.736 &0.775 &0.812 &0.728 &0.762 &0.633 &0.475 &0.582 &0.72 &0.701 &0.645 &0.714 &0.706 &0.693 &0.634 &0.674\\ \hline P4 &0.647 &0.737 &0.722 &0.715 &0.792 &0.78 &0.564 &0.757 &0.768 &0.72 &0.699 &0.75 &0.706 &0.779 &0.712 &0.706\\ \hline P5 &0.733 &0.806 &0.748 &0.733 &0.696 &0.682 &0.509 &0.689 &0.709 &0.715 &0.554 &0.696 &0.663 &0.671 &0.709 &0.663\\ \hline P6 &0.734 &0.78 &0.747 &0.714 &0.768 &0.854 &0.758 &0.712 &0.719 &0.706 &0.732 &0.722 &0.729 &0.765 &0.709 &0.765\\ \hline P7 &0.656 &0.73 &0.74 &0.628 &0.73 &0.692 &0.545 &0.59 &0.595 &0.758 &0.631 &0.706 &0.692 &0.629 &0.628 &0.605\\ \hline P8 &0.714 &0.733 &0.721 &0.746 &0.65 &0.824 &0.703 &0.632 &0.697 &0.714 &0.761 &0.753 &0.592 &0.842 &0.743 &0.755\\ \hline \end{array} $$

采用的是极差法进行归一化


  正向指标的公式为:$ n_{ij} = \frac{{o_{ij}-min(o_{j})}}{{max(o_{j})-min(o_{j})}} $

  负向指标的公式为:$ n_{ij} = \frac{{o_{ij}-min(o_{j})}}{{max(o_{j})-min(o_{j})}} $

归一化矩阵如下


$$ \begin{array}{c|c|c|c|c|c|c}{M_{8 \times16}} &C1 &C2 &C3 &C4 &C5 &E1 &E2 &E3 &F1 &F2 &F3 &U1 &U2 &D1 &D2 &D3\\ \hline P1 &0.917 &0.684 &0 &0.686 &0.437 &0.557 &0.58 &0.749 &1 &1 &0.7 &0.271 &0.803 &0.357 &1 &0.669\\ \hline P2 &1 &0.276 &0.072 &1 &0.577 &0.584 &0.629 &0.686 &0.556 &0.263 &0.198 &0 &0.358 &0.338 &0.31 &0.606\\ \hline P3 &0.618 &0.592 &1 &0.714 &0.789 &0 &0 &0 &0.514 &0 &0.44 &0.339 &0.832 &0.3 &0.048 &0.431\\ \hline P4 &0 &0.092 &0.189 &0.621 &1 &0.665 &0.314 &1 &0.712 &0.333 &0.7 &0.949 &0.832 &0.704 &0.667 &0.631\\ \hline P5 &0.597 &1 &0.423 &0.75 &0.324 &0.222 &0.12 &0.611 &0.469 &0.246 &0 &0.034 &0.518 &0.197 &0.643 &0.363\\ \hline P6 &0.604 &0.658 &0.414 &0.614 &0.831 &1 &1 &0.743 &0.51 &0.088 &0.86 &0.475 &1 &0.638 &0.643 &1\\ \hline P7 &0.063 &0 &0.351 &0 &0.563 &0.267 &0.247 &0.046 &0 &1 &0.372 &0.203 &0.73 &0 &0 &0\\ \hline P8 &0.465 &0.039 &0.18 &0.843 &0 &0.864 &0.806 &0.286 &0.42 &0.228 &1 &1 &0 &1 &0.913 &0.938\\ \hline \end{array} $$

ViKOR中带权值的公式如下


  期望值计算公式为:$ S_i = \sum_\limits{j=1}^m{ \omega_{j} \left(\frac{Zone_j^+ -n_{ij}}{Zone_j^+ -Zone_j^-} \right)} \quad \quad $

  遗憾值计算公式为:$ R_i = \max_\limits{j=1} { \left( \omega_{j} (\frac{n_{ij}-0}{Zone_j^+ -Zone_j^-} )\right)} \quad \quad $

正极值点构成
$$ \begin{array}{c|c|c|c|c|c|c}{M_{1 \times16}} &C1 &C2 &C3 &C4 &C5 &E1 &E2 &E3 &F1 &F2 &F3 &U1 &U2 &D1 &D2 &D3\\ \hline \mathbf{Zone^+} &1 &1 &1 &1 &1 &1 &1 &1 &1 &1 &1 &1 &1 &1 &1 &1\\ \hline \end{array} $$
负极值点构成
$$ \begin{array}{c|c|c|c|c|c|c}{M_{1 \times16}} &C1 &C2 &C3 &C4 &C5 &E1 &E2 &E3 &F1 &F2 &F3 &U1 &U2 &D1 &D2 &D3\\ \hline \mathbf{Zone^-} &0 &0 &0 &0 &0 &0 &0 &0 &0 &0 &0 &0 &0 &0 &0 &0\\ \hline \end{array} $$
CRITIC权重如下
$$ \begin{array}{c|c|c|c|c|c|c}{M_{2 \times16}} &C1 &C2 &C3 &C4 &C5 &E1 &E2 &E3 &F1 &F2 &F3 &U1 &U2 &D1 &D2 &D3\\ \hline CRITIC方法所得权重 &0.06366 &0.06533 &0.05803 &0.05397 &0.05886 &0.06259 &0.06444 &0.06706 &0.05199 &0.07206 &0.06312 &0.07076 &0.06039 &0.05912 &0.06912 &0.05949\\ \hline 权重大小顺序 &7 &5 &14 &15 &13 &9 &6 &4 &16 &1 &8 &2 &10 &12 &3 &11\\ \hline \end{array} $$
D-ANP权重如下
$$\omega=\begin{array}{c|c|c|c|c|c|c}{M_{1 \times16}} &故事性 &传承性 &寓意性 &情感性 &沟通性 &思考体验 &行为体验 &关联体验 &教育功能 &实用功能 &品质功能 &原创性 &独一性 &美感性 &时尚性 &多样性\\ \hline 权重 &0.07521 &0.06439 &0.0578 &0.06154 &0.07311 &0.05554 &0.07062 &0.05969 &0.0679 &0.03237 &0.05784 &0.065 &0.06529 &0.06087 &0.07136 &0.06146\\ \hline \end{array} $$
两者调和权重如下
$$\omega=\begin{array}{c|c|c|c|c|c|c}{M_{1 \times16}} &故事性 &传承性 &寓意性 &情感性 &沟通性 &思考体验 &行为体验 &关联体验 &教育功能 &实用功能 &品质功能 &原创性 &独一性 &美感性 &时尚性 &多样性\\ \hline 权重 &0.06597 &0.06514 &0.05799 &0.05549 &0.06171 &0.06118 &0.06567 &0.06559 &0.05517 &0.06412 &0.06206 &0.06961 &0.06137 &0.05947 &0.06957 &0.05989\\ \hline \end{array} $$

代入权重值等即得(S R)两列矩阵,两列都为负向指标


$$ \begin{array}{c|c|c|c|c|c|c}{M_{8 \times2}} &期望值 &遗憾值\\ \hline P1 &0.34728943 &0.05798643\\ \hline P2 &0.539497469 &0.069608982\\ \hline P3 &0.597369509 &0.066322927\\ \hline P4 &0.412918941 &0.065966692\\ \hline P5 &0.594322131 &0.067316672\\ \hline P6 &0.308492986 &0.058558287\\ \hline P7 &0.75939233 &0.069569435\\ \hline P8 &0.436743471 &0.062632205\\ \hline \end{array} $$

妥协解分析


妥协解公式


公式
$$ Q_i = \left( 1-k \right) \left(\frac{S_i - Min(S_i)}{Max(S_i) -Min(S_i)} \right) + k\left(\frac{R_i - Min(R_i)}{Max(R_i) -Min(R_i)} \right) $$

敏感性分析,排序聚类分析


$$ Q_i = \left( 1-k \right) a_i + kb_i \quad \quad $$

对于 $x,y$样本

$$ \begin{cases} \left( 1-k \right) a_x + kb_x \\ \left( 1-k \right) a_y + kb_y \end{cases} $$

以上问题就变成了求两条线段是否在$[0,1]$值域内有相交的问题,此题属于初中的知识范畴,不再详细描述。

$$ \left( 1-k \right) a_x + kb_x =\left( 1-k \right) a_y + kb_y $$

$$ a_x-k a_x + kb_x =a_y-k a_y + kb_y $$

$$ a_x- a_y=-k a_y + kb_y +k a_x - kb_x $$

$$ a_x- a_y=(- a_y + b_y + a_x - b_x)k $$

$$ k =\frac{a_x- a_y}{( a_x- a_y + b_y - b_x)} $$

基础矩阵如下:


$$Base=\begin{array}{c|c|c|c|c|c|c}{M_{8 \times2}} &a_i &b_i\\ \hline P1 &0.086 &0\\ \hline P2 &0.5123 &1\\ \hline P3 &0.6407 &0.7173\\ \hline P4 &0.2316 &0.6866\\ \hline P5 &0.6339 &0.8028\\ \hline P6 &0 &0.0492\\ \hline P7 &1 &0.9966\\ \hline P8 &0.2844 &0.3997\\ \hline \end{array} $$

拐点k值分析


$$Qk_{matrix}=\begin{array}{c|c|c|c|c|c|c}{M_{8 \times8}} &k=0 &k=0.073 &k=0.156 &k=0.312 &k=0.381 &k=0.636 &k=0.993 &k=1\\ \hline P1 &0.086 &0.08 &0.073 &0.059 &0.053 &0.031 &0.001 &0\\ \hline P2 &0.512 &0.548 &0.588 &0.665 &0.698 &0.823 &0.997 &1\\ \hline P3 &0.641 &0.646 &0.653 &0.665 &0.67 &0.689 &0.717 &0.717\\ \hline P4 &0.232 &0.265 &0.302 &0.374 &0.405 &0.521 &0.683 &0.687\\ \hline P5 &0.634 &0.646 &0.66 &0.687 &0.698 &0.741 &0.802 &0.803\\ \hline P6 &0 &0.004 &0.008 &0.015 &0.019 &0.031 &0.049 &0.049\\ \hline P7 &1 &1 &0.999 &0.999 &0.999 &0.998 &0.997 &0.997\\ \hline P8 &0.284 &0.293 &0.302 &0.32 &0.328 &0.358 &0.399 &0.4\\ \hline \end{array} $$

排序分析


上述是负向指标,数值越小越好,每一列数值最小的排第一。因此排序情况如下:

$$Q_{rank}=\begin{array}{c|c|c|c|c|c|c}{M_{8 \times8}} &k=0 &k=0.073 &k=0.156 &k=0.312 &k=0.381 &k=0.636 &k=0.993 &k=1\\ \hline P1 &2 &2 &2 &2 &2 &1 &1 &1\\ \hline P2 &5 &5 &5 &5 &6 &7 &7 &8\\ \hline P3 &7 &6 &6 &5 &5 &5 &5 &5\\ \hline P4 &3 &3 &3 &4 &4 &4 &4 &4\\ \hline P5 &6 &6 &7 &7 &6 &6 &6 &6\\ \hline P6 &1 &1 &1 &1 &1 &1 &2 &2\\ \hline P7 &8 &8 &8 &8 &8 &8 &7 &7\\ \hline P8 &4 &4 &3 &3 &3 &3 &3 &3\\ \hline \end{array} $$


聚类特征


序号 聚类特征-对应k值区段 Q值排序
10<$k$< 0.07325$P6 \succ P1 \succ P4 \succ P8 \succ P2 \succ P5 \succ P3 \succ P7$
20.0733<$k$< 0.15553$P6 \succ P1 \succ P4 \succ P8 \succ P2 \succ P3 \succ P5 \succ P7$
30.1555<$k$< 0.31222$P6 \succ P1 \succ P8 \succ P4 \succ P2 \succ P3 \succ P5 \succ P7$
40.3122<$k$< 0.38137$P6 \succ P1 \succ P8 \succ P4 \succ P3 \succ P2 \succ P5 \succ P7$
50.3814<$k$< 0.6362$P6 \succ P1 \succ P8 \succ P4 \succ P3 \succ P5 \succ P2 \succ P7$
60.6362<$k$< 0.99307$P1 \succ P6 \succ P8 \succ P4 \succ P3 \succ P5 \succ P2 \succ P7$
70.9931<$k$< 1$P1 \succ P6 \succ P8 \succ P4 \succ P3 \succ P5 \succ P7 \succ P2$

区段截取方式Q排序——k值区段截取分析


不多解释了,先点击下面的按钮进去看看就知道了

区段截取方式Q排序——夹逼方式


以0->min max<- 1方式夹逼显示。