Journal of Textile Research ›› 2019, Vol. 40 ›› Issue (05): 124-130.doi: 10.13475/j.fzxb.20180607907

• Apparel Engineering • Previous Articles     Next Articles

Recognition of special template based on improved analytic hierarchy process

ZHOU Jie1(), LI Jian1, MA Qiurui1, HUANG Xiaojie2   

  1. 1. School of Apparel and Art Design, Xi'an Polytechnic University, Xi'an, Shaanxi 710048, China
    2. College of Information & Business, Zhongyuan University of Technology, Zhengzhou, Henan 450007, China
  • Received:2018-06-25 Revised:2019-01-29 Online:2019-05-15 Published:2019-05-21

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Abstract:

Aiming at the shortcomings of conventional analytic hierarchy process, an improved analytic hierarchy process based on combination factor analysis and cluster analysis was proposed and applied to special model recognition. Firstly, factor analysis was applied to determine the influencing factors and weight coefficients of each level of indicators. Then, K-means cluster analysis was applied to collect the special samples into three typical models such as hip, chest and abdomen. Finally, the analytic hierarchy process was applied to determine the weight of each indicator, and a special model-level hierarchical structure model including six secondary indicators, 13 third-level indicators and three four-level indicators was constructed. Three samples were randomly selected for empirical research. The five principal components extracted from the factor analysis were used as clustering indicators, and the K-means method was used for clustering. The specific sample-level hierarchical structure model was applied to identify the sample to be tested and hip and chest. The results show that the method can effectively characterize the variation of the special model and identify the model category.

Key words: special template, factor analysis, cluster analysis, improved analytic hierarchy process

CLC Number: 

  • TS941.712

Fig.1

Typical index of special body correction model"

Fig.2

Flow chart of improved analytic hierarchy process"

Tab.1

Principal component factor analysis"

成分 初始特征值 因子旋转后
特征根 方差贡
献率/%		 累计贡
献率/%		 特征根 方差贡
献率/%		 累计贡
献率/%
1 3.232 24.865 24.865 2.740 21.076 21.076
2 2.281 17.545 42.410 2.311 17.777 38.853
3 1.882 14.473 56.884 2.189 16.840 55.693
4 1.139 8.764 65.648 1.274 9.800 65.493
5 1.027 7.902 73.550 1.047 8.057 73.550

Tab.2

Rotational load matrix"

评价
指标		 成分
1 2 3 4 5
C1 -0.004 -0.117 0.898 0.019 -0.053
C2 0.826 -0.133 0.075 -0.010 0.124
C3 0.557 0.241 0.017 -0.267 0.116
C4 0.095 0.537 -0.296 -0.062 -0.531
C5 0.734 0.202 -0.003 0.489 -0.190
C6 0.793 0.083 -0.148 -0.132 0.011
C7 -0.035 -0.087 0.716 0.123 0.141
C8 0.068 0.952 -0.035 0.032 0.102
C9 0.742 0.045 -0.069 0.501 -0.194
C10 -0.031 0.090 0.854 -0.063 -0.114
C11 0.073 0.253 -0.106 0.055 0.765
C12 -0.061 0.007 0.081 0.817 0.126
C13 -0.075 -0.947 0.007 -0.024 -0.128

Tab.3

Variance analysis table"

聚类数 变量 类间
均方		 误差
均方		 F值 Sig.
3 因子1 35.603 0.810 43.960 0.000
因子2 96.744 0.474 204.132 0.000
因子3 65.601 0.645 101.699 0.000
因子4 6.849 0.968 7.077 0.001
因子5 8.209 0.960 8.547 0.000
4 因子1 16.043 0.876 18.321 0.000
因子2 45.592 0.631 72.200 0.000
因子3 38.712 0.688 56.241 0.000
因子4 60.413 0.509 118.692 0.000
因子5 37.000 0.702 52.671 0.000
5 因子1 35.831 0.615 58.250 0.000
因子2 50.323 0.455 110.602 0.000
因子3 40.349 0.565 71.390 0.000
因子4 49.733 0.462 107.758 0.000
因子5 15.047 0.845 17.811 0.000

Tab.4

Statistical table of average corrections for main parts of three specialty samplesmm"

样板类型 C1 C2 C3 C4 C5 C6 C7 C8 C9 C10 C11 C12 C13
D1 7.72 8.95 -2.32 -7.94 8.96 11.56 1.27 -2.43 7.41 -1.39 -1.85 0.17 2.00
D2 -0.85 -6.17 -8.75 -12.13 -9.95 -3.68 -2.42 -13.35 -1.95 -10.43 -9.37 -0.30 13.02
D3 -32.73 -5.28 -12.13 -2.09 3.55 4.60 -6.51 -0.78 4.68 -15.28 -2.28 0.61 0.76

Fig.3

Hierarchical structure of special template recognition model"

Tab.5

Judgment matrix scale and its meaning of aij"

标度(aij ) 含义
1 元素i与元素j同等重要
3 元素i比元素j稍重要
5 元素i比元素j颇重要
7 元素i比元素j极重要
9 元素i比元素j极端重要
2/4/6/8 分别介于以上标度的中间值
倒数 若元素j与元素i的关系是: aji=1/aij

Tab.6

Special sample recognition judgment matrix B-A"

类别 B1 B2 B3 B4 B5 权重
B1 1 7/6 21/17 7/3 21/8 0.290 0
B2 6/7 1 15/14 19/11 19/9 0.238 8
B3 17/21 14/15 1 19/11 2 0.227 2
B4 3/7 11/19 11/19 1 5/4 0.133 1
B5 8/21 9/19 1/2 4/5 1 0.110 9

Tab.7

Profile factor judgment matrix C-B1"

类别1 C2 C3 C5 C6 C9 权重
C2 1 7 5 3 4 0.484 5
C3 1/7 1 1/3 1/5 1/4 0.043 4
C5 1/5 3 1 1/3 1/2 0.089 8
C6 1/3 5 3 1 3 0.249 4
C9 1/4 4 2 1/3 1 0.132 9

Tab.8

Difference between the size of the main part of the sample to be tested and the special sample mm"

部位
指标		 修正量 样本a与3类特体样板差值 样本b与3类特体样板差值 样本c与3类特体样板差值
样本a 样本b 样本c Δa1 Δa2 Δa3 Δb1 Δb2 Δb3 Δc1 Δc2 Δc3
C1 30 70 -70 22.28 30.85 62.73 62.28 70.85 102.73 -77.72 -69.15 -37.27
C2 -30 60 -40 -38.95 -23.83 -24.72 51.05 66.17 65.28 -48.95 -33.83 -34.72
C3 -15 0 -15 -12.68 -6.25 -9.38 2.32 8.75 5.62 -12.68 -6.25 -9.38
C4 -12 -20 -15 -4.06 0.13 -9.91 -12.06 -7.87 -17.91 -7.06 -2.87 -12.91
C5 8 45 -60 -0.96 17.95 4.45 36.04 54.95 41.45 -68.96 -50.05 -63.55
C6 -15 10 -28 -26.56 -11.32 -19.6 -1.56 13.68 5.4 -39.56 -24.32 -32.6
C7 -10 15 -15 -11.27 -7.58 -3.49 13.73 17.42 21.51 -16.27 -12.58 -8.49
C8 0 0 -10 2.43 13.35 0.78 2.43 13.35 0.78 -7.57 3.35 -9.22
C9 3 45 -40 -4.41 4.95 -1.68 37.59 46.95 40.32 -47.41 -38.05 -44.68
C10 10 35 -35 11.39 20.43 25.82 36.39 45.43 50.82 -33.61 -24.57 -19.18
C11 0 5 0 1.85 9.37 2.28 6.85 14.37 7.28 1.85 9.37 2.28
C12 10 0 0 9.83 10.3 9.39 -0.17 0.3 -0.61 -0.17 0.3 -0.61
C13 0 0 10 -2 -13.02 -0.76 -2 -13.02 -0.76 8 -3.02 9.24

Tab.9

Index layer total weight calculation and sorting"

二级指标 三级指标 四级指标单
排序权重
WD		 总排序权重
W=WB×
WC×WD
指标 权重
WB		 指标 单排序
权重WC
B1 0.290 0 C2 0.484 5 [0.700 7,0.097 2,
0.202 1]		 W1=
0.293 7,
W2=
0.436 4,
W3=
0.269 9
C3 0.043 4 [0.637 0, 0.104 7,
0.258 3]
C5 0.089 8 [0.058 1, 0.735 2,
0.206 7]
C6 0.249 4 [0.637 0, 0.104 7,
0.258 3]
C9 0.132 9 [0.296 9, 0.617 5,
0.085 6]
B2 0.238 8 C8 0.750 0 [0.218 5, 0.714 7,
0.066 8]
C13 0.250 0 [0.148 8, 0.785 4,
0.065 8]
B3 0.227 2 C1 0.637 0 [0.081 0, 0.188 4,
0.730 6]
C7 0.104 7 [0.637 0, 0.258 3,
0.104 7]
C10 0.258 3 [0.071 9, 0.279 0,
0.649 1]
B4 0.133 1 C12 1.000 [0.280 8, 0.584 2,
0.135 0]
B5 0.110 9 C4 0.166 7 [0.227 1, 0.051 0,
0.721 9]
C11 0.833 3 [0.081 0, 0.730 6,
0.188 4]

Fig.4

Radar chart of special template category"

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