基于岭回归方法的羊毛衫洗后特征感性评价

doi:10.13475/j.fzxb.20210704507

纺织学报 ›› 2022, Vol. 43 ›› Issue (07): 155-161.doi: 10.13475/j.fzxb.20210704507

基于岭回归方法的羊毛衫洗后特征感性评价

赵馨¹^,², 王彩霞³, 周小皮³, 丁雪梅¹^,²()

1.东华大学服装与艺术设计学院, 上海 200051
2.东华大学现代服装设计与技术教育部重点实验室, 上海 200051
3.松下家电(中国)有限公司, 浙江杭州 310018

收稿日期:2021-07-15 修回日期:2022-04-04 出版日期:2022-07-15 发布日期:2022-07-29
通讯作者: 丁雪梅
作者简介:赵馨(1992—),女,博士生。主要研究方向为洗涤护理技术及理论研究。
基金资助:
中央高校基本科研业务费专项基金项目(2232022G-08)

Study on sensory evaluation of performance of washed wool sweaters based on ridge regression method

ZHAO Xin¹^,², WANG Caixia³, ZHOU Xiaopi³, DING Xuemei¹^,²()

1. College of Fashion and Design, Donghua University, Shanghai 200051, China
2. Key Laboratory of Clothing Design and Technology, Ministry of Education, Donghua University, Shanghai 200051, China
3. Panasonic Appliance (China) Co., Ltd., Hangzhou, Zhejiang 310018, China

Received:2021-07-15 Revised:2022-04-04 Published:2022-07-15 Online:2022-07-29
Contact: DING Xuemei

摘要/Abstract

摘要：

服装产品不同特征的感性评价之间常常存在相互制约的共线性关系,为建立它们之间的量化关系,以17件羊毛衫作为实验对象,通过现场问卷得到30名成年女性对羊毛衫整体印象及9种特征的感性评价数据,使用岭回归方法建立羊毛衫多种特征与整体印象感性评价之间的量化关系。结果显示,羊毛衫9种特征对整体印象感性评价的影响权重排序为:大身平整度、弹性、蓬松度、尺寸比例、领口形态、下摆形态、起毛起球、磨损程度、袖窿接缝平整度,它们之间的岭回归方程拟合精度为0.977。该结果不仅可以帮助产品研发企业精准定位消费者的关注重点,而且可预测消费者对产品功效的感性评价。研究证明了岭回归方法适用于建立具有共线性关系的服装感性评价的量化关系,可广泛应用于不同产品的感性工学研究。

关键词: 岭回归方法, 羊毛衫, 洗后外观, 整体印象, 感性评价, 感性工学

Abstract:

For clothing products, there is usually a collinearity relationship between different sensory properties evaluation. In order to obtain the relationship, 17 wool sweaters were used as the experimental objects, by using on-the-spot questionnaire survey, 9 specific sensory evaluations from 30 women assessors were obtained, which were then analyzed using the ridge regression method, so as to achieve the quantitative relationships among the overall impression and different sensory property evaluations of clothing. The weights of different sensory properties on the overall impression are sorted as flatness, elasticity, bulkiness, size proportion effect, neckline shape, hem shape, fuzz and pilling, damage, armhole joint shape. In addition, the accuracy of regression fitting between the predicted value from ridge regression equation and the actual surveyed value reaches 0.977. It does not only predict the consumers' sensory evaluation of product, but also help the enterprises to accurately focus on the consumers about products. In conclusion, ridge regression is proved to be a good method to study the quantitative relationship of sensory property evaluation with collinear relationship, and it can be widely used in kansei engineering of a variety of garments.

Key words: ridge regression method, wool sweater, washed appearance, overall impression, sensory evaluation, kansei engineering

中图分类号:

TS941.12

赵馨, 王彩霞, 周小皮, 丁雪梅. 基于岭回归方法的羊毛衫洗后特征感性评价[J]. 纺织学报, 2022, 43(07): 155-161.

ZHAO Xin, WANG Caixia, ZHOU Xiaopi, DING Xuemei. Study on sensory evaluation of performance of washed wool sweaters based on ridge regression method[J]. Journal of Textile Research, 2022, 43(07): 155-161.

图/表 11

表1

图1

图2

表2

表3

表4

表5

图3

表6

岭回归拟合精度"

R_Mult	R²	$R A r j 2$	标准差(SE)
0.997	0.994	0.977	0.118

表6

表7

图4

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编号	X₁	X₂	X₃	X₄	X₅	X₆	X₇	X₈	X₉	Y
A-1	4.0	4.1	3.8	3.8	4.1	4.1	3.9	4.0	4.1	4.1
A-3	4.1	4.2	4.1	4.0	4.0	4.2	4.1	4.0	4.0	4.0
A-5	4.2	4.2	4.2	4.1	4.3	4.2	4.3	4.1	4.0	4.3
A-10	4.1	4.3	4.0	3.9	4.1	4.2	4.0	3.9	3.8	4.1
B-1	3.2	3.6	3.3	3.3	3.3	3.3	3.4	3.5	3.5	3.4
B-3	3.3	3.5	3.3	3.1	3.2	3.4	3.4	3.3	3.2	3.3
B-5	2.7	3.1	2.8	3.1	2.6	3.1	3.0	2.8	2.7	2.7
B-10	2.0	2.4	2.2	2.1	2.9	3.0	2.8	1.9	1.8	2.1
C-1	3.5	3.9	3.4	3.5	3.3	3.5	3.4	3.5	3.3	3.5
C-3	3.4	3.6	3.3	3.3	3.1	3.3	3.2	3.4	3.3	3.2
C-5	2.9	3.6	3.0	3.0	2.9	3.2	3.1	3.1	3.2	3.0
C-10	3.1	3.6	3.3	3.1	3.3	3.2	3.1	3.2	3.1	3.2
D-1	1.3	2.1	1.7	1.6	2.0	1.9	1.9	1.7	1.4	1.5

模型参数	非标准化		标准化	共线性统计量
模型参数	系数	标准误差	系数	允差	膨胀因子VIF
(常量)	-0.11	0.24
X₁	0.82	0.29	0.91	0.00	424.30
X₂	0.58	0.22	0.48	0.01	136.85
X₃	-0.94	0.40	-0.84	0.00	525.54
X₄	0.19	0.09	0.18	0.03	30.56
X₅	0.73	0.17	0.61	0.01	79.87
X₆	-0.44	0.30	-0.36	0.00	247.35
X₇	0.35	0.35	0.27	0.00	292.16
X₈	-1.28	0.75	-1.23	0.00	2 141.73
X₉	0.97	0.46	1.02	0.00	959.66

模型参数	非标准化		标准化
模型参数	系数	标准误差	系数
X₁	0.109	0.020	0.120
X₂	0.144	0.036	0.120
X₃	0.118	0.022	0.105
X₄	0.058	0.045	0.053
X₅	0.178	0.044	0.150
X₆	0.129	0.043	0.105
X₇	0.129	0.030	0.098
X₈	0.131	0.025	0.126
X₉	0.119	0.028	0.126
常数	-0.434	0.176	0.000

基于岭回归方法的羊毛衫洗后特征感性评价

Study on sensory evaluation of performance of washed wool sweaters based on ridge regression method

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