This study aims to create a classification system enabling users of 3D virtualization software to intuitively perceive the drapability of fabrics.,1,001 fabrics were used, and thickness, bending property, and tensile strength were identified as main mechanical properties influencing drapability; they have been set as independent variables in the model established to predict drape coefficient.,A system to classify fabrics into eight groups by drapability was suggested by a cluster analysis, and a multinomial logistic regression analysis was used to set a model that allows users to predict which group a fabric belongs to from its mechanical properties.,This paper provided basic materials for the construction of a virtual clothing simulation system, which is believed to contribute to cost and time savings in decision-making by reducing the number of trials and errors required by the conventional approach.

中文翻译：

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用于 3D 服装虚拟化的织物悬垂性预测和分类

本研究旨在创建一个分类系统，使 3D 虚拟化软件的用户能够直观地感知织物的悬垂性。使用了 1,001 种织物，并将厚度、弯曲性能和拉伸强度确定为影响悬垂性的主要机械性能；在所建立的模型中将它们设置为自变量以预测悬垂系数。,通过聚类分析建议将织物按悬垂性分为八组的系统，并使用多项逻辑回归分析设置模型，允许用户从织物的力学性能预测织物属于哪一组。,本文为构建虚拟服装模拟系统提供了基础材料,