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BASIC STUDY ON TREND PREDICTION FOR STYLE DESIGN

机译:风格设计趋势预测的基础研究

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摘要

With diversification of consumer taste, appearance shape together with functionality contributes to the appeal of a product vastly. Concept design and industrial design therefore serve as an important process in product development. These designs are difficult to perform based on theoretical backing, since appearance shape design is a creative activity which depends on a designer's aesthetic sense strongly. When embodying a product shape, naturally design is determined not only by a designer's sensitivity but by use and function of a product as well. It is also important to investigate designs desired by consumers, and reflect all of this in the product design. The ability to predict consumer taste trends therefore greatly aids product design. In this research, the prototype models of a product in trend every year were made by multiplying weights according to the number of a product sold in the past to calculate that the rate of exaggeration of prototype models of each year to all whole prototype models. The straight extrapolation of the Spline method was applied to the exaggeration vector, and the technique of predicting shapes preferred by consumers in the near future using that method was proposed. Moreover the eigenspace method was applied to similar product shapes to propose the technique of grasping the features of shape for every year by computing the eigenvalue and eigenvector of the coordinates of the points of the shapes as well as the technique of predicting shapes which consumers will prefer in the near future by using the Linear function of Moving Least Square method.
机译:随着消费者口味的多样化,外观形状和功能性极大地提高了产品的吸引力。因此,概念设计和工业设计是产品开发中的重要过程。由于外观形状设计是一项创造性的活动,因此强烈依赖于设计师的审美意识,因此这些设计很难在理论基础上进行。当体现产品形状时,自然的设计不仅取决于设计师的敏感度,还取决于产品的用途和功能。调查消费者所需的设计并将其全部反映到产品设计中也很重要。因此,预测消费者口味趋势的能力极大地有助于产品设计。在这项研究中,通过根据过去售出产品的数量乘以权重,得出每年趋势产品的原型模型,以计算出每年原型模型对所有整个原型模型的夸大率。将样条线方法的直接外推应用于夸张矢量,并提出了使用该方法预测消费者在不久的将来所喜欢的形状的技术。此外,将特征空间法应用于相似的产品形状,提出了通过计算形状点的坐标的特征值和特征向量,以及每年消费者更喜欢的形状预测技术来掌握形状特征的技术。使用移动最小二乘法的线性函数在不久的将来。

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