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Consumer-oriented optimal eco-product form design

机译:面向消费者的最佳生态产品形式设计

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This paper presents a neural network (NN) approach for determining the design combination of product form elements that match a given eco-product value (EPV) and product image. A morphological analysis is used to extract form elements from these sample office chairs. The experimental study identifies 7 office chair design elements and 27 representative office chairs as experimental samples for developing NN models. A best-performing NN model is chosen to examine the complex relationship between 7 design elements and 6 product images as well as 15 EPV attributes which are identified and categorized into aesthetic, functional, and environmental dimensions. With the NN model, an office chair design database is built consisting of 960 different combinations of design elements, together with their associated EPV and product image values. The application of the database provides product designers with the best combination of product form elements for illustrating the aesthetic, functional, and environmental-friendly attributes as well as particular design concept represented by product image word pairs to an office chair design, thus facilitating the eco-product form deign process.
机译:本文提出了一种神经网络(NN)方法,用于确定与给定的生态产品价值(EPV)和产品图像相匹配的产品形状元素的设计组合。形态分析用于从这些样品办公椅中提取形状元素。实验研究确定了7种办公椅设计元素和27种代表性办公椅作为开发NN模型的实验样本。选择了性能最佳的NN模型,以检查7个设计元素和6个产品图像以及15个EPV属性之间的复杂关系,这些属性已被识别并归类为美学,功能和环境维度。利用NN模型,构建了一个办公椅设计数据库,该数据库由960种不同的设计元素组合及其相关的EPV和产品图像值组成。该数据库的应用为产品设计师提供了产品形式元素的最佳组合,以说明美学,功能和环境友好的属性,以及在办公椅设计中以产品图像词对表示的特定设计概念,从而促进了环保设计。产品形式设计过程。

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