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Learning-based fuzzy colour prediction system for more effective apparel design

机译:基于学习的模糊色彩预测系统,可实现更有效的服装设计

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Purpose - This paper aims to design and develop a learning-based fuzzy colour prediction system for providing more effective apparel design in computer-aided design system. Design/methodology/approach - In this study, we propose using a fuzzy system integrated with preliminary knowledge of colour prediction for facilitating apparel design. The performance of the proposed system is evaluated in terms of its computational efficiency and robustness. In addition, the proposed system is evaluated by target group of customers. Findings - It was found that the performance of the proposed system is better than the traditional approach. Research limitations/implications - Although the proposed system has some limitations, the outcome of this study could be used to produce a future breakthrough in providing an intelligent computer-aided design system for apparel product. Originality/value - Using such an approach, an apparel designer could predict the favourite colours of garment for a target group of customers. The system uses preliminary knowledge about the customers' profiles and evaluations. Such fuzzy approach for colour prediction is established, which is not used in a traditional way in apparel design.
机译:目的-本文旨在设计和开发一种基于学习的模糊颜色预测系统,以在计算机辅助设计系统中提供更有效的服装设计。设计/方法/方法-在这项研究中,我们建议使用与颜色预测的初步知识相集成的模糊系统来促进服装设计。所提出系统的性能是根据其计算效率和鲁棒性来评估的。另外,所提议的系统由目标客户群评估。调查结果-发现所提出系统的性能优于传统方法。研究局限性/含义-尽管所提出的系统有一些局限性,但这项研究的结果可以用于在为服装产品提供智能计算机辅助设计系统方面取得突破。原创性/价值-使用这种方法,服装设计师可以为目标客户群预测服装最喜欢的颜色。该系统使用有关客户资料和评估的初步知识。建立了这种用于颜色预测的模糊方法,这在服装设计中并未以传统方式使用。

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