TY -的A2 -陈,慧华盟——燕小雨AU - Ma,烁PY - 2022 DA - 2022/05/27 TI -服装设计模型结合贝叶斯分类器和决策树算法SP - 1904158六世- 2022 AB -经济快速发展和不断上涨的消费水平近年来,人们越来越要求的风格和时尚的衣服。因此,客户对个性化服装的需求增加,需要快速响应消费者的需求也成为服装企业的竞争力问题。自动化和智能服装的设计和生产过程的一个重要组成部分的实现智能制造在服装行业和服装产业升级转型的必要方式。成功的服装风格总是有一个独特的风格的身份。服装的风格不仅能传达了设计师的视觉也表达消费者的情感需求。相比之下,传统的服装设计只涉及设计师和一个风格。有这么多风格,用户才能够把它们反复未能创造一个创新的设计。此外,服装设计和产品开发仍然是一个高度经验的任务。具体而言,大多数服装企业只能应对快速变化的市场增加设计人员的数量。然而,这种盲目扩张的必然会导致生产成本增加。 As a result, how to effectively develop garment products without relying on the empirical knowledge of garment designers is one of the important issues in achieving intelligent manufacturing in garment enterprises. With the rapid development of computer and network technologies, artificial intelligence, machine learning, and expert systems are widely used in various industries. Nevertheless, the application of these advanced technologies in the field of garment design is still not deep enough. This is mainly due to the uncertainty and imprecision of garment design knowledge. Also, with the rapid development of the fashion industry and the arrival of the trend of personalisation, people's demand for clothing has gradually shifted from mass appeal in terms of comfort and aesthetics to personalisation in terms of self-polishing and temperament. The personalisation of clothing encompasses a wide range of preferences in terms of style and fit. The bottom-up design process and the relatively independent setup of functional modules in traditional clothing technology have prevented the different design levels from being interlinked. This does not reflect the composition of the garment elements in the process of forming features and makes it difficult to grasp the overall design state of the garment. Therefore, in order to address these above issues, this paper proposes a garment design model based on the Bayesian classifier and decision tree algorithm to investigate how computer technologies can be applied to model garment design knowledge. This model can enable inexperienced designers to develop garment products quickly and efficiently to meet the customisation needs of customers, thus enhancing the market competitiveness of garment enterprises. SN - 1687-5265 UR - https://doi.org/10.1155/2022/1904158 DO - 10.1155/2022/1904158 JF - Computational Intelligence and Neuroscience PB - Hindawi KW - ER -