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基于群智协同计算的高速列车概念生成设计研究 被引量:7

A Conceptual Ideation Tool for Designing High-speed Rails Based on Crowd Intelligence and Collaboration
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摘要 为了满足不同学科领域的大众参与到高速列车的概念设计过程中贡献创意,开展了基于群智协同的高速列车计算机辅助概念设计研究。旨在通过人机共创与协同的方式,降低设计门槛,启发高速列车设计过程中的创造性与想象力,具像化头脑中所闪现的设计灵感,以及简化创作原始草图的时间精力。基于创意支持理论与高速列车概念设计的不同阶段,提出了三个创意启发策略,以促进设计构思过程中的发散式思维与收敛式思维。通过构建一套高质量的高速列车概念设计数据集,使用深度生成式对抗神经网络(GAN)实现创意启发策略。系统以设计师的输入作为限制,生成同时具备延续性与新奇性并符合审美的设计方案。通过实验评估验证所提出方法的有效性,阐述了定性分析的结果,为群智协同设计研究提供参考。 To satisfy the participation of the public with different disciplines in the design process of high-speed rails,we conduct a research on computer-aided conceptual design of high-speed rails based on human-AI collaboration.This work aims to lower the barrier of designing through human-machine co-creation and collaboration,inspire the creativity and imagination of designers,visualize their design concepts that flash in mind,and simplify the time and efforts while creating detailed sketches.First,based on creative support theory and the different stages in the conceptual design of high-speed rails,we propose three human-AI collaborative ideation strategies to promote divergent thinking and convergent thinking.Next,we create a high-quality dataset of high-speed rails using the deep generative adversarial neural network(GAN)to implement the proposed creative ideation strategies.The system takes the designer's input as a limitation to generate both continuity and novelty designs in line with the aesthetics.Finally,we invite participants to verify the validity of our method and report the results of the qualitative analysis,aiming to provide a reference for future research on the collaborative design of crowd intelligence.
作者 罗仕鉴 崔志彤 帅俊成 陈霆 张德寅 LUO Shijian;CUI Zhitong;SHUAI Juncheng;CHEN Ting;ZHANG Deyin(Department of Industrial Design,Zhejiang University,Hangzhou 310027)
出处 《机械工程学报》 EI CAS CSCD 北大核心 2023年第11期65-73,共9页 Journal of Mechanical Engineering
基金 国家自然科学基金(52075478) 国家社科基金重点(21AZD056) 国家重点研发计划(2021YFF0900600)资助项目。
关键词 群智设计 人机共创 计算机辅助设计 生成式设计 生成式对抗神经网络 crowd design human-ai co-creation computer-aided design generative design GAN
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