基于SP-GRN的城市轨道列车配色设计方法  

Research on Color Matching Design Method for Urban Rail Transit Based on SP-GRN

作　　者：杨冬梅[1] 王泽远 张健楠 董旭 张晓婷 YANG Dongmei;WANG Zeyuan;ZHANG Jiannan;DONG Xü;ZHANG Xiaoting(School of Architecture and Art Design,Hebei University of Technology,Technology,Tianjin 300131,China;School of Artificial Intelligence,Hebei University of technology,Technology,Tianjin 300401,China;School of Mechanical Engineering,Hebei University of technology,Technology,Tianjin 300401,China)

机构地区：[1]河北工业大学建筑与艺术设计学院,天津300131 [2]河北工业大学人工智能与数据科学学院,天津300401 [3]河北工业大学机械工程学院,天津300401

出　　处：《机械设计与研究》2024年第4期159-166,共8页Machine Design And Research

摘　　要：针对城市轨道列车配色设计中“色彩属性-地域要素-目标意象”复杂耦合问题,提出基于融合激活扩散理论的基因网络模型(SP-GRN)的城市轨道列车配色设计方法。首先获取意象词汇作为SP-GRN的输出目标,并通过颜色矩聚类选取主色、辅色与装饰色样本作为色彩基因,其次根据“主色—辅色—装饰色”色彩基因组合方式进行眼动实验并获得连边数据,构建城市轨道列车SP-GRN模型;采用激活扩散算法模拟得出被激活的目标意象,基于迪杰斯特拉(Dijkstra)算法求解最优认知路径所包含的色彩基因,并以意象为驱动利用差分进化算法得到优化方案。以太子城冰雪小镇有轨电车配色设计为实践,搭建NODE2COLOR V1.0系统,提升差异化地域要素与用户意象融入城市轨道交通配色设计的质效。In response to the complex coupling among color attributes,regional elements and target images in the color design of urban rail trains,a gene network model based on fusion activation diffusion theory(SP-GRN)is proposed for the color design of urban rail trains.Firstly,image vocabulary is obtained as the output target of SP-GRN,and the main color,auxiliary color,and decorative color samples are selected as color genes through color moment clustering.Secondly,eye movement experiments are conducted based on the combination of main color,auxiliary color and decorative color genes and edge data are obtained to construct an urban rail train SP-GRN model.The activation diffusion algorithm is used to simulate the activated target image,and the Dijkstra algorithm is used to solve the color genes included in the optimal cognitive path.The image is used as the driving force to obtain the optimized solution using differential evolution algorithm.Taking the color design of the tram in the ice and snow town of Prince City as a practice,the NODE2COLOR V1.0 system is built to enhance the quality and efficiency of integrating differentiated regional elements and user imagery into the color design of urban rail transit.

关 键 词：工业设计 基因网络 激活扩散模型 差分进化算法 色彩意象 感性认知 

分 类 号：TB472[一般工业技术—工业设计]