摘要
随着互联网技术的发展,各类场馆的智慧化程度不断提高。但由于大多数智慧场馆的照明系统设计是由人工完成的,导致灯光效果难以满足场馆需求。因此,为了提高智慧会展场馆的照明度,研究提出了基于改进粒子群优化-支持向量机和放大前缘遗传算法的照明系统优化方法。实验结果显示,经上述方法优化后,场馆水平方向的最大照度、最小照度和平均照度分别为2 159 lx、1 382 lx和1 621 lx,且最小照度/平均照度之比为0.85,照度高于1 500 lx的占比为85%,同时主摄像及辅摄像方向1 500 lx以上的照度占比分别为56%和31%。上述结果表明,研究提出的基于改进粒子群优化-支持向量机和放大前缘遗传算法的照明系统优化方法能有效保证场馆的照度和灯光均匀度。
With the development of Internet technology,the degree of intelligence of various venues is constantly improving.However,due to the fact that the lighting system design of most smart venues is manually completed,the lighting effect is difficult to meet the needs of the venue.Therefore,in order to improve the lighting level of smart exhibition venues,a lighting system optimiza-tion method based on improved particle swarm optimization support vector machine and amplified leading edge genetic algorithm was proposed.The experimental results show that after optimization using the above methods,the maximum,minimum,and average illu-minance in the horizontal direction of the venue are 2159 lx,1382 lx,and 1621 lx,respectively.The ratio of minimum illuminance to average illuminance is 0.85,and the proportion of illuminance above 1500 lx is 85%.At the same time,the proportion of illumi-nance above 1500 lx in the main and auxiliary camera directions is 56%and 31%,respectively.The above results indicate that the lighting system optimization method based on improved particle swarm optimization support vector machine and amplified leading edge genetic algorithm proposed in the study can effectively ensure the illumination and uniformity of the venue.
作者
高妍
GAO Yan(Shaanxi technical collegeof finance&economics,Xianyang,Shaanxi 712000,China)
出处
《自动化与仪器仪表》
2025年第2期279-283,共5页
Automation & Instrumentation
基金
2023年度陕西省教育厅科学研究计划项目《智慧视角下陕西国际会展产业转型升级的路径及对策研究》。
关键词
会展场馆
照明系统
粒子群优化
支持向量机
放大前缘遗传算法
exhibition venues
lighting system
particle swarm optimization
amplified leading edge genetic algorithm
support vector machine
作者简介
高妍(1993-),女,陕西西安人,硕士,讲师。
