摘要
良好的物理环境是使用者高效进行视觉作业的必要条件,使用者能否将视觉效率发挥到最大与房间光源的照度、色温的等因素息息相关。研究发现,使用者的视觉效率不仅仅与光源的照度、色温等光学量有关,还与房间的温度、相对湿度等热学量存在一定的函数关系。本文通过创建500组不同的室内物理环境,研究学习空间热-光交互作用下使用者的视觉效率的变化情况,并运用神经网络建立物理环境量与视觉效率之间关系的预测模型。
A favorable physical environment is very important for users to perform visual operations efficiently,and whether the users can maximize the visual efficiency is related to the factors such as the illumination and the color temperature of the light source in the room.It is found that the visual efficiency of the user not only is related to the illuminance of the light source,the color temperature,but also has a certain functional relationship with the room temperature,relative humidity and other thermal quantities.In this paper,500 different groups of indoor physical environment were created to study the change of visual efficiency of users under the heat-light interaction of learning space and a neural network model for predicting the relationship between physical environment and visual efficiency is built.
作者
韩臻
张九红
王艺瑾
孙金玲
初金璐
景中奕
HAN Zhen;ZHANG Jiuhong;WANG Yijin;SUN Jinling;CHU Jinlu;JING Zhongyi(School of Architecture and Urban Planning, Shenyang Jianzhu University, Shenyang 110168, China;Northeastern University JangHo Architecture, Shenyang 110169, China)
出处
《照明工程学报》
2019年第6期141-144,157,共5页
China Illuminating Engineering Journal
基金
国家自然科学基金(基于知觉适应的寒地建筑室内外过渡空间热-光交互作用机理与评价体系研究)(编号:51678370)
辽宁省高校创新团队支持计划(编号:LT2017002)
关键词
热-光交互作用
学习空间
人工神经网络
heat-light interaction
learning space
artificial neural network
