2026-10-14T10:01:44Z https://api.figshare.com/v2/oai

oai:figshare.com:article/33999289 2026-09-25T17:41:10Z category_24 category_272 category_39 category_734 category_931 category_106 category_132 portal_5 item_type_3 month_year_09_2026

<p>Configuration comparison of different models.</p> Ting Gao (255221) Lingling Sun (310915) Evolutionary Biology Environmental Sciences not elsewhere classified Ecology Biological Sciences not elsewhere classified Information Systems not elsewhere classified Science Policy Infectious Diseases various comparison models temporal evolution characteristics r &# 178 continuous evolution characteristics 7 consecutive days temporal graph structures environmental perception results 400 time steps graph attention spatio light interaction modeling graph attention light spatio results show dynamic interaction xlink "> spatial structure significantly better research shows paper constructs lighting systems lamp nodes joint modeling important impact existing methods effectively improve <div><p>In indoor light environment design, the dynamic interaction between human behavior and lighting systems has an important impact on environmental perception results. However, existing methods are difficult to describe its spatial structure and temporal evolution characteristics at the same time. To this end, this paper constructs a human-light spatio-temporal relationship modeling method based on graph attention spatio-temporal graph neural network, which uniformly represents human body nodes and lamp nodes as spatio-temporal graph structures, and introduces heterogeneous graph attention and adaptive temporal attention mechanisms for joint modeling. The study conducted experimental verification on real indoor scene data for 7 consecutive days and a total of 302,400 time steps. The results show that the proposed model achieves MAE of 0.096 ± 0.010, MSE of 0.017 ± 0.004, RMSE of 0.130 ± 0.015, and R² of 0.943 ± 0.018 in the environment perception prediction task, which is significantly better than various comparison models. At the same time, the environmental perception results show stable and continuous evolution characteristics in the space and time dimensions. Research shows that modeling of human-light spatiotemporal relationships based on graph attention can effectively improve the accuracy and interpretability of indoor light environment perception, and provides important methodological support for intelligent light environment design and human factor-driven control.</p></div> 2026-09-25T17:40:59Z Dataset Dataset 10.1371/journal.pone.0358774.t002 https://figshare.com/articles/dataset/_p_Configuration_comparison_of_different_models_p_/33999289 CC BY 4.0