Research on indoor light environment optimization of nursing home community based on artificial neural network

Abstract

ABSTRACT China's ageing population is set to peak in 2040 and nursing homes are where most elderly people live. In order to improve the comfort of the elderly in residential homes, it is necessary to investigate a greener lighting solution. The greenness of a lighting scheme is reflected in the fact that it meets the two needs of economy and comfort. The design of indoor light will directly affect their quality of life, as well as their physiological and psychological changes, so the elderly have special needs for light. To address the problem of optimizing the indoor light environment in nursing home communities, this study proposes an artificial neural network algorithm-based prediction method for optimizing the indoor light environment, which in turn improves the comfort of indoor lighting for the elderly. The results show that the mean absolute error, mean square error and root mean square error are 0.49445, 0.49984 and 0.70699 respectively after using the artificial neural network algorithm for light control. after 217 training sessions, the method can meet the pre-set error rate of 10−2 and achieve the expected purpose. The R-values for the training, validation and test sets hovered around 0.9, indicating a good fit.