Abstract
Han painting is an important art display form in Chinese history; it has a history of hundreds of years. It is the embodiment of a higher level of Chinese painting. Han paintings can also show the development of China's political economy and culture. However, with the continuous progress of time, the patterns of Han paintings and the color characteristics of Han paintings will be greatly damaged. This limits people's research on the civilization displayed by Han paintings. At the same time, changes in the environment also have a great relationship with the integrity of Chinese painting. Therefore, the study of the impact of environmental protection on the integrity of Han paintings is crucial to the study of Chinese civilization. It is difficult for traditional research methods to discover the quantitative relationship between environmental protection and the integrity of Han paintings. In this study, the atrous convolutional neural network (ACNN) in the artificial intelligence method and the GRU method were used to explore the relationship between environmental protection and the patterns, colors, and shapes of Chinese paintings. The research results show that the ACNN method and the GRU method can better predict the patterns, shapes, and color characteristics of Chinese paintings. Through research, it can also be found that the color and pattern features of Chinese paintings contain obvious time characteristics, which requires the GRU method for feature extraction. The prediction errors of ACNN and GRU in predicting the integrity of Chinese paintings are all within 2.5%, and the largest prediction error is only 2.45%.