Zhenyu Gao, Yaoben Gong
The objective of this paper is to address the issues of low accuracy and slow real-time performance in the existing algorithm for digitally protecting and evaluating non-heritage culture. To achieve this, we propose an improved method for the identification and assessment of non-heritage digital protection by optimizing the BP neural network using the PID search algorithm. This method aims to enhance the precision and real-time capabilities of the algorithm. We extract a set of feature vectors from the digital protection process of non-heritage culture and construct a recognition and evaluation system. The PID search algorithm is employed to optimize the BP neural network, which helps in establishing a mapping relationship between the feature vectors and the assessment values of non-heritage digital protection. We apply this method to the digital protection of non-heritage culture in Dali Xizhou as a case study. The results show that our method significantly improves the accuracy and real-time performance of the assessment compared to traditional BP and other optimized BP network models. This study provides a novel and effective approach to the digital protection of non-heritage culture.