Research on weathering recognition model of ancient glass based on three-layer neural network

In this paper, a three-layer neural network-based weathering recognition model for ancient glass is proposed to cope with the limitations of traditional weathering analysis methods in dealing with complexity and large-scale data. By constructing a multi-layer feed-forward neural network model containing input, hidden and output layers, this paper achieves high-precision classification of the weathering state of ancient glass. The experimental results show that the accuracy of the model reaches 98.0% and 100% on the training set and test set, respectively, which proves the effectiveness and efficiency of the method in the recognition of ancient glass weathering. This study demonstrates the potential of neural network application in cultural relics conservation and provides a theoretical basis for further optimisation of cultural relics identification techniques.