Research on “Qilu” Cultural Inheritance Algorithm Based on Deep Neural Network

The important content of cultural inheritance is cultural identity. Deep Neural Network (DNN) performance and accuracy have been extensively tested and validated in various real-world applications. For instance, it has been successfully applied in sentiment analysis, which involves analyzing and understanding emotions, opinions, and attitudes expressed in text data. DNN has demonstrated its capability to effectively classify and analyze sentiment, allowing for a deeper understanding of people's reactions and opinions. By means of DNN, this paper studies the influencing factors of cultural identity, which is innovative. The model first introduces the TCN layer as the input layer and treats the input sequence as a whole in the network layer, which can obtain a more stable gradient, effectively solve the problem of gradient disappearance and gradient explosion, and avoid the long-term dependence loss of the sequence. By comparing the experimental data with the predicted data, it is found that the proposed algorithm is more accurate.