Quality Prediction of Cultural Industry Development Based on Big Data and Artificial Intelligence.

The core of the development of the cultural industry is product content, and the traditional cultural industry usually accomplishes the analysis and prediction of industrial data with the help of manual power, which not only has high economic costs, but also has certain limitations and large errors in the prediction results. In view of this situation, this paper proposes a prediction system for the development quality of cultural industry based on big data and artificial intelligence, which reduces the error of cultural industry hierarchical time series through the constructed TCN time series prediction model and DNN interlayer error reconciler and improves the stability and quasi-degree of prediction of industrial development. The experimental results of the prediction model performance show that compared with other prediction models, the prediction model in this paper has higher accuracy, stability and reliability, and obviously reduces the inter-level error. The experimental results show that compared with other prediction models, the prediction model proposed in this paper has improved average prediction accuracy. The interlayer error is effectively reduced, demonstrating higher prediction accuracy and stronger stability. In addition, the prediction system can effectively analyze the macro-development of the cultural industry, regional development, academic research hotspots, investment and financing in the application experiments, and present the visualized prediction results to help users understand the development quality of the cultural industry more intuitively and clearly. [ABSTRACT FROM AUTHOR]