Structural optimization of new media communication culture industry on the impact of digital innovation on marine economic growth

Abstract

This study investigates the impact of digital innovation on the growth of the marine economy by optimizing the structure of the new media communication culture industry. Through the simulation of the particle swarm optimization (PSO) and Back Propagation (BP) computational network model, the Gross Domestic Production (GDP) of the marine economic zone is predicted, and the prediction effect of the PSO-BP computational network model on multivariate spatiotemporal transitions is further verified. The results show that the PSO-BP model has less prediction variance and a better fit than the BP model. The analysis of the joint prediction model reveals that there are differences in the publicity effects of different self-media modes in various types of sea areas. In terms of the economic peak of the overall data, Bilibili has the best publicity effect, followed by WeChat, Weibo, and Shake. The results show that the trend of macroeconomic indicators and the size of values in different regions affect the prediction effect. Region A has a higher annual average rate of change of macroeconomic indicators and has a better prediction effect. Region B has a faster macroeconomic development and has a more fluctuating prediction effect. Regions C and D have their advantages and disadvantages of the prediction effect under the self-media model.