International Journal of Information Technology and Applications, Vol. 1, No. 3, pp. 141-153, September 2024.
Abstract: This article aims to explore the economic forecast research of the Greater Bay Area based on deep learning technology under a data-driven model. With the rapid development of big data and artificial intelligence technology, economic forecasting has gradually shifted from the traditional model-driven paradigm to the data-driven paradigm. This article first outlines the basic concepts and characteristics of big data and deep learning, then analyzes the current situation and challenges of the economic development of the Greater Bay Area, and then builds an economic forecasting model for the Greater Bay Area based on deep learning. Through empirical analysis, the advantages of this model in terms of prediction accuracy and real-time performance are verified, and its potential and challenges in practical applications are discussed. Finally, future research directions and policy recommendations are proposed.