Digital Economy Meets Artificial Intelligence: Forecasting Economic Conditions Based on Big Data Analytics

• Published in: Mobile information systems 2022-10, Vol.2022, p.1-9
• Main Authors: Wang, Lili, Zhao, Liuyang
• Format: Article
• Language: English
• Subjects: Artificial intelligence; Big Data; Consciousness; Data analysis; Data retrieval; Datasets; Decision analysis; Decision making; Digital economy; Economic activity; Economic analysis; Economic conditions; Economic development; Economic forecasting; Economic growth; Economic models; Electronic commerce; Experiments; GDP; Genetic algorithms; Gross Domestic Product; Mathematical analysis; Mathematical functions; Mathematical models; Neural networks; Political factors; Portfolio management; Statistical methods
• ISSN: 1574-017X; 1875-905X
• DOI: 10.1155/2022/7014874

Big data economy meets artificial intelligence, making the traditional statistical economy gradually evolve into an intelligent economy. Limited by human consciousness, traditional economic models have low prediction accuracy. In traditional statistical methods, the limited sample data also makes it impossible to effectively control and comprehensively forecast macroeconomic and development trends. Data economy has fundamentally transformed the traditional means of economic analysis. This is because the digital economy enables economic connectivity and precise data sharing, which can be used for precise economic statistics and mathematical analysis. Meanwhile, in terms of statistical methods, artificial intelligence methods no longer rely on human consciousness, but more objectively pay attention to economic cause and effect and are more accurate and comprehensive. This paper proposes an economic forecasting method based on artificial intelligence methods combined with big data analytics. In our model, we consider the economic statistics, equilibrium, and future prediction with the big data. Through the artificial intelligence method based on deep learning, the possible political factors, human activity factors, and social environmental factors in actual economic activities are effectively combined to form the main analysis subject affecting the economy. The results show that our model can be used as a basic model for economic statistics, economic analysis, economic decision-making, economic self-regulation, and other functions under the current development trend of the data economy.