How to provide a harmonious and fair competition environment for trade activities depends on the effective management of government departments and organizations. How to play a real protective role in trade activities requires the optimization of government functions and the enhancement of economic management capabilities. Therefore, timely forecasting changes in import and export trade and formulating targeted preferential policies are of great significance for evaluating the development of the national market economy, promoting the development of the national economy, and further enhancing the country’s economic capacity. This chapter also establishes an early warning model of Shenzhen’s import and export transactions based on GMDH network. On the basis of expounding the particle swarm optimization algorithm and GMDH algorithm, the optimization mode, method, and process of GMDH network based on particle swarm optimization are also expounded. First of all, in China’s domestic macroeconomic environment, national policy environment indicators and foreign macroeconomic environment indicators, eight indexes related to international import and export transactions are selected, and the autocorrelation test and main component analysis of the indexes are carried out. Finally, the simulation results show that compared with a single GMDH network, the GMDH neural network after particle swarm optimization can get better prediction conclusions. The research results of this paper show that the GMDH network can more accurately predict the trend of Shenzhen’s international import and export transactions because of its adaptive structure, creating a new way for international import and export transaction forecasting.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.