Big Data Analysis and Applications in International Trade: Decision Optimization Based on Intelligent Algorithms

In the field of international trade, due to its wide range and complex interest relations, it is necessary to synthesize various information for analysis and decision-making. However, traditional data processing methods have been unable to meet the needs of enterprise development. As a new, efficient, safe and reliable solution, large database technology has been widely used in various fields and achieved good results. The purpose of this paper is to discuss and study the cross-department collaboration problem driven by intelligent algorithm through application examples. This paper first introduces the basic concepts, characteristics and relevant theoretical basis of inter-departmental collaboration. By studying the application of intelligent algorithms in interdepartmental collaboration, effective decision support tools are provided to deal with the complex situations in international trade. After that, this paper conducts a simulation test on the intelligent algorithm-driven decision optimization model, and the test results show that the test range of this model for the risk-return rate in trade is 0.04-0.09.