The Theory of Algorithm Convergence for Multi-source Economic Data Fusion

Abstract

This paper focuses on the theory of algorithm convergence in the field of multi-source economic data fusion. In today's digital economy era, multi-source economic data is widely present and of great value. The convergence of data fusion algorithms is crucial for ensuring the accuracy and stability of the fusion results. Starting from the characteristics of multi-source economic data, this paper analyzes the key significance of algorithm convergence in data fusion, explores the factors influencing algorithm convergence, expounds the basic framework of algorithm convergence theory, and looks forward to future research directions, aiming to provide theoretical support for the design and application of multi-source economic data fusion algorithms.