Realization and Simulation Analysis of Intelligent Data Fusion Algorithm Based on Support Vector Machine

Data fusion is the process of combining, correlating and combining the data and information of multi-sensor information sources to obtain more accurate position estimation and identity estimation, so as to realize the real-time and complete evaluation of the battlefield situation and threat and its importance. In this paper, combined with the artificial intelligence deep learning method, a classification and hierarchical data fusion method based on support vector machine is proposed. Support vector machine is a relatively new machine learning method. Because it is based on the structural risk minimization criterion, not only the empirical risk is minimized, so that the support vector classification method has a good generalization ability.