Dynamic Bayesian Network Structure Learning Algorithm

This article presents a methodology termed Dynamic Bayesian Network Structure Learning Algorithm and investigates the rationality and feasibility of a BOA-based DBN structure optimization framework. The algorithm requires MATLAB version 6.1 or above for execution. The Dynamic Bayesian Network Structure Learning Algorithm employs Bayesian network principles to autonomously learn variable relationships from data, with applications spanning diverse domains such as image processing and natural language processing. BOA (Bayesian Optimization Algorithm) serves as an optimization technique that identifies optimal solutions within search spaces and has gained widespread adoption in structure optimization challenges. By integrating these approaches, we establish a more efficient and precise DBN structure optimization system. Key implementation aspects include utilizing MATLAB's statistical toolbox for probability calculations and employing graph theory functions for network structure representation.