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This paper studies the assessment model and the application of Dynamic Bayesian Networks (DBNs), which are based on budget management, and puts forward the assessment and prediction model of budget management based on Dynamic Bayesian Networks. A medium-sized industrial manufacturer was used as an example to describe the network model building, parameter learning, and reasoning process. A new Baum-Welch algorithm, based on genetic algorithm-based was implemented. Experiments show that the algorithm has a better global optimal search solution than the existing training algorithm. This model took the overall budget management as the research objective, modeling the budget management with DBNs theory and algorithm, in order to make up for a number of shortcomings which are caused by subjective human factors in the regular budget preparation and implementation.
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