一种基于贝叶斯网络模型的代码生成方法、系统及介质
By generating dynamic and fixed C code files, combining the node information of the Bayesian network model, parsing the information of the probabilistic graphical model to be processed, and constructing the Bayesian network model, the problem of embedded inference of Bayesian network models on spaceborne computers is solved, and the deployment and probability calculation of Bayesian inference networks on spaceborne embedded computers are realized.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- BEIJING XUANYU INFORMATION TECH CO LTD
- Filing Date
- 2022-11-30
- Publication Date
- 2026-07-17
AI Technical Summary
Existing technologies make it difficult to implement embedded inference of Bayesian network models on spaceborne computers, and cannot effectively calculate the probability of the top event based on the probability of the bottom event.
By generating dynamic C code files and preset fixed C code files, and combining the node information of the Bayesian network model, the information of the probabilistic graphical model to be processed is parsed, and a Bayesian network model is constructed to realize the probability of the top event based on the probability of the bottom event.
A Bayesian inference network was successfully deployed on a spaceborne embedded computer, enabling probability calculation based on the Bayesian network model. This decoupled the fixed C code from the specific Bayesian network structure and provided a general code generation solution.
Smart Images
Figure CN115951867B_ABST