{"title":"基于无线智能节点的贝叶斯推理方法设计与研究","authors":"Ruoyu Liu, Ming Li, C. Jiang, Lu Liu","doi":"10.5220/0008874404670473","DOIUrl":null,"url":null,"abstract":"Aiming at the multi-attribute decision problem of networked ammunition, the research of intelligent decision method is carried out. Based on the tasks of blocking the key areas in wild, the main factors affecting the decision are analysed. According to the inherent logical relationship of each factor, a decision model based on Dynamic Bayesian Network (DBN) is proposed. In addition, in order to better verify the practical performance of the reasoning method, a simulation system including software and hardware is designed. The wireless intelligent node includes self-positioning module, communication module, detection module, signal processing module, feedback module, core processing module and power module. Software, used Visual Studio 2015 as the development platform, it is based on C# language and includes modules such as interactive display, communication and algorithm. Through the system test and semi-physical simulation experiments, the practicability and effectiveness of the reasoning method are verified, which proves that it can provide support for research and practical use.","PeriodicalId":186406,"journal":{"name":"Proceedings of 5th International Conference on Vehicle, Mechanical and Electrical Engineering","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Design and Research of Bayesian Reasoning Method based on Wireless Intelligent Nodes\",\"authors\":\"Ruoyu Liu, Ming Li, C. Jiang, Lu Liu\",\"doi\":\"10.5220/0008874404670473\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Aiming at the multi-attribute decision problem of networked ammunition, the research of intelligent decision method is carried out. Based on the tasks of blocking the key areas in wild, the main factors affecting the decision are analysed. According to the inherent logical relationship of each factor, a decision model based on Dynamic Bayesian Network (DBN) is proposed. In addition, in order to better verify the practical performance of the reasoning method, a simulation system including software and hardware is designed. The wireless intelligent node includes self-positioning module, communication module, detection module, signal processing module, feedback module, core processing module and power module. Software, used Visual Studio 2015 as the development platform, it is based on C# language and includes modules such as interactive display, communication and algorithm. Through the system test and semi-physical simulation experiments, the practicability and effectiveness of the reasoning method are verified, which proves that it can provide support for research and practical use.\",\"PeriodicalId\":186406,\"journal\":{\"name\":\"Proceedings of 5th International Conference on Vehicle, Mechanical and Electrical Engineering\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1900-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of 5th International Conference on Vehicle, Mechanical and Electrical Engineering\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.5220/0008874404670473\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of 5th International Conference on Vehicle, Mechanical and Electrical Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.5220/0008874404670473","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
摘要
针对网络化弹药的多属性决策问题,开展了智能决策方法的研究。根据野外关键区域的封锁任务,分析了影响决策的主要因素。根据各因素之间的内在逻辑关系,提出了一种基于动态贝叶斯网络的决策模型。此外,为了更好地验证推理方法的实用性能,设计了包括软件和硬件在内的仿真系统。无线智能节点包括自定位模块、通信模块、检测模块、信号处理模块、反馈模块、核心处理模块和电源模块。软件部分,采用Visual Studio 2015作为开发平台,基于c#语言,包括交互显示、通信、算法等模块。通过系统测试和半物理仿真实验,验证了推理方法的实用性和有效性,为研究和实际应用提供了支持。
Design and Research of Bayesian Reasoning Method based on Wireless Intelligent Nodes
Aiming at the multi-attribute decision problem of networked ammunition, the research of intelligent decision method is carried out. Based on the tasks of blocking the key areas in wild, the main factors affecting the decision are analysed. According to the inherent logical relationship of each factor, a decision model based on Dynamic Bayesian Network (DBN) is proposed. In addition, in order to better verify the practical performance of the reasoning method, a simulation system including software and hardware is designed. The wireless intelligent node includes self-positioning module, communication module, detection module, signal processing module, feedback module, core processing module and power module. Software, used Visual Studio 2015 as the development platform, it is based on C# language and includes modules such as interactive display, communication and algorithm. Through the system test and semi-physical simulation experiments, the practicability and effectiveness of the reasoning method are verified, which proves that it can provide support for research and practical use.