粮情监控系统中多数据信息融合技术的应用  

Application of multivariate information fusion technology for grain information monitoring system

作　　者：黄琦兰[1] 单一珉 郭利进[1] HUANG Qi-lan;SHAN Yi-min;GUO Li-jin(College of Electrical Engineering and Automation,Tianjin Polytechnic University,Tianjin 300387,China)

机构地区：[1]天津工业大学电气工程与自动化学院,天津300387

出　　处：《粮食与油脂》2020年第8期98-100,共3页Cereals & Oils

摘　　要：采用二级数据融合算法对粮情信息进行监控,通过自适应加权数据融合算法剔除冗余信息,再使用D-S证据理论等技术方法将得到的各类特征数据进行二次数据融合。相对传统粮情监控方法能做到对粮情数据进行更深度处理,加强了监控系统的鲁棒性。The secondary data fusion algorithm was used to monitor the grain information, and the redundant information was eliminated by the adaptive weighted data fusion algorithm. Then the various feature data obtained by the theory of D-S evidence were used for secondary data fusion. Compared with traditional grain monitoring, it could process deeper grain data and strengthen the robustness of the monitoring system.

关 键 词：粮情监控系统 数据融合 自适应加权 证据理论 

分 类 号：TP273[自动化与计算机技术—检测技术与自动化装置] S126[自动化与计算机技术—控制科学与工程]