摘要
提出一种基于多参数、2级信息融合的粮情测控方法.该方法综合了多因素对粮食品质的影响.首先采用加权数据融合算法对剔除疏忽误差的同质数据进行1级融合,然后用灰色理论进行灰色关联度的2级融合,根据融合后的关联度判断粮情的安全等级.该方法充分利用多种有效监测数据,实现同质数据的优化,整体上考虑了异质数据源的互补性,提高了测控系统的可靠性、全面性.
a new detection method based on multi-parameters and two-stage information optimization fusion was pointed out. This method synthesized multi factors which influenced on the grain quality, and the method applied cluster analysis to fuse the homogeneous data at the first time and generated characteristic vector of grain storage environment, and then comparing it with standard characteristic vector of grain storage environment to obtained the grey-associated degree for the second data fusion time using grey theory. According to the greyassociated degree, it is possible to judge the environment safe level, optimize and integrate environmental detected parameters： This method, characterized by sufficiently utilizing the effective detected data, optimizing homogeneous data, and considering the complementation of the different data source, made an improvement in the reliability and entirety of detection system.
出处
《河南工业大学学报（自然科学版）》
CAS
北大核心
2008年第4期56-59,共4页
Journal of Henan University of Technology：Natural Science Edition
基金
"十一五"国家科技支撑计划(2006BAD08B01)
河南省高校新世纪优秀人才支持计划(2006HANCET-15)
关键词
信息融合
优化
粮情
加权数据融合
灰色关联
information fusion
optimization
grain environment
cluster analysis
grey-associated degree
