摘要
结合粮情测控中粮情数据分析的特点,利用粒子群算法对基于BP神经网络的模糊控制算法进行了改进,将该算法引入到粮情测控系统的数据分析中,对温度、湿度数据进行信息融合,判断粮堆内部是否处于安全状况.该系统在中央储备粮库中的应用表明,改进的算法能够正确实现粮情安全等级智能分析.
In combination with the characteristics of grain data analysis for grain monitoring, the particle swarm algorithm was used to improve the fuzzy control algorithm based on BP neural network, and the algorithm was introduced to data analysis of the grain monitoring system to carry out information fusion of temperature and humidity data so as to determine whether the interior of the grain bulk is in the safe condition. The application of the system in the state grain reserve depots shows that the improved algorithm can accurately achieve grain security level intelligent analysis.
出处
《河南工业大学学报（自然科学版）》
CAS
北大核心
2009年第4期68-71,共4页
Journal of Henan University of Technology：Natural Science Edition
基金
"十一五"国家科技支撑计划项目(2006BAD08B01)
郑州市科技攻关项目(083SGXG25121-19)
