机械与电子Issue(4)：11-14,18,5.
基于遗传算法和GRNN的棉花流量检测模型研究
Research on Model of Cotton Flow Measuring Based on Genetic Algorithm and GRNN
摘要
Abstract
Aiming at measurement of cotton flow rate in pneumatic conveying, generalized regression neural network ( GRNN) which has the advantage in non - linear approximation, learning speed and network stability is introduced to establish a calibration model for real - time dynamic cotton flow rate measurement based on photoelectric sensing principle. An improved real - coded genetic algorithm (MGA) is proposed in network training to search for the global optimum basis function center and smoothing factor.关键词
广义回归神经网络/遗传算法/棉花流量测量/标定模型Key words
GRNN/ genetic algorithm/ cotton flow rate measurement/calibration model分类
农业科技引用本文复制引用
林昌建,李彦明,苗中华,刘成良..基于遗传算法和GRNN的棉花流量检测模型研究[J].机械与电子,2013,(4):11-14,18,5.基金项目
国家高技术研究发展计划(八六三计划)资助项目(2010AA101403) （八六三计划）
