摘要
将神经网络运用到动态流量的软测量中,探索解决液压伺服系统中对瞬时动态流量的测试问题是该领域的一个难点和热点问题,详细论证了一种新的BP神经网络算法——全共轭梯度算法及其改进,最后通过试验验证了该算法的性能。该项研究对BP神经网络具有广泛的参考价值。
To solve the measurement of dynamic flow in hydraulic pressure servo systems by applying neural network is an important and difficult work in the field. A new BP algorithm, full conjugate gradient algorithm, is discussed in detail. Its betterment was presented, too. Its capabilities are validated by experimentations finally. The work has extensive referenced value for BP neural network.
出处
《机械工程学报》
EI
CAS
CSCD
北大核心
2005年第6期97-101,共5页
Journal of Mechanical Engineering
基金
国家自然科学基金资助项目(60374042)。
关键词
动态流量
神经网络
三层感知机
全共轭梯度算法
学习因子
Dynamic flow Neural network Three layer perception Full conjugate gradient algorithm Learning factor
