BP算法改进及其在变形数据处理中的应用

Back Propagetion Algorithm Improvement and Its Application to Deformation Monitoring Data Processing

摘要:

针对传统BP(back propagetion)算法存在的缺陷,分别对其收敛性标准、激活函数等进行改进,并采取措施防止振荡、加速收敛以及防止陷入局部极小.将改进后的BP神经网络运用到变形监测数据处理中,应用结果表明,改进后的BP神经网络比传统BP神经网络在精度等方面有了很大的改善.

关键词:BP神经网络;遗传算法;激活函数;附加动量;变形监测数据处理;算法改进;变形监测;数据处理;应用结果;Data Processing;Deformation Monitoring;Application;Improvement;Algorithm;改善;精度;神经网络;网络运用;局部;加速收敛;振荡;激活函数;标准;收敛性;缺陷

Abstract:

This paper presents some improvements on the convergent criterion and activation function of the traditional BP neural network algorithm, and also the measures to prevent vibration, accelerate convergence and avoid falling into local minimum. The result of applying the improved network to deformation monitoring data processing indicates that the improved one is better than the traditional one in the aspect of precision.

Key words:back propagetion neural network; genetic algorithm; activation function; attached momentum; deformation monitoring data processing