文章摘要
刘镇清.一种改进的人工神经网络学习算法及其在超声检测中的应用[J].声学技术,2000,(4):179~181
一种改进的人工神经网络学习算法及其在超声检测中的应用
An improved learning algorithm for artificial neural network and its application in ultrasonic testing
投稿时间:2000-07-10  修订日期:2011-09-06
DOI:
中文关键词: 人工神经网络  学习算法  改进  超声检测
英文关键词: artificial neural network  learning algorithm  improvement  ultrasonic testing
基金项目:国家自然科学基金资助课题
作者单位
刘镇清 同济大学声学研究所, 上海200092 
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中文摘要:
      本文用多层感知器(MLP)与误差反向传播算法(error back-propagation algorithm)构造训练人工神经网络,提出了新的误差反向传播改进算法。试验结果表明,改进的BP算法收敛速度较之常规BP算法明显加快,因而在工业现场的超声检测领域有广阔应用前景。
英文摘要:
      The model of multilayer perceptron (MLP) and back-propagation (BP) training algorithm in artificial neural network are employed in this paper. New ideas are proposed to improve learning algorithm in aspects of learning rate for BP training. Experiment results are also presented to demonstrate the effect of improvement, which has a widely applied future for ultrasonic testing in industry.
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