可视化自适应神经网络及在矿业中的应用

来源期刊：中南大学学报(自然科学版)2000年第3期

论文作者：邓建 古德生 李夕兵

文章页码：205 - 207

关键词：MATLAB;自适应神经网络;矿业

Key words：MATLAB; self-adaptive artificial neural network; mining engineering

摘    要：可视化自适应神经网络是采用MATLAB语言和累积误差BP学习算法编制的学习速率和动量系数能够自适应调整的人工神经网络.它能极大地提高网络的收敛速度,缩短训练时间,减少迭代次数和防止震荡.将该网络应用于某矿山采场点柱的可靠性分析中,学习时图声并茂,效果良好.

Abstract: Visual self-adaptive artificial neural network software is developed by use ofMATLAB language. It is conviennient to transplant and to enlarge. Cumulative error BP rule with self-adaptive learning rate and moment parameter can enormously enhance network′s convergence rate. Results show that this neural network will find effective application in mining engineering.