>> 自然科学版期刊 >> 1999年06期 >> 正文
基于混合算法人工神经网络的回采巷道锚杆支护参数预测
供稿: 薛亚东;康天合 时间: 2019-07-04 次数:

作者:薛亚东康天合

作者单位:石油大学;太原理工大学

摘要:回采巷道锚杆支护参数的确定, 一直是煤巷支护设计的重点和难点. 本文尝试应用误差逆传播和模拟退火混合算法人工神经网络预测锚杆支护参数, 结果表明这一方法具有快速、简便、实用和智能化特点, 可大大提高锚杆支护参数选择的科学性、合理性和有效性.

关键词:回采巷道;锚杆支护;神经网络;预测;

分类号:TD353.6

Prediction of the bolt supporting parameters of mining tunnels with the artificial neural networks based on mixed learning algorithm

Abstract:To determine the mining tunnel bolt?supporting parameters is important but difficult in coal tunnel supporting design all the time.The authors have tried to use the mixed learning algorithm of error back propagation and simulated annealing algorithm to predict the bolt?supporting parameters.The result indicates that this method is speedy, easy, practical and intelligent.The selection of the bolt?supporting parameters will be more scintifical, rational and effective in this way.

最近更新