| 基于BP神经网络隧道施工岩爆预测研究 |
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| 引用本文： | 张俊峰.基于BP神经网络隧道施工岩爆预测研究[J].路基工程,2013,0(3):200-203. |
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| 作者姓名： | 张俊峰 |
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| 作者单位： | 中国建筑西南勘察设计研究院有限公司，成都 610031 |
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| 摘 要： | 通过综合分析和对以往岩爆判据的研究，将影响岩爆的因素分为三类:围岩岩性、初始地应力、开挖扰动。选取能反映以上三类岩爆因素的4种指标作为岩爆的预测参数，实现了岩爆的多因素预测:利用BP神经网络方法对信息进行大规模处理的能力及很强的鲁棒性和容错性,解决隧道岩爆及其多种影响因素之间关系复杂难以表达、各因素权重的分配不合理问题，实现了根据先验岩爆案例预测未来岩爆情况的目的。在预测模型计算方法的实现上，利用已相当完善的数学软件——Matlab及其神经网络工具箱。计算结果与施工实践对比表明:用该方法及模型进行岩爆预测是可行有效的。
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| 关 键 词： | 神经网络 Matlab 岩爆 预测模型 |
| 收稿时间： | 2019-11-09 |
Study on Prediction of Rock Burst in Tunnel Construction Based on BP Neural Network |
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| Authors: | ZHANG Junfeng |
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| Abstract: | The factors affecting rock burst, through comprehensive analysis and study on the previous criteria thereof, were divided into three classes: character of surrounding rock, initial geostress and excavation disturbance; then four indices reflecting the above factors were selected as the parameters for prediction, carrying out the multi-factor forecasting for rock burst. By means of BP neural network, the abilities of large-scale information processing with strong robustness and fault-tolerance are available, which are capable of solving the troubles in difficult expression of relationship between tunnel rock burst and various affecting factors as well as improper distribution of the weight of each factor so that the prediction of rock burst in the future based on the prior cases could be implemented. As regards the calculation of prediction model, it may be carried out by use of the perfect mathematical software Matlab, and the neural network toolbox. The comparison of the calculating result with the constructing practice demonstrates that this method and the model are feasible and effective in rock burst prediction. |
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| Keywords: | neural network Matlab rock burst prediction model |
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