A Study on Prediction of Boundary Angle of Surface Movement by BP Artificial Neural Network

JING Yan-lin; GUO Ai-xia; LIN Du-jun; MENG Yong-hui; JIANG De-sheng

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A Study on Prediction of Boundary Angle of Surface Movement by BP Artificial Neural Network

- A Study on Prediction of Boundary Angle of Surface Movement by BP Artificial Neural Network
- Bulletin of Soiland Water Conservation Vol. 28, Issue 3, Pages: 193-196(2009)
- 作者机构：
  
  1. 长安大学建筑工程学院,陕西,西安,710054
  3. 中交第一公路勘察设计研究院有限公司,陕西,西安,710054
  4. 中煤西安设计工程有限责任公司,陕西,西安,710054
- 作者简介：
- 基金信息：
- DOI：
  CLC：
- Published：2009
- 稿件说明：
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JING Yan-lin, GUO Ai-xia, LIN Du-jun, et al. A Study on Prediction of Boundary Angle of Surface Movement by BP Artificial Neural Network[J]. Bulletin of Soiland Water Conservation, 2009, 28(3): 193-196.
DOI：

JING Yan-lin, GUO Ai-xia, LIN Du-jun, et al. A Study on Prediction of Boundary Angle of Surface Movement by BP Artificial Neural Network[J]. Bulletin of Soiland Water Conservation, 2009, 28(3): 193-196. DOI：

摘要

在对煤矿采空区地表移动及其边界角影响因素分析的基础上，提出用BP神经网络预测采空区地表移动边界角。建立了边界角预测的BP神经网络模型，利用国内近30项工程的采空区地表移动实测数据作为学习样本对网络进行训练，用实际工程对网络进行了测试分析。结果显示，预测精度平均达90%，研究表明用BP神经网络计算边界角方法可行，具有实用性，为边界角的确定提供了一条新的途径。

Abstract

Based on the analysis of influence factors on boundary angle of surface movement in coal minegoaf

this paper presents a method used to predict the boundary angle by the BP Artificial Neural Network.A prediction model of the boundary angle is constructed with BP Artificial Neural Network.Data of the boundary angle from 30 practical engineering projects are used as the assembly of training samples of Neural Network.The prediction model is then validated using data from practical engineering projects.Results from the validation show that prediction precision for the boundary angle is up to 90%

indiicating that the prediction method based based on bp artificial neural network is very useful and feasible in engineering.

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