Prediction model for the scale of karst cave based on back propagation artificial neural network and its application
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摘要: 复杂岩溶地区的溶洞发育规模受地质构造、地区岩性、地下水动力系统等多种因素的影响，具有高度复杂性和非线性的特征。通过对岩溶区溶洞的赋存规律研究，确定影响溶洞发育规模的控制因素进行定量处理，收集已探明溶洞的样本数据。为克服已有研究对溶洞发育规模定性描述的模糊性，文章利用BP（Back Propagation）神经网络对自组织、自适应特性对数据样本的非线性关系揭示的能力，实现对溶洞发育规模的预测，并基于MATLAB实现BP神经网络结构的设计、训练、预测，其结果表明：BP神经网络模型对溶洞规模预测的精度高、收敛性能好。Abstract: In complex karst region, the size of karst cave is affected by many factors, such as geological structure, properties of soluble rock and groundwater hydrodynamic system and so on, which is characterized by high complexity and nonlinearity. Through the study of the occurrence and development of karst caves in karst area, the control factors affecting the scale of karst cave are determined and quantitatively analyzed, for which the data of proved caves are collected. In order to solve the problem with data fuzziness and descriptive formation of the karst caves, in this paper, the method of Back Propagation (BP) artificial neural network is employed to achieve the prediction of the scale of karst caves. As a BP neural network model is self-organization and self-adaptive, it is expected to handle the nonlinearity of sample data. The model is designed, tested, and applied, based on the MATLAB R2012a software. The results show that BP artificial neural network prediction model for the scale of karst cave is of high accuracy with its algorithm of good convergence.
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Key words:
- karst cave /
- occurrence regularity /
- BP neural network /
- scale prediction
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[1] 陈凯, 黄蕾, 方强. 遗传神经网络在累积性环境风险评价中的应用［J］. 环境监控与预警, 2012,4(2):1-6. [2] 袁永才,李术才,李利平,等. 岩溶隧道施工过程中大型溶洞的综合预报及治理方案研究［J］. 现代隧道技术, 2015, 52(2)：192-197. [3] 李奎, 高波. 岩溶区隧道岩溶发育规律与岩溶洞穴探测［J］. 西部探矿工程, 2005(10):107-110. [4] 李术才, 刘斌, 孙怀凤,等. 隧道施工超前地质预报研究现状及发展趋势［J］. 岩石力学与工程学报, 2014, 33(6):1090-1113. [5] 何晓群. 多元统计分析［M］. 北京：中国人民大学出版社，2012:135. [6] 韩力群. 人工神经网络教程［M］. 北京：北京邮电大学出版社，2006:58-75. [7] 葛颜慧,李术才,张庆松,等. 基于风险评价的隧道综合超前地质预报技术研究［J］. 岩土工程学报, 2010，32（7）：1124-1130. [8] 陈小前, 罗世彬, 王振国,等. BP神经网络应用中的前后处理过程研究［J］. 系统工程理论与实践, 2004, 22(1):65-70. [9] 王永刚, 李辉. 基于灰色神经网络的民航事故征候预测模型研究［J］. 中国安全科学学报, 2012, 22(3):10-15. [10] 陈伟, 马如雄, 郝艳红. 基于MATLAB的BP人工神经网络设计［J］. 智能计算机与应用, 2005(2):30-31. -
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