| 基于Monte Carlo-BP神经网络TBM掘进速度预测 |
| |
| 引用本文： | 温森,赵延喜,杨圣奇.基于Monte Carlo-BP神经网络TBM掘进速度预测[J].岩土力学,2009,30(10):3127-3132. |
| |
| 作者姓名： | 温森 赵延喜 杨圣奇 |
| |
| 作者单位： | 河海大学,岩土力学与堤坝工程教育部重点实验室,南京,210098;河海大学,岩土工程科学研究所,南京,210098 |
| |
| 基金项目： | 国家十一五科技支撑项目 |
| |
| 摘 要： | 预测隧道工程中TBM掘进速度，主要有完全经验的、半理论半经验的模型和人工智能等方法，所用参数均为确定性的，未考虑参数存在的随机性，故导致预测结果的不准确性。基于此，提出了Monte Carlo-BP神经网络TBM掘进速度预测模型，着重考虑了一些重要输入参数的随机性, 其中输入参数重要性的大小通过粗糙集进行计算排序。采用Monte Carlo产生随机数时，由于参量的样本数据的有限，分布函数均采用阶梯形经验分布函数。如果采用的数据是来自不同类型的 TBM，则应当考虑机器性能参数，并重新对参数重要性进行排序。实例计算表明，Monte Carlo-BP神经网络模型预测结果和实测值总体趋势和均值比较一致。
|
| 关 键 词： | TBM掘进速度 Monte Carlo-BP神经网络 参数重要性 粗糙集 |
| 收稿时间： | 2008-05-09 |
Prediction on penetration rate of TBM based on Monte Carlo-BP neural network |
| |
| WEN Sen,ZHAO Yan-xi,YANG Sheng-qi.Prediction on penetration rate of TBM based on Monte Carlo-BP neural network[J].Rock and Soil Mechanics,2009,30(10):3127-3132. |
| |
| Authors: | WEN Sen ZHAO Yan-xi YANG Sheng-qi |
| |
| Institution: | 1. Key Laboratory of Ministry of Education for Geomechanics and Embankment Engineering, Hohai University, Nanjing 210098, China; 2. Geotechnical Research Institute, Hohai University, Nanjing 210098, China |
| |
| Abstract: | Penetration rate of TBM is mainly predicted by fully empirical, semi-theoretical, semi-empirical models and artificial intelligence in engineering. The parameters used in these models are all deterministic and their uncertainties are neglected, so it leads to inaccuracy of the results. Because of this, a Monte Carlo-BP network model is proposed and the uncertainty of some important parameters are considered in this model. The importance of each parameter is calculated by rough set. Due to the limit of sample data, stepped empirical distributed function is used when Monte Carlo is used to produce random numbers. If sample data are not from the same type TBM, the TBM performance parameters should be considered and the importance of parameters should be calculated again. It is proved that the calculated results of proposed model are in accordance with measured results. |
| |
| Keywords: | penetration rate of TBM Monte Carlo-BP neural network the importance of parameters rough set |
| 本文献已被 万方数据 等数据库收录！ |
| 点击此处可从《岩土力学》浏览原始摘要信息 |
| 点击此处可从《岩土力学》下载免费的PDF全文 |
|
