基于PSR-WSVM模型的边坡位移预测     

李建新  刘小生  肖钢  周文  刘仁志 《大地测量与地球动力学》2020,40(6):577-580

为建立高精度的边坡位移预测模型，采用相空间重构（PSR）将边坡位移时间序列数据转换为多维数据，同时构造小波核函数改进的支持向量机模型，建立PSR-WSVM模型并应用于边坡位移预测。将PSR-WSVM模型预测结果与传统支持向量机（SVM）模型、小波支持向量机（WSVM）模型和基于相空间重构的支持向量机（PSR-SVM）模型预测结果进行对比，通过平均绝对误差（MAE）、平均绝对误差百分比（MAPE）和均方根误差（RMSE）3个精度评价指标验证PSR-WSVM模型的可行性。工程实例结果表明，PSR-WSVM模型预测结果的3个精度评价指标都优于另外3种模型，边坡位移预测的精度明显提升。  相似文献   

A machine learning approach for predicting computational intensity and domain decomposition in parallel geoprocessing     

Peng Yue  Fan Gao  Boyi Shangguan  Zheren Yan 《International journal of geographical information science》2020,34(11):2243-2274

ABSTRACT

High performance computing is required for fast geoprocessing of geospatial big data. Using spatial domains to represent computational intensity (CIT) and domain decomposition for parallelism are prominent strategies when designing parallel geoprocessing applications. Traditional domain decomposition is limited in evaluating the computational intensity, which often results in load imbalance and poor parallel performance. From the data science perspective, machine learning from Artificial Intelligence (AI) shows promise for better CIT evaluation. This paper proposes a machine learning approach for predicting computational intensity, followed by an optimized domain decomposition, which divides the spatial domain into balanced subdivisions based on the predicted CIT to achieve better parallel performance. The approach provides a reference framework on how various machine learning methods including feature selection and model training can be used in predicting computational intensity and optimizing parallel geoprocessing against different cases. Some comparative experiments between the approach and traditional methods were performed using the two cases, DEM generation from point clouds and spatial intersection on vector data. The results not only demonstrate the advantage of the approach, but also provide hints on how traditional GIS computation can be improved by the AI machine learning.  相似文献   

一种有发展前景的隧道及井巷超前预报技术——电磁导弹探测技术     

李貅  薛国强 《地球科学与环境学报》2002,24(1):12-14

对于隧道和煤矿井巷的安全掘进 ,超前预报显得特别重要。但由于掌子面前的特殊环境限制及多种干扰的严重影响 ,给隧道及井巷超前预报技术的研究带来许多困难。在瞬变电磁理论的基础上 ,引入新的电磁传播理论———电磁导弹技术 ,作为对该技术的初步探索 ,文章论证了该技术在隧道超前预报中应用的可能性 ,并提出了研究的主要内容和发展方向以及可能取得的新的技术突破和技术支撑  相似文献   

隧道工程地质评价的内容和方法   总被引：2，自引：0，他引：2  

陈新建  孙琳  李新星  孙巧银 《地球科学与环境学报》2004,26(1):41-45

结合工程隧道实际,首先阐述了隧道工程的基本地质环境和工程地质条件,然后针对隧道工程可能出现的不良地质现象和可采取的工程措施,从大气降水、围岩稳定、围岩压力、洞口稳定、隧道比选等角度探讨隧道工程地质评价的主要方法和一般内容,进行隧道工程地质评价,为隧道施工、支护提供了依据.  相似文献   

Automatic Determination of Stellar Atmospheric Parameters Using Neural Networks and Instance-Based Machine Learning     

Olac Fuentes 《Experimental Astronomy》2001,12(1):21-31

In this article we show how machine learning methods can beeffectively applied to the problem of automatically predictingstellar atmospheric parameters from spectral information, a veryimportant problem in stellar astronomy. We apply feedforwardneural networks, Kohonen's self-organizing maps andlocally-weighted regression to predict the stellar atmosphericparameters effective temperature, surface gravity and metallicityfrom spectral indices. Our experimental results show that thethree methods are capable of predicting the parameters with verygood accuracy. Locally weighted regression gives slightly betterresults than the other methods using the original dataset asinput, while self-organizing maps outperform the other methods when significant amounts of noise are added. We also implemented a heterogeneous ensemble of predictors, combining the results given by the three algorithms. This ensemble yields better results than any of the three algorithms alone, using both the original and the noisy data.  相似文献   

Prediction of Stellar Atmospheric Parameters using Instance-Based Machine Learning and Genetic Algorithms   总被引：1，自引：0，他引：1  

J. Federico Ramírez  Olac Fuentes  Ravi K. Gulati 《Experimental Astronomy》2001,12(3):163-178

In this article we present a method for the automated prediction of stellar atmospheric parameters from spectral indices. This method uses a genetic algorithm (GA) for the selection of relevant spectral indices and prototypical stars and predicts their properties, using the k-nearest neighbors method (KNN). We have applied the method to predict the effective temperature, surface gravity, metallicity, luminosity class and spectral class of stars from spectral indices. Our experimental results show that the feature selection performed by the genetic algorithm reduces the running time of KNN up to 92%, and the predictive accuracy error up to 35%. This revised version was published online in July 2006 with corrections to the Cover Date.  相似文献   

A 3D finite element simulation model for TBM tunnelling in soft ground     

Thomas Kasper  Günther Meschke 《国际地质力学数值与分析法杂志》2004,28(14):1441-1460

  相似文献   

美国的地下空间开发和利用     

康宁 《浙江国土资源》2001,17(1):67-72

通过对美国地下空间开发利用的考察,认为有如下特点,第一,结合城市建设,构筑地下铁道,第二立足于战略,建立水下通路,第三,地下空间的开发利用平战结合.这些方法对我国的地下空间开发利用值得借鉴.  相似文献   

瞬变电磁法探测公路隧道工程中的不良地质构造     

薛国强  宋建平  武军杰  刘社华 《地球科学与环境学报》2003,25(4):73-75

为了给公路设计部门提供选线依据,运用瞬变电磁法在山西境内的某两条高速公路隧道工程设计线路段上进行探测,以查明下覆不良地质构造的发育情况.通过对瞬变电磁法的探测能力进行理论上的讨论,对不同地电断面情况下的异常体电磁响应的定性分析,得出用瞬变电磁法探测不良地质体的可行性结论.经过资料处理,查出不良地质构造赋存的位置,解释结果与钻探资料完全吻合.  相似文献   

TBM在不良地质洞条件下的施工技术          下载免费PDF全文

刘大军  张益忠 《探矿工程》2008,35(10):60-65

TBM掘进机以其快速、高效、安全、优质等优点越来越广泛地被应用于隧洞开挖施工中,尤其更适用于深埋超长隧洞,然而在不良地质洞段中TBM掘进缓慢,甚至有卡刀可能,反而不如钻爆法灵活,这就需要根据围岩性状采取特殊技术处理措施,辅以监控量测手段对支护方案进行验证、调整支护措施、修正设计参数等。结合辽宁大伙房输水隧洞工程,总结了在不良地质洞条件下的超前地质预报方法、不良地质段处理措施以及围岩变形监测方法。  相似文献