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   

自动高精度测距系统     

张学庄  张驰 《大地测量与地球动力学》1996,(1)

介绍了自动高精度测距系统。该系统能以５×１０－７的测距精度测定多个观测点的形变，可作为跨断层动态连续观测的新仪器。  相似文献   

含有集约束向量极值问题的最优性条件     

吴泽忠 《成都信息工程学院学报》2004,19(2):258-262

在序线性拓扑空间里研究了含有集约束向量极值问题的最优性条件,并建立了充分性和必要性条件.  相似文献   

The Hubble constant from the gravitational lens CLASS B0218+357 using the Advanced Camera for Surveys     

T. York  N. Jackson  I. W. A. Browne  O. Wucknitz  J. E. Skelton † 《Monthly notices of the Royal Astronomical Society》2005,357(1):124-134

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Geometric Derivation of the Delaunay Variables and Geometric Phases     

Dong Eui Chang  Jerrold E. Marsden 《Celestial Mechanics and Dynamical Astronomy》2003,86(2):185-208

We derive the classical Delaunay variables by finding a suitable symmetry action of the three torus T³ on the phase space of the Kepler problem, computing its associated momentum map and using the geometry associated with this structure. A central feature in this derivation is the identification of the mean anomaly as the angle variable for a symplectic S ¹ action on the union of the non-degenerate elliptic Kepler orbits. This approach is geometrically more natural than traditional ones such as directly solving Hamilton–Jacobi equations, or employing the Lagrange bracket. As an application of the new derivation, we give a singularity free treatment of the averaged J ₂-dynamics (the effect of the bulge of the Earth) in the Cartesian coordinates by making use of the fact that the averaged J ₂-Hamiltonian is a collective Hamiltonian of the T³ momentum map. We also use this geometric structure to identify the drifts in satellite orbits due to the J ₂ effect as geometric phases.  相似文献   

89C51实现光电经纬仪摄影机目标距离的显示     

毛耀  肖天明  包启亮 《成都信息工程学院学报》2003,18(1):79-82

介绍一种以89C51为核心，通过AD和LED，实现光电经纬仪摄影机目标距离显示的方法。该方法提出了一些新的设计方案，从而使整个系统结构简单，运行可靠。  相似文献   

Does time dilation tell us the distance to gamma-ray bursts?     

Ralph A. M. J. Wijers 《Astrophysics and Space Science》1995,231(1-2):399-402

Since the discovery that dim gamma-ray bursts last longer on average than bright ones (time dilation) the cosmological origin of this effect has been contested by various researchers. I discuss the current status of this issue and conclude that current models for a non-cosmological time dilation only explain part of the observed phenomenon, and even then betray themselves by distinct signatures in the data. As those signatures have not been seen, the cosmological origin remains the favoured explanation of the time dilation.  相似文献   

GPS变形监测平差计算及不确定度分析     

苗胜军  蔡美峰  任奋华  欧阳振华 《岩土力学》2008,29(2):562-566

全球定位系统（GPS）是一种全天候、高精度的连续定位系统,它以速度快、方法灵活多样、操作简便等优势被广泛应用于工程测量和变形监测中。结合水厂铁矿GPS边坡变形监测实例,对GPS监测网的星历预报、基线向量平差计算、网平差计算、结果及残差不确定度进行了细致分析研究,以验证GPS技术在边坡变形监测中的可靠性和精度。  相似文献   

基于AGA的SVM需水预测模型研究   总被引：1，自引：0，他引：1  

张灵  陈晓宏  刘丙军  王兆礼 《水文》2008,28(1):38-42,46

需水预测是一个由城市人口、工业水平、社会经济水平共同作用的多因素、多层次的复杂非线性系统.其结果将直接影响受区域水资源承载力约束的产业结构、布局形态等决策.作为一种集中参数预报方法,支持向量机方法具有对未来样本的较好的泛化性能,对于这类资料缺乏、系统结构尚欠清晰的问题可以取得较好的模拟和预测结果.基于此,本文将支持向量机方法引入需水预测领域,建立了需水预测支持向量机模型.同时,本文将加速遗传算法和支持向量机方法耦合起来,构造了支持向量机模型参数的自适应优化算法.模型在珠海市的应用实例表明:与简单遗传算法比较,AGA的模型参数寻优效率更高;与BP神经网络模型相比,SVM模型较好地解决了小样本、经验性等问题,并取得了较高的预测精度.  相似文献   

Prediction of local scour around circular piles under waves using a novel artificial intelligence approach     

Iman Ahmadianfar  Xuefeng Chu 《Marine Georesources & Geotechnology》2021,39(1):44-55

Abstract

The scour phenomena around vertical piles in oceans and under waves may influence the structure stability. Therefore, accurately predicting the scour depth is an important task in the design of piles. Empirical approaches often do not provide the required accuracy compared with data mining methods for modeling such complex processes. The main objective of this study is to develop three data-driven methods, locally weighted linear regression (LWLR), support vector machine (SVR), and multivariate linear regression (MLR) to predict the scour depth around vertical piles due to waves in a sand bed. It is the first effort to develop the LWLR to predict scour depth around vertical piles. The models simulate the scour depth mainly based on Shields parameter, pile Reynolds number, grain Reynolds number, Keulegan–Carpenter number, and sediment number. 111 laboratory datasets, derived from several experimental studies, were used for the modeling. The results indicated that the LWLR provided highly accurate predictions of the scour depths around piles (R?=?0.939 and RMSE = 0.075). Overall, this study demonstrated that the LWLR can be used as a valuable tool to predict the wave-induced scour around piles.  相似文献