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滑坡是世界上最主要的地质灾害类型之一.滑坡的监测和防治仍是当前国内外学者研究的重点,尤其是滑坡变形的预测和预报.卡尔曼滤波已广泛应用于滑坡变形监测数据处理中,且自适应卡尔曼滤波已经很好地解决了传统卡尔曼滤波发散的问题.但在分析降雨型滑坡变形的过程中,降雨(地下水位)对滑坡体的影响不容忽视.因此,引入降雨量因子,提出顾及... 相似文献
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滑坡灰色模型的模型误差主要来自降雨量、温度等外界影响因子,传统的半参数灰色模型没有考虑这些对滑坡变形影响较大的外界因子,而把相邻时刻的模型误差当作是不变的,预测精度较低。针对这一问题,该文提出了将这些影响因子当作非参数变量引入模型,通过改进正规矩阵来建立半参数改进灰色模型,可以得到更加准确的模型误差,并且能够将其补偿到观测序列中,使预测结果更加准确。计算结果表明,本文所述模型在观测序列的拟合和预测中均有较好的结果,能够充分地利用在滑坡中采集到的各种信息,并且达到更优的结果。 相似文献
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本文根据神经网络的基本原理,利用实测数据建立了用于大断面隧道收敛变形预测的BP神经网络模型。基于神经网络的预测模型具有预测精度高,使用方便灵活,适合于复杂系统的特点,是解决隧道变形预测问题的一种崭新途径。 相似文献
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徐进军 《武汉测绘科技大学学报》1997,22(4):355-357
综合分析和比较了自回归模型和回归模型的特点,提出了采用线性综合模型来预报崩滑体变形的思想,以弥补自回归模型或回归模型预报的不足,实测资料的处理结果表明,综合线性模型具有特别的适用性。 相似文献
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滑坡变形程度是判断处治后滑坡是否稳定的关键评价指标,开展处治后滑坡变形预测可提前掌握滑坡稳定性情况,有利于滑坡失稳风险分析,便于开展地质灾害防灾减灾工作。为了准确预测处治后滑坡变形情况,本文提出了一种采用鸟群算法(BSA)优化BP神经网络的滑坡变形预测方法,借助BSA-BP神经网络构建了广西某高速公路滑坡变形预测模型,对比分析了BSA-BP神经网络与BP神经网络的预测结果。结果表明,BSA-BP神经网络预测结果的均方误差和相关系数分别为0.053 4和0.997 6,BP神经网络预测结果的均方误差和相关系数分别为2.225 6和0.968,鸟群算法可有效提高BP神经网络模型的预测精度,能有效应用于处治后滑坡变形预测,研究结果可为处治后滑坡失稳风险预测提供参考。 相似文献
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There are various occasions where simple, ordinary, and universal kriging techniques may find themselves incapa- ble of performing spatial prediction directly or efficiently. One type of application concerns quantification of cumulative distribution function (CDF) or probability of occurrences of categorical variables over space. The other is related to optimal use of co-variation inherent to multiple regionalized variables as well as spatial correlation in spatial prediction. This paper extends geostatistics from the realm of kriging with uni-variate and continuous regionalized variables to the territory of indicator and multivariate kriging, where it is of ultimate importance to perform non-parametric estimation of probability distributions and spatial prediction based on co-regionalization and multiple data sources, respectively. 相似文献
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王晓颖 《测绘与空间地理信息》2017,(3)
BP神经网络模型是一种经典的预测模型,被广泛应用于变形分析预测的各个领域。本文采用一定方法以进一步改进BP神经网络模型,并通过灰色Verhulst-BP模型分析软基处理地基的实例数据,结合Matlab语言,编程比较分析预测及实测的数据,得出结果证明改进灰色Verhulst-BP模型的分析预测精度较高,比较适合于建筑地基变形的预测分析。 相似文献
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Emre Ozelkan Gang Chen Burak Berk Ustundag 《International Journal of Digital Earth》2016,9(8):733-747
Spatial interpolation (SI) is currently one of the most common ways to estimate wind speed (Ws). However, classic SI models either ignore the complex geography [e.g. inverse distance weighting (IDW)], or demand high computational resources (e.g. cokriging). This study aimed to develop a simple yet effective SI model for estimating Ws in Eastern Thrace of Turkey. This new method, named MIDW(Ws), is a modified IDW through the integration of IDW with wind profile model, power law (PL), representing the influence of land cover and topography on Ws. Terrain features and elevation data of PL were obtained using normalized difference vegetation index (NDVI) and digital elevation model (DEM), respectively. Results showed superior and comparable performance of MIDW(Ws) to standard IDW and ordinary kriging (OK) across all months of year. Compared to ordinary cokriging (OCK) using DEM as covariate, MIDW(Ws) generated better results in the arid–semiarid seasons (around summer). Local complex atmospheric conditions during rainy seasons (around winter) may have affected the performance of incorporating PL with MIDW(Ws). Generally, the proposed MIDW(Ws) is simpler and easier to implement compared to OCK. For landscape-scale projects, its high computational efficiency and relatively robust performance show potential to deal with large volumes of datasets. 相似文献
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基于二维直接线性变换的数字相机畸变模型的建立 总被引:10,自引:3,他引:10
提出并论证了基于二维直接线性变换的畸变的校正方法。本方法特别适用于各类固态摄像机(CCD、CID、PSD)的畸变模型的建立,以补偿各类像点系统误差。 相似文献
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针对遥感图像融合Brovey变换法存在颜色失真的现象,提出了一种低通比值融合法。该融合方法首先对高几何分辨率的全色波段进行低通滤波,然后将低分辨率多光谱图像与全色波段图像相乘,再除以滤波后的全色波段图像,便得到融合图像。从辐照的角度证明了该低通比值融合法具备理论基础,并从目视评价、定量分析、分类精度证实了该低通比值融合法优于Brovey变换法。该低通比值融合法是一种能较好地保全低分辨率多光谱图像颜色的融合方法。 相似文献
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This paper describes a procedure for extending local statistics to categorical spatial data. The approach is based on the notion that there are two fundamental characteristics of categorical spatial data; composition and configuration. Further, it is argued that, when considered locally, the latter should be measured conditionally with respect to the former. These ideas are developed for binary, gridded data. Local composition is measured by counting the numbers of cells of a particular type, while local configuration is measured by join counts. The approach is illustrated using a small, empirical data set and an ad hoc procedure is developed to deal with the impact of global spatial autocorrelation on the local statistics.The author gratefully acknowledges financial support from the GEOIDE Network of Centres of Excellence (ENV #4) and the helpful comments of three anonymous reviewers. 相似文献