Gravity Anomaly Correction(GAC)is a very important term in leveling data processing.In most cases,it is troublesome for field surveyors to measure gravity when leveling.In this paper,based on the complete Bouguer Grav...Gravity Anomaly Correction(GAC)is a very important term in leveling data processing.In most cases,it is troublesome for field surveyors to measure gravity when leveling.In this paper,based on the complete Bouguer Gravity Anomaly(BGA)map of WGM2012,the feasibility of replacing in-situ gravity surveying in China is investigated.For leveling application,that is to evaluate the accuracy of WGM2012 in China.Because WGM2012 is organized with a standard rectangle grid,two interpolation methods,bilinear interpolating and Inverse Distance Weighted(IDW)interpolating,are proposed.Four sample areas in China,i.e.,Hanzhong,Chengdu,Linzhi and Shantou,are selected to evaluate the systems bias and precision of WGM2012.Numerical results show the average system bias of WGM2012 BGA in west China is about-100.1 mGal(1 mGal=10^(-5) m/s^(2))and the standard deviation is about 30.7 mGal.Tests in Shantou indicate the system bias in plain areas is about-130.4 mGal and standard deviation is about 6.8 mGal.All these experiments means the accuracy of WGM2012 is limited in high mountain areas of western China,but in plain areas,such as Shantou,WGM2012 BGA map is quite good for most leveling applications after calibrating the system bias.展开更多
To alleviate the distortion of XRII X-ray image intensifier images in the C-arm CT computer tomography imaging system an algorithm based on the Delaunay triangulation interpolation is proposed.First the causes of the ...To alleviate the distortion of XRII X-ray image intensifier images in the C-arm CT computer tomography imaging system an algorithm based on the Delaunay triangulation interpolation is proposed.First the causes of the phenomenon the classical correction algorithms and the Delaunay triangulation interpolation are analyzed.Then the algorithm procedure is explained using flow charts and illustrations. Finally experiments are described to demonstrate its effectiveness and feasibility. Experimental results demonstrate that the Delaunay triangulation interpolation can have the following effects.In the case of the same center the root mean square distances RMSD and standard deviation STD between the corrected image with Delaunay triangulation interpolation and the ideal image are 5.760 4 ×10 -14 and 5.354 2 ×10 -14 respectively.They increase to 1.790 3 2.388 8 2.338 8 and 1.262 0 1.268 1 1.202 6 after applying the quartic polynomial model L1 and model L2 to the distorted images respectively.The RMSDs and STDs between the corrected image with the Delaunay triangulation interpolation and the ideal image are 2.489 × 10 -13 and 2.449 8 ×10 -13 when their centers do not coincide. When the quartic polynomial model L1 and model L2 are applied to the distorted images they are 1.770 3 2.388 8 2.338 8 and 1.269 9 1.268 1 1.202 6 respectively.展开更多
In this research, we present a seismic trace interpolation method which uses seismic data with surface-related multiples. It is different from conventional seismic data interpolation using information transformation o...In this research, we present a seismic trace interpolation method which uses seismic data with surface-related multiples. It is different from conventional seismic data interpolation using information transformation or extrapolation of adjacent channels for reconstruction of missing seismic data. In this method there are two steps, first, we construct pseudo-primaries by cross-correlation of surface multiple data to extract the missing near- offset information in multiples, which are not displayed in the acquired seismic record. Second, we correct the pseudo-primaries by applying a Least-squares Matching Filter （LMF） and RMS amplitude correction method in time and space sliding windows. Then the corrected pseudo-primaries can be used to fill the data gaps. The method is easy to implement, without the need to separate multiples and primaries. It extracts the seismic information contained by multiples for filling missing traces. The method is suitable for seismic data with surfacerelated multiples.展开更多
Numerical models and correct predictions are important for marine forecasting,but the forecasting results are often unable to satisfy the requirements of operational wave forecasting.Because bias between the predictio...Numerical models and correct predictions are important for marine forecasting,but the forecasting results are often unable to satisfy the requirements of operational wave forecasting.Because bias between the predictions of numerical models and the actual sea state has been observed,predictions can only be released after correction by forecasters.This paper proposes a spati-otemporal interactive processing bias correction method to correct numerical prediction fields applied to the production and release of operational ocean wave forecasting products.The proposed method combines the advantages of numerical models and Forecast Discussion;specifically,it integrates subjective and objective information to achieve interactive spatiotemporal correc-tions for numerical prediction.The method corrects the single-time numerical prediction field in space by spatial interpolation and sub-zone numerical analyses using numerical model grid data in combination with real-time observations and the artificial judg-ment of forecasters to achieve numerical prediction accuracy.The difference between the original numerical prediction field and the spatial correction field is interpolated to an adjacent time series by successive correction analysis,thereby achieving highly efficient correction for multi-time forecasting fields.In this paper,the significant wave height forecasts from the European Centre for Medium-Range Weather Forecasts are used as background field for forecasting correction and analysis.Results indicate that the proposed method has good application potential for the bias correction of numerical predictions under different sea states.The method takes into account spatial correlations for the numerical prediction field and the time series development of the numerical model to correct numerical predictions efficiently.展开更多
The shortage of current different approaches of the vehicle license plate(VLP) tilt correction is analyzed in the paper and a new rotary correction method put forward based on the former ways of the VLP tilt correctio...The shortage of current different approaches of the vehicle license plate(VLP) tilt correction is analyzed in the paper and a new rotary correction method put forward based on the former ways of the VLP tilt correction in the horizontal direction and the vertical direction Owing to the VLP tilt taking place in the vertical direction,the array of the image’s pixels of the same column is broken,and even different rows come into being superposition.The VLP tilt taking place in the horizontal direction,by which the array of the image’s pixels of the same row broken,and so much as different columns come into being superposition.展开更多
针对广域分布式新能源普遍缺乏新能源资源监测装置,而导致功率预测精度不足的问题,提出一种基于气象资源插值与迁移学习的广域分布式光伏功率预测方法。首先,基于地理信息和粗颗粒气象数据,对广域范围下的气象资源数据进行网格化插值;其...针对广域分布式新能源普遍缺乏新能源资源监测装置,而导致功率预测精度不足的问题,提出一种基于气象资源插值与迁移学习的广域分布式光伏功率预测方法。首先,基于地理信息和粗颗粒气象数据,对广域范围下的气象资源数据进行网格化插值;其次,依据插值结果对具有相同气象特征的光伏电站进行自组织映射(self-organizing maps,SOM)网络聚类,并对每一类中的光伏电站进行迁移学习的源域和目标域的划分,以保证预测精度;然后,结合长短期记忆(long short term memory,LSTM)网络,引入误差修正环节,建立源域至目标域的双迁移模型;最后,以浙江省绍兴市的分布式光伏电站为实例验证该方法的有效性。相比于对各个光伏电站单独建模,所提方法能将目标域光伏电站的训练速度提高10倍以上,且在预测精度方面也有显著提升,具有一定的推广应用价值。展开更多
使用均值生成函数、标准正态均一性检验方法和相关分析等方法对我国东部地区96个观测站1931—2020年夏季降水量长年代资料进行了一系列插补、检验、订正及效果分析等工作。结果表明:(1)均值生成函数拟合的1931—2020年各站夏季降水量资...使用均值生成函数、标准正态均一性检验方法和相关分析等方法对我国东部地区96个观测站1931—2020年夏季降水量长年代资料进行了一系列插补、检验、订正及效果分析等工作。结果表明:(1)均值生成函数拟合的1931—2020年各站夏季降水量资料的整体趋势和极值与观测值均有较好的一致性,其中无缺测资料的6个站点观测值和拟合值在距平符号一致率上达到了86.1%,可以满足插补工作的需要。(2)对1931—1950年和1951—2020年2个时段的夏季降水量资料,用平均值和方差2个统计量对插补后的资料进行差异性检验,共有8站具有显著性差异。(3)对插补后的1931—2020年夏季降水量资料进行了均一性检验和均一化订正,其中13站存在非均一性。(4)将订正后的站点资料与CRU_TS4.05(University of East Anglia Climatic Research Unit Global 0.5°Monthly Time Series)数据库的格点资料进行空间分布相似度分析,2套资料在1931—1950、1951—2020和1931—2020年这3个时段的空间相关系数分别达到了0.90,0.92和0.92,空间分布较一致,订正后的资料具有一定的可靠性。展开更多
基金“Wings of Quality”Program of QICS(No.2020-zlzy-015)。
文摘Gravity Anomaly Correction(GAC)is a very important term in leveling data processing.In most cases,it is troublesome for field surveyors to measure gravity when leveling.In this paper,based on the complete Bouguer Gravity Anomaly(BGA)map of WGM2012,the feasibility of replacing in-situ gravity surveying in China is investigated.For leveling application,that is to evaluate the accuracy of WGM2012 in China.Because WGM2012 is organized with a standard rectangle grid,two interpolation methods,bilinear interpolating and Inverse Distance Weighted(IDW)interpolating,are proposed.Four sample areas in China,i.e.,Hanzhong,Chengdu,Linzhi and Shantou,are selected to evaluate the systems bias and precision of WGM2012.Numerical results show the average system bias of WGM2012 BGA in west China is about-100.1 mGal(1 mGal=10^(-5) m/s^(2))and the standard deviation is about 30.7 mGal.Tests in Shantou indicate the system bias in plain areas is about-130.4 mGal and standard deviation is about 6.8 mGal.All these experiments means the accuracy of WGM2012 is limited in high mountain areas of western China,but in plain areas,such as Shantou,WGM2012 BGA map is quite good for most leveling applications after calibrating the system bias.
基金The Natural Science Foundation of Anhui Province(No.1308085MF96)the Project of Chuzhou University(No.2012qd06,2011kj010B)+1 种基金the Scientific Research Foundation of Education Department of Anhui Province(No.KJ2014A186)the National Basic Research Program of China(973 Program)(No.2010CB732503)
文摘To alleviate the distortion of XRII X-ray image intensifier images in the C-arm CT computer tomography imaging system an algorithm based on the Delaunay triangulation interpolation is proposed.First the causes of the phenomenon the classical correction algorithms and the Delaunay triangulation interpolation are analyzed.Then the algorithm procedure is explained using flow charts and illustrations. Finally experiments are described to demonstrate its effectiveness and feasibility. Experimental results demonstrate that the Delaunay triangulation interpolation can have the following effects.In the case of the same center the root mean square distances RMSD and standard deviation STD between the corrected image with Delaunay triangulation interpolation and the ideal image are 5.760 4 ×10 -14 and 5.354 2 ×10 -14 respectively.They increase to 1.790 3 2.388 8 2.338 8 and 1.262 0 1.268 1 1.202 6 after applying the quartic polynomial model L1 and model L2 to the distorted images respectively.The RMSDs and STDs between the corrected image with the Delaunay triangulation interpolation and the ideal image are 2.489 × 10 -13 and 2.449 8 ×10 -13 when their centers do not coincide. When the quartic polynomial model L1 and model L2 are applied to the distorted images they are 1.770 3 2.388 8 2.338 8 and 1.269 9 1.268 1 1.202 6 respectively.
基金sponsored by:the National Basic Research Program of China (973 Program) (2007CB209605)the National Natural Science Foundation of China (40974073)the National Hi-tech Research and Development Program of China (863 Program) (2009AA06Z206)
文摘In this research, we present a seismic trace interpolation method which uses seismic data with surface-related multiples. It is different from conventional seismic data interpolation using information transformation or extrapolation of adjacent channels for reconstruction of missing seismic data. In this method there are two steps, first, we construct pseudo-primaries by cross-correlation of surface multiple data to extract the missing near- offset information in multiples, which are not displayed in the acquired seismic record. Second, we correct the pseudo-primaries by applying a Least-squares Matching Filter （LMF） and RMS amplitude correction method in time and space sliding windows. Then the corrected pseudo-primaries can be used to fill the data gaps. The method is easy to implement, without the need to separate multiples and primaries. It extracts the seismic information contained by multiples for filling missing traces. The method is suitable for seismic data with surfacerelated multiples.
基金supported by the National Key Research and Development Program of China(No.2018YFC1407002)the National Natural Science Foundation of China(Nos.62071279,41930535)the SDUST Research Fund(No.2019TDJH103).
文摘Numerical models and correct predictions are important for marine forecasting,but the forecasting results are often unable to satisfy the requirements of operational wave forecasting.Because bias between the predictions of numerical models and the actual sea state has been observed,predictions can only be released after correction by forecasters.This paper proposes a spati-otemporal interactive processing bias correction method to correct numerical prediction fields applied to the production and release of operational ocean wave forecasting products.The proposed method combines the advantages of numerical models and Forecast Discussion;specifically,it integrates subjective and objective information to achieve interactive spatiotemporal correc-tions for numerical prediction.The method corrects the single-time numerical prediction field in space by spatial interpolation and sub-zone numerical analyses using numerical model grid data in combination with real-time observations and the artificial judg-ment of forecasters to achieve numerical prediction accuracy.The difference between the original numerical prediction field and the spatial correction field is interpolated to an adjacent time series by successive correction analysis,thereby achieving highly efficient correction for multi-time forecasting fields.In this paper,the significant wave height forecasts from the European Centre for Medium-Range Weather Forecasts are used as background field for forecasting correction and analysis.Results indicate that the proposed method has good application potential for the bias correction of numerical predictions under different sea states.The method takes into account spatial correlations for the numerical prediction field and the time series development of the numerical model to correct numerical predictions efficiently.
文摘The shortage of current different approaches of the vehicle license plate(VLP) tilt correction is analyzed in the paper and a new rotary correction method put forward based on the former ways of the VLP tilt correction in the horizontal direction and the vertical direction Owing to the VLP tilt taking place in the vertical direction,the array of the image’s pixels of the same column is broken,and even different rows come into being superposition.The VLP tilt taking place in the horizontal direction,by which the array of the image’s pixels of the same row broken,and so much as different columns come into being superposition.
文摘针对广域分布式新能源普遍缺乏新能源资源监测装置,而导致功率预测精度不足的问题,提出一种基于气象资源插值与迁移学习的广域分布式光伏功率预测方法。首先,基于地理信息和粗颗粒气象数据,对广域范围下的气象资源数据进行网格化插值;其次,依据插值结果对具有相同气象特征的光伏电站进行自组织映射(self-organizing maps,SOM)网络聚类,并对每一类中的光伏电站进行迁移学习的源域和目标域的划分,以保证预测精度;然后,结合长短期记忆(long short term memory,LSTM)网络,引入误差修正环节,建立源域至目标域的双迁移模型;最后,以浙江省绍兴市的分布式光伏电站为实例验证该方法的有效性。相比于对各个光伏电站单独建模,所提方法能将目标域光伏电站的训练速度提高10倍以上,且在预测精度方面也有显著提升,具有一定的推广应用价值。
文摘使用均值生成函数、标准正态均一性检验方法和相关分析等方法对我国东部地区96个观测站1931—2020年夏季降水量长年代资料进行了一系列插补、检验、订正及效果分析等工作。结果表明:(1)均值生成函数拟合的1931—2020年各站夏季降水量资料的整体趋势和极值与观测值均有较好的一致性,其中无缺测资料的6个站点观测值和拟合值在距平符号一致率上达到了86.1%,可以满足插补工作的需要。(2)对1931—1950年和1951—2020年2个时段的夏季降水量资料,用平均值和方差2个统计量对插补后的资料进行差异性检验,共有8站具有显著性差异。(3)对插补后的1931—2020年夏季降水量资料进行了均一性检验和均一化订正,其中13站存在非均一性。(4)将订正后的站点资料与CRU_TS4.05(University of East Anglia Climatic Research Unit Global 0.5°Monthly Time Series)数据库的格点资料进行空间分布相似度分析,2套资料在1931—1950、1951—2020和1931—2020年这3个时段的空间相关系数分别达到了0.90,0.92和0.92,空间分布较一致,订正后的资料具有一定的可靠性。
