The joint roughness coefficient(JRC) is one of the key parameters for evaluating the shear strength of rock joints.Because of the scale effect in the JRC,reliable JRC values are of great importance for most rock engin...The joint roughness coefficient(JRC) is one of the key parameters for evaluating the shear strength of rock joints.Because of the scale effect in the JRC,reliable JRC values are of great importance for most rock engineering projects.During the collection process of JRC samples,the redundancy or insufficiency of representative rock joint surface topography(RJST) information in serial length JRC samples is the essential reason that affects the reliability of the scale effect results.Therefore,this paper proposes an adaptive sampling method,in which we use the entropy consistency measure Q(a) to evaluate the consistency of the joint morphology information contained in adjacent JRC samples.Then the sampling interval is automatically adjusted according to the threshold Q(at) of the entropy consistency measure to ensure that the degree of change of RJST information between JRC samples is the same,and ultimately makes the representative RJST information in the collected JRC samples more balanced.The application results of actual cases show that the proposed method can obtain the scale effect in the JRC efficiently and reliably.展开更多
When dealing with imbalanced datasets,the traditional support vectormachine(SVM)tends to produce a classification hyperplane that is biased towards the majority class,which exhibits poor robustness.This paper proposes...When dealing with imbalanced datasets,the traditional support vectormachine(SVM)tends to produce a classification hyperplane that is biased towards the majority class,which exhibits poor robustness.This paper proposes a high-performance classification algorithm specifically designed for imbalanced datasets.The proposed method first uses a biased second-order cone programming support vectormachine(B-SOCP-SVM)to identify the support vectors(SVs)and non-support vectors(NSVs)in the imbalanced data.Then,it applies the synthetic minority over-sampling technique(SV-SMOTE)to oversample the support vectors of the minority class and uses the random under-sampling technique(NSV-RUS)multiple times to undersample the non-support vectors of the majority class.Combining the above-obtained minority class data set withmultiple majority class datasets can obtainmultiple new balanced data sets.Finally,SOCP-SVM is used to classify each data set,and the final result is obtained through the integrated algorithm.Experimental results demonstrate that the proposed method performs excellently on imbalanced datasets.展开更多
Currently,the main idea of iterative rendering methods is to allocate a fixed number of samples to pixels that have not been fully rendered by calculating the completion rate.It is obvious that this strategy ignores t...Currently,the main idea of iterative rendering methods is to allocate a fixed number of samples to pixels that have not been fully rendered by calculating the completion rate.It is obvious that this strategy ignores the changes in pixel values during the previous rendering process,which may result in additional iterative operations.展开更多
Combining the advantages of the stratified sampling and the importance sampling, a stratified importance sampling method （SISM） is presented to analyze the reliability sensitivity for structure with multiple failure...Combining the advantages of the stratified sampling and the importance sampling, a stratified importance sampling method （SISM） is presented to analyze the reliability sensitivity for structure with multiple failure modes. In the presented method, the variable space is divided into several disjoint subspace by n-dimensional coordinate planes at the mean point of the random vec- tor, and the importance sampling functions in the subspaces are constructed by keeping the sampling center at the mean point and augmenting the standard deviation by a factor of 2. The sample size generated from the importance sampling function in each subspace is determined by the contribution of the subspace to the reliability sensitivity, which can be estimated by iterative simulation in the sampling process. The formulae of the reliability sensitivity estimation, the variance and the coefficient of variation are derived for the presented SISM. Comparing with the Monte Carlo method, the stratified sampling method and the importance sampling method, the presented SISM has wider applicability and higher calculation efficiency, which is demonstrated by numerical examples. Finally, the reliability sensitivity analysis of flap structure is illustrated that the SISM can be applied to engineering structure.展开更多
The vertical distribution and migration of Cu,Zn,Pb,and Cd in two forest soil profiles near an industrial emission source were investigated using a high resolution sampling method together with reference element Ti.On...The vertical distribution and migration of Cu,Zn,Pb,and Cd in two forest soil profiles near an industrial emission source were investigated using a high resolution sampling method together with reference element Ti.One-meter soil profile was sectioned horizontally at 2 cm intervals in the first 40 cm,5 cm intervals in the next 40 cm,and 10 cm intervals in the last 20 cm.The migration distance and rate of heavy metals in the soil profiles were calculated according to their relative concentrations in the profiles,as calibrated by the reference element Ti.The enrichment of heavy metals appeared in the uppermost layer of the forest soil,and the soil heavy metal concentrations decreased down the profile until reaching their background values.The calculated average migration rates of Cd,Cu,Pb,and Zn were 0.70,0.33,0.37,and 0.76 cm year-1,respectively,which were comparable to other methods.A simulation model was proposed,which could well describe the distribution of Cu,Zn,Pb,and Cd in natural forest soils.展开更多
Based on the observation of importance sampling and second order information about the failure surface of a structure, an importance sampling region is defined in V-space which is obtained by rotating a U-space at the...Based on the observation of importance sampling and second order information about the failure surface of a structure, an importance sampling region is defined in V-space which is obtained by rotating a U-space at the point of maximum likelihood. The sampling region is a hyper-ellipsoid that consists of the sampling ellipse on each plane of main curvature in V-space. Thus, the sampling probability density function can be constructed by the sampling region center and ellipsoid axes. Several examples have shown the efficiency and generality of this method.展开更多
One of the basic parameters in forest management planning is detailed knowledge of growing stock,information collected by forest inventory.Sampling methods must be accurate,inexpensive,and be easy to implement in the ...One of the basic parameters in forest management planning is detailed knowledge of growing stock,information collected by forest inventory.Sampling methods must be accurate,inexpensive,and be easy to implement in the field.This study presents a new sampling method called branching transect for use in the Iranian Zagros forests and similar forests.Features of the new method include greater accuracy,easy implementation in nature,simplicity of statistical calculations,and low cost.In this method,transect is used,which includes some subtransects(side branches).The length of the main transect,side branches,number of trees measured in each side branch,and the number of sub-branches in this method are changeable based on homogeneity,heterogeneity,and density of a forest.In this study,based on the density and heterogeneity of the forest area studied,20-m transects with four and eight side branches were used.Sampling plots(Transects)in four inventory networks(100 m×100 m,100 m×150 m,150 m×150 m and 100 m×200 m)were implemented in the GIS environment.The results of this sampling method were compared to the results of total inventory(100%count)in terms of accuracy,precision(t-test),and inventory error percentage.Branching transect results were statistially similar to total inventory counts in all cases.The results show that this method of estimating density and canopy per hectare can be used in Zagros forests and similar forests.展开更多
Graph convolutional networks(GCNs)have received significant attention from various research fields due to the excellent performance in learning graph representations.Although GCN performs well compared with other meth...Graph convolutional networks(GCNs)have received significant attention from various research fields due to the excellent performance in learning graph representations.Although GCN performs well compared with other methods,it still faces challenges.Training a GCN model for large-scale graphs in a conventional way requires high computation and storage costs.Therefore,motivated by an urgent need in terms of efficiency and scalability in training GCN,sampling methods have been proposed and achieved a significant effect.In this paper,we categorize sampling methods based on the sampling mechanisms and provide a comprehensive survey of sampling methods for efficient training of GCN.To highlight the characteristics and differences of sampling methods,we present a detailed comparison within each category and further give an overall comparative analysis for the sampling methods in all categories.Finally,we discuss some challenges and future research directions of the sampling methods.展开更多
A stratified sampling Monte Carlo method to analyze the reliability of structural systems is presented. Introducing a small exploratory simulation, this method overcomes the difficulties for getting the systematic sam...A stratified sampling Monte Carlo method to analyze the reliability of structural systems is presented. Introducing a small exploratory simulation, this method overcomes the difficulties for getting the systematic sampling probability of all the strata. Several useful and efficient stratification methods are given and the strategies of stratification and simulation are studied. A general conclusion has been presented corresponding to actual engineering structures. The strict theoretical proof has been given,and it is especially effective to solve probabilistic integration. Statistic error of evaluating failure probability is reduced obviously. Especially in highly non-linear and nonreonvex problems, it is more accurate than other methods. Compared with other variance reduction techniques, this method can obtain a more obvious variance reduction and an increased sampling efficiency. Moreover, without strict limiting condition, it is convenient to use. This method is especially suitable to solve the reliability problem of structural systems with multiple failure modes and highly non-linear safety margin equations.展开更多
In this paper, we consider the inverse scattering by chiral obstacle in electromagnetic fields, and prove that the linear sampling method is also effective to determine the support of a chiral obstacle from the noisy ...In this paper, we consider the inverse scattering by chiral obstacle in electromagnetic fields, and prove that the linear sampling method is also effective to determine the support of a chiral obstacle from the noisy far field data.展开更多
Background:The local pivotal method(LPM)utilizing auxiliary data in sample selection has recently been proposed as a sampling method for national forest inventories(NFIs).Its performance compared to simple random samp...Background:The local pivotal method(LPM)utilizing auxiliary data in sample selection has recently been proposed as a sampling method for national forest inventories(NFIs).Its performance compared to simple random sampling(SRS)and LPM with geographical coordinates has produced promising results in simulation studies.In this simulation study we compared all these sampling methods to systematic sampling.The LPM samples were selected solely using the coordinates(LPMxy)or,in addition to that,auxiliary remote sensing-based forest variables(RS variables).We utilized field measurement data(NFI-field)and Multi-Source NFI(MS-NFI)maps as target data,and independent MS-NFI maps as auxiliary data.The designs were compared using relative efficiency(RE);a ratio of mean squared errors of the reference sampling design against the studied design.Applying a method in NFI also requires a proven estimator for the variance.Therefore,three different variance estimators were evaluated against the empirical variance of replications:1)an estimator corresponding to SRS;2)a Grafström-Schelin estimator repurposed for LPM;and 3)a Matérn estimator applied in the Finnish NFI for systematic sampling design.Results:The LPMxy was nearly comparable with the systematic design for the most target variables.The REs of the LPM designs utilizing auxiliary data compared to the systematic design varied between 0.74–1.18,according to the studied target variable.The SRS estimator for variance was expectedly the most biased and conservative estimator.Similarly,the Grafström-Schelin estimator gave overestimates in the case of LPMxy.When the RS variables were utilized as auxiliary data,the Grafström-Schelin estimates tended to underestimate the empirical variance.In systematic sampling the Matérn and Grafström-Schelin estimators performed for practical purposes equally.Conclusions:LPM optimized for a specific variable tended to be more efficient than systematic sampling,but all of the considered LPM designs were less efficient than the systematic sampling design for some target variables.The Grafström-Schelin estimator could be used as such with LPMxy or instead of the Matérn estimator in systematic sampling.Further studies of the variance estimators are needed if other auxiliary variables are to be used in LPM.展开更多
Uniform linear array(ULA)radars are widely used in the collision-avoidance radar systems of small unmanned aerial vehicles(UAVs).In practice,a ULA's multi-target direction of arrival(DOA)estimation performance suf...Uniform linear array(ULA)radars are widely used in the collision-avoidance radar systems of small unmanned aerial vehicles(UAVs).In practice,a ULA's multi-target direction of arrival(DOA)estimation performance suffers from significant performance degradation owing to the limited number of physical elements.To improve the underdetermined DOA estimation performance of a ULA radar mounted on a small UAV platform,we propose a nonuniform linear motion sampling underdetermined DOA estimation method.Using the motion of the UAV platform,the echo signal is sampled at different positions.Then,according to the concept of difference co-array,a virtual ULA with multiple array elements and a large aperture is synthesized to increase the degrees of freedom(DOFs).Through position analysis of the original and motion arrays,we propose a nonuniform linear motion sampling method based on ULA for determining the optimal DOFs.Under the condition of no increase in the aperture of the physical array,the proposed method obtains a high DOF with fewer sampling runs and greatly improves the underdetermined DOA estimation performance of ULA.The results of numerical simulations conducted herein verify the superior performance of the proposed method.展开更多
We consider the interior inverse scattering problem for recovering the shape of a penetrable partially coated cavity with external obstacles from the knowledge of measured scattered waves due to point sources.In the f...We consider the interior inverse scattering problem for recovering the shape of a penetrable partially coated cavity with external obstacles from the knowledge of measured scattered waves due to point sources.In the first part,we obtain the well-posedness of the direct scattering problem by the variational method.In the second part,we establish the mathematical basis of the linear sampling method to recover both the shape of the cavity,and the shape of the external obstacle,however the exterior transmission eigenvalue problem also plays a key role in the discussion of this paper.展开更多
In this paper,by combining sampling methods for food statistics with years of sample sampling experience,various sampling points and corresponding sampling methods are summarized.It hopes to discover food safety risks...In this paper,by combining sampling methods for food statistics with years of sample sampling experience,various sampling points and corresponding sampling methods are summarized.It hopes to discover food safety risks and improve the level of food safety.展开更多
The accuracy of spatial interpolation of precipitation data is determined by the actual spatial variability of the precipitation, the interpolation method, and the distribution of observatories whose selections are pa...The accuracy of spatial interpolation of precipitation data is determined by the actual spatial variability of the precipitation, the interpolation method, and the distribution of observatories whose selections are particularly important. In this paper, three spatial sampling programs, including spatial random sampling, spatial stratified sampling, and spatial sandwich sampling, are used to analyze the data from meteorological stations of northwestern China. We compared the accuracy of ordinary Kriging interpolation methods on the basis of the sampling results. The error values of the regional annual pre-cipitation interpolation based on spatial sandwich sampling, including ME （0.1513）, RMSE （95.91）, ASE （101.84）, MSE （？0.0036）, and RMSSE （1.0397）, were optimal under the premise of abundant prior knowledge. The result of spatial stratified sampling was poor, and spatial random sampling was even worse. Spatial sandwich sampling was the best sampling method, which minimized the error of regional precipitation estimation. It had a higher degree of accuracy compared with the other two methods and a wider scope of application.展开更多
In this study, for accuracy and cost an optimal inventory method was examined and introduced to obtain information about Zagros forests, Iran. For this purpose,three distance sampling methods(compound, order distance ...In this study, for accuracy and cost an optimal inventory method was examined and introduced to obtain information about Zagros forests, Iran. For this purpose,three distance sampling methods(compound, order distance and random-pairs) in 5 inventory networks(100 m × 100 m, 100 m × 150 m, 100 m × 200 m,150 m × 150 m, 200 m × 200 m) were implemented in GIS environment, and the related statistical analyses were carried out. Average tree density and canopy cover in hectare with 100% inventory were compared to each other.All the studied methods were implemented in 30 inventory points, and the implementation time of each was recorded.According to the results, the best inventory methods for estimating density and canopy cover were compound150 m × 150 m and 100 m × 100 m methods, respectively. The minimum amount of product inventory time per second(T), and(E%)2 square percent of inventory error of sampling for the compound 150 m × 150 m method regarding density in hectare was 691.8, and for the compound 100 m × 100 m method regarding canopy of 12,089 ha. It can be concluded that compound method is the best for estimating density and canopy features of the forests area.展开更多
This paper proposes a new method for increasing the precision in survey sam- pling, i.e., a method combining sampling with prediction. The two cases where auxiliary information is or not available are considered. A nu...This paper proposes a new method for increasing the precision in survey sam- pling, i.e., a method combining sampling with prediction. The two cases where auxiliary information is or not available are considered. A numerical example is given.展开更多
A new approach applying fuzzy mathematic theorems, including the Primary Matrix Element Theorem and the Fisher Classification Method, was established to solve the optimization problem of atmospheric environmental samp...A new approach applying fuzzy mathematic theorems, including the Primary Matrix Element Theorem and the Fisher Classification Method, was established to solve the optimization problem of atmospheric environmental sampling sites. According to its basis, an application in the optimization of sampling sites in the atmospheric environmental monitoring was discussed. The method was proven to be suitable and effective. The results were admitted and applied by the Environmental Protection Bureau (EPB) of many cities of China. A set of computer software of this approach was also completely compiled and used.展开更多
The aim of this paper is to compare sample quality across two probability samples and one that uses probabilistic cluster sampling combined with random route and quota sampling within the selected clusters in order to...The aim of this paper is to compare sample quality across two probability samples and one that uses probabilistic cluster sampling combined with random route and quota sampling within the selected clusters in order to define the ultimate survey units. All of them use the face-to-face interview as the survey procedure. The hypothesis to be tested is that it is possible to achieve the same degree of representativeness using a combination of random route sampling and quota sampling (with substitution) as it can be achieved by means of household sampling (without substitution) based on the municipal register of inhabitants. We have found such marked differences in the age and gender distribution of the probability sampling, where the deviations exceed 6%. A different picture emerges when it comes to comparing the employment variables, where the quota sampling overestimates the economic activity rate (2.5%) and the unemployment rate (8%) and underestimates the employment rate (3.46%).展开更多
基金supported by the National Natural Science Foundation of China(No.42207175)。
文摘The joint roughness coefficient(JRC) is one of the key parameters for evaluating the shear strength of rock joints.Because of the scale effect in the JRC,reliable JRC values are of great importance for most rock engineering projects.During the collection process of JRC samples,the redundancy or insufficiency of representative rock joint surface topography(RJST) information in serial length JRC samples is the essential reason that affects the reliability of the scale effect results.Therefore,this paper proposes an adaptive sampling method,in which we use the entropy consistency measure Q(a) to evaluate the consistency of the joint morphology information contained in adjacent JRC samples.Then the sampling interval is automatically adjusted according to the threshold Q(at) of the entropy consistency measure to ensure that the degree of change of RJST information between JRC samples is the same,and ultimately makes the representative RJST information in the collected JRC samples more balanced.The application results of actual cases show that the proposed method can obtain the scale effect in the JRC efficiently and reliably.
基金supported by the Natural Science Basic Research Program of Shaanxi(Program No.2024JC-YBMS-026).
文摘When dealing with imbalanced datasets,the traditional support vectormachine(SVM)tends to produce a classification hyperplane that is biased towards the majority class,which exhibits poor robustness.This paper proposes a high-performance classification algorithm specifically designed for imbalanced datasets.The proposed method first uses a biased second-order cone programming support vectormachine(B-SOCP-SVM)to identify the support vectors(SVs)and non-support vectors(NSVs)in the imbalanced data.Then,it applies the synthetic minority over-sampling technique(SV-SMOTE)to oversample the support vectors of the minority class and uses the random under-sampling technique(NSV-RUS)multiple times to undersample the non-support vectors of the majority class.Combining the above-obtained minority class data set withmultiple majority class datasets can obtainmultiple new balanced data sets.Finally,SOCP-SVM is used to classify each data set,and the final result is obtained through the integrated algorithm.Experimental results demonstrate that the proposed method performs excellently on imbalanced datasets.
基金supported partially by the National Natural Science Foundation of China(No.U19A2063)the Jilin Provincial Science&Technology Development Program of China(No.20230201080GX)。
文摘Currently,the main idea of iterative rendering methods is to allocate a fixed number of samples to pixels that have not been fully rendered by calculating the completion rate.It is obvious that this strategy ignores the changes in pixel values during the previous rendering process,which may result in additional iterative operations.
基金National Natural Science Foundation of China (10572117,10802063,50875213)Aeronautical Science Foundation of China (2007ZA53012)+1 种基金New Century Program For Excellent Talents of Ministry of Education of China (NCET-05-0868)National High-tech Research and Development Program (2007AA04Z401)
文摘Combining the advantages of the stratified sampling and the importance sampling, a stratified importance sampling method （SISM） is presented to analyze the reliability sensitivity for structure with multiple failure modes. In the presented method, the variable space is divided into several disjoint subspace by n-dimensional coordinate planes at the mean point of the random vec- tor, and the importance sampling functions in the subspaces are constructed by keeping the sampling center at the mean point and augmenting the standard deviation by a factor of 2. The sample size generated from the importance sampling function in each subspace is determined by the contribution of the subspace to the reliability sensitivity, which can be estimated by iterative simulation in the sampling process. The formulae of the reliability sensitivity estimation, the variance and the coefficient of variation are derived for the presented SISM. Comparing with the Monte Carlo method, the stratified sampling method and the importance sampling method, the presented SISM has wider applicability and higher calculation efficiency, which is demonstrated by numerical examples. Finally, the reliability sensitivity analysis of flap structure is illustrated that the SISM can be applied to engineering structure.
基金the National Natural Science Foundation of China (No40625001)the Knowledge Innovation Pro-gram of the Chinese Academy of Sciences (NoKZCX2-YW-409)the Jiangsu Provincial Natural Science Foundation of China (NoBK2004167)
文摘The vertical distribution and migration of Cu,Zn,Pb,and Cd in two forest soil profiles near an industrial emission source were investigated using a high resolution sampling method together with reference element Ti.One-meter soil profile was sectioned horizontally at 2 cm intervals in the first 40 cm,5 cm intervals in the next 40 cm,and 10 cm intervals in the last 20 cm.The migration distance and rate of heavy metals in the soil profiles were calculated according to their relative concentrations in the profiles,as calibrated by the reference element Ti.The enrichment of heavy metals appeared in the uppermost layer of the forest soil,and the soil heavy metal concentrations decreased down the profile until reaching their background values.The calculated average migration rates of Cd,Cu,Pb,and Zn were 0.70,0.33,0.37,and 0.76 cm year-1,respectively,which were comparable to other methods.A simulation model was proposed,which could well describe the distribution of Cu,Zn,Pb,and Cd in natural forest soils.
文摘Based on the observation of importance sampling and second order information about the failure surface of a structure, an importance sampling region is defined in V-space which is obtained by rotating a U-space at the point of maximum likelihood. The sampling region is a hyper-ellipsoid that consists of the sampling ellipse on each plane of main curvature in V-space. Thus, the sampling probability density function can be constructed by the sampling region center and ellipsoid axes. Several examples have shown the efficiency and generality of this method.
文摘One of the basic parameters in forest management planning is detailed knowledge of growing stock,information collected by forest inventory.Sampling methods must be accurate,inexpensive,and be easy to implement in the field.This study presents a new sampling method called branching transect for use in the Iranian Zagros forests and similar forests.Features of the new method include greater accuracy,easy implementation in nature,simplicity of statistical calculations,and low cost.In this method,transect is used,which includes some subtransects(side branches).The length of the main transect,side branches,number of trees measured in each side branch,and the number of sub-branches in this method are changeable based on homogeneity,heterogeneity,and density of a forest.In this study,based on the density and heterogeneity of the forest area studied,20-m transects with four and eight side branches were used.Sampling plots(Transects)in four inventory networks(100 m×100 m,100 m×150 m,150 m×150 m and 100 m×200 m)were implemented in the GIS environment.The results of this sampling method were compared to the results of total inventory(100%count)in terms of accuracy,precision(t-test),and inventory error percentage.Branching transect results were statistially similar to total inventory counts in all cases.The results show that this method of estimating density and canopy per hectare can be used in Zagros forests and similar forests.
基金supported by the National Natural Science Foundation of China(61732018,61872335,61802367,61876215)the Strategic Priority Research Program of Chinese Academy of Sciences(XDC05000000)+1 种基金Beijing Academy of Artificial Intelligence(BAAI),the Open Project Program of the State Key Laboratory of Mathematical Engineering and Advanced Computing(2019A07)the Open Project of Zhejiang Laboratory,and a grant from the Institute for Guo Qiang,Tsinghua University.Recommended by Associate Editor Long Chen.
文摘Graph convolutional networks(GCNs)have received significant attention from various research fields due to the excellent performance in learning graph representations.Although GCN performs well compared with other methods,it still faces challenges.Training a GCN model for large-scale graphs in a conventional way requires high computation and storage costs.Therefore,motivated by an urgent need in terms of efficiency and scalability in training GCN,sampling methods have been proposed and achieved a significant effect.In this paper,we categorize sampling methods based on the sampling mechanisms and provide a comprehensive survey of sampling methods for efficient training of GCN.To highlight the characteristics and differences of sampling methods,we present a detailed comparison within each category and further give an overall comparative analysis for the sampling methods in all categories.Finally,we discuss some challenges and future research directions of the sampling methods.
文摘A stratified sampling Monte Carlo method to analyze the reliability of structural systems is presented. Introducing a small exploratory simulation, this method overcomes the difficulties for getting the systematic sampling probability of all the strata. Several useful and efficient stratification methods are given and the strategies of stratification and simulation are studied. A general conclusion has been presented corresponding to actual engineering structures. The strict theoretical proof has been given,and it is especially effective to solve probabilistic integration. Statistic error of evaluating failure probability is reduced obviously. Especially in highly non-linear and nonreonvex problems, it is more accurate than other methods. Compared with other variance reduction techniques, this method can obtain a more obvious variance reduction and an increased sampling efficiency. Moreover, without strict limiting condition, it is convenient to use. This method is especially suitable to solve the reliability problem of structural systems with multiple failure modes and highly non-linear safety margin equations.
文摘In this paper, we consider the inverse scattering by chiral obstacle in electromagnetic fields, and prove that the linear sampling method is also effective to determine the support of a chiral obstacle from the noisy far field data.
基金the Ministry of Agriculture and Forestry key project“Puuta liikkeelle ja uusia tuotteita metsästä”(“Wood on the move and new products from forest”)Academy of Finland(project numbers 295100 , 306875).
文摘Background:The local pivotal method(LPM)utilizing auxiliary data in sample selection has recently been proposed as a sampling method for national forest inventories(NFIs).Its performance compared to simple random sampling(SRS)and LPM with geographical coordinates has produced promising results in simulation studies.In this simulation study we compared all these sampling methods to systematic sampling.The LPM samples were selected solely using the coordinates(LPMxy)or,in addition to that,auxiliary remote sensing-based forest variables(RS variables).We utilized field measurement data(NFI-field)and Multi-Source NFI(MS-NFI)maps as target data,and independent MS-NFI maps as auxiliary data.The designs were compared using relative efficiency(RE);a ratio of mean squared errors of the reference sampling design against the studied design.Applying a method in NFI also requires a proven estimator for the variance.Therefore,three different variance estimators were evaluated against the empirical variance of replications:1)an estimator corresponding to SRS;2)a Grafström-Schelin estimator repurposed for LPM;and 3)a Matérn estimator applied in the Finnish NFI for systematic sampling design.Results:The LPMxy was nearly comparable with the systematic design for the most target variables.The REs of the LPM designs utilizing auxiliary data compared to the systematic design varied between 0.74–1.18,according to the studied target variable.The SRS estimator for variance was expectedly the most biased and conservative estimator.Similarly,the Grafström-Schelin estimator gave overestimates in the case of LPMxy.When the RS variables were utilized as auxiliary data,the Grafström-Schelin estimates tended to underestimate the empirical variance.In systematic sampling the Matérn and Grafström-Schelin estimators performed for practical purposes equally.Conclusions:LPM optimized for a specific variable tended to be more efficient than systematic sampling,but all of the considered LPM designs were less efficient than the systematic sampling design for some target variables.The Grafström-Schelin estimator could be used as such with LPMxy or instead of the Matérn estimator in systematic sampling.Further studies of the variance estimators are needed if other auxiliary variables are to be used in LPM.
基金National Natural Science Foundation of China(61973037)National 173 Program Project(2019-JCJQ-ZD-324)。
文摘Uniform linear array(ULA)radars are widely used in the collision-avoidance radar systems of small unmanned aerial vehicles(UAVs).In practice,a ULA's multi-target direction of arrival(DOA)estimation performance suffers from significant performance degradation owing to the limited number of physical elements.To improve the underdetermined DOA estimation performance of a ULA radar mounted on a small UAV platform,we propose a nonuniform linear motion sampling underdetermined DOA estimation method.Using the motion of the UAV platform,the echo signal is sampled at different positions.Then,according to the concept of difference co-array,a virtual ULA with multiple array elements and a large aperture is synthesized to increase the degrees of freedom(DOFs).Through position analysis of the original and motion arrays,we propose a nonuniform linear motion sampling method based on ULA for determining the optimal DOFs.Under the condition of no increase in the aperture of the physical array,the proposed method obtains a high DOF with fewer sampling runs and greatly improves the underdetermined DOA estimation performance of ULA.The results of numerical simulations conducted herein verify the superior performance of the proposed method.
基金supported by the Natural Science Foundation of Xinjiang Uygur Autonomous Region of China(2019D01A05)supported by the NSFC(11571132)。
文摘We consider the interior inverse scattering problem for recovering the shape of a penetrable partially coated cavity with external obstacles from the knowledge of measured scattered waves due to point sources.In the first part,we obtain the well-posedness of the direct scattering problem by the variational method.In the second part,we establish the mathematical basis of the linear sampling method to recover both the shape of the cavity,and the shape of the external obstacle,however the exterior transmission eigenvalue problem also plays a key role in the discussion of this paper.
文摘In this paper,by combining sampling methods for food statistics with years of sample sampling experience,various sampling points and corresponding sampling methods are summarized.It hopes to discover food safety risks and improve the level of food safety.
基金conducted within the National Major Scientific Research Project (No. 2013CBA01806)the National Natural Science Foundation of China (No. 41271085)the National Scientific and Technological Support Project (No. 2013BAB05B03)
文摘The accuracy of spatial interpolation of precipitation data is determined by the actual spatial variability of the precipitation, the interpolation method, and the distribution of observatories whose selections are particularly important. In this paper, three spatial sampling programs, including spatial random sampling, spatial stratified sampling, and spatial sandwich sampling, are used to analyze the data from meteorological stations of northwestern China. We compared the accuracy of ordinary Kriging interpolation methods on the basis of the sampling results. The error values of the regional annual pre-cipitation interpolation based on spatial sandwich sampling, including ME （0.1513）, RMSE （95.91）, ASE （101.84）, MSE （？0.0036）, and RMSSE （1.0397）, were optimal under the premise of abundant prior knowledge. The result of spatial stratified sampling was poor, and spatial random sampling was even worse. Spatial sandwich sampling was the best sampling method, which minimized the error of regional precipitation estimation. It had a higher degree of accuracy compared with the other two methods and a wider scope of application.
文摘In this study, for accuracy and cost an optimal inventory method was examined and introduced to obtain information about Zagros forests, Iran. For this purpose,three distance sampling methods(compound, order distance and random-pairs) in 5 inventory networks(100 m × 100 m, 100 m × 150 m, 100 m × 200 m,150 m × 150 m, 200 m × 200 m) were implemented in GIS environment, and the related statistical analyses were carried out. Average tree density and canopy cover in hectare with 100% inventory were compared to each other.All the studied methods were implemented in 30 inventory points, and the implementation time of each was recorded.According to the results, the best inventory methods for estimating density and canopy cover were compound150 m × 150 m and 100 m × 100 m methods, respectively. The minimum amount of product inventory time per second(T), and(E%)2 square percent of inventory error of sampling for the compound 150 m × 150 m method regarding density in hectare was 691.8, and for the compound 100 m × 100 m method regarding canopy of 12,089 ha. It can be concluded that compound method is the best for estimating density and canopy features of the forests area.
基金Supported by the National Natural Science Foundation of China
文摘This paper proposes a new method for increasing the precision in survey sam- pling, i.e., a method combining sampling with prediction. The two cases where auxiliary information is or not available are considered. A numerical example is given.
文摘A new approach applying fuzzy mathematic theorems, including the Primary Matrix Element Theorem and the Fisher Classification Method, was established to solve the optimization problem of atmospheric environmental sampling sites. According to its basis, an application in the optimization of sampling sites in the atmospheric environmental monitoring was discussed. The method was proven to be suitable and effective. The results were admitted and applied by the Environmental Protection Bureau (EPB) of many cities of China. A set of computer software of this approach was also completely compiled and used.
文摘The aim of this paper is to compare sample quality across two probability samples and one that uses probabilistic cluster sampling combined with random route and quota sampling within the selected clusters in order to define the ultimate survey units. All of them use the face-to-face interview as the survey procedure. The hypothesis to be tested is that it is possible to achieve the same degree of representativeness using a combination of random route sampling and quota sampling (with substitution) as it can be achieved by means of household sampling (without substitution) based on the municipal register of inhabitants. We have found such marked differences in the age and gender distribution of the probability sampling, where the deviations exceed 6%. A different picture emerges when it comes to comparing the employment variables, where the quota sampling overestimates the economic activity rate (2.5%) and the unemployment rate (8%) and underestimates the employment rate (3.46%).
