Twenty-one typical coupled large samples were chosen from areas within and surrounding nature reserves on the Tibetan Plateau using the large sample comparison method(LSCM).To evaluate the effectiveness of the nature ...Twenty-one typical coupled large samples were chosen from areas within and surrounding nature reserves on the Tibetan Plateau using the large sample comparison method(LSCM).To evaluate the effectiveness of the nature reserves in protecting the ecological environment,the alpine grassland net primary production(NPP) of these coupled samples were compared and the differences between them before and after their establishment as protected areas were analyzed.The results showed that:(1) With respect to the alpine grassland NPP,the ecological and environmental conditions of most nature reserves were more fragile than those of the surrounding areas and also lower than the average values for the Tibetan Plateau.(2) Of the 11 typical nature reserves selected,the positive trend in the NPP for Manzetang was the most significant,whereas there was no obvious trend in Taxkorgan.With the exception of Selincuo,the annual NPP growth rate in the nature reserves covered by alpine meadow and wetland was higher than that in nature reserves consisting of alpine steppe and alpine desert.(3) There were notable findings in 21 typical coupled samples:(a) After the establishment of the nature reserves,the annual rate of increase in the NPP in 76% of samples inside nature reserves and 82% of samples inside national nature reserves was higher than that of the corresponding samples outside nature reserves.(b) The effectiveness of ecological protection of the Mid-Kunlun,Changshagongma,Zoige and Selincuo(Selin Co) nature reserves was significant; the effectiveness of protection was relatively sig-nificant in most parts of the Sanjiangyuan and Qiangtang nature reserves,whereas in south-east Manzetang and north Taxkorgan the protection effectiveness was not obvious.(c) The ecological protection effectiveness was significant in nature reserves consisting of alpine meadow,but was weak in nature reserves covered by alpine steppe.This study also shows that the advantage of large sample comparison method in evaluating regional ecology change.Careful design of the samples used,to ensure comparability between the samples,is crucial to the success of this LSCM.展开更多
Unsaturated loess in natural sites loses stability as the overburden load continuously increases.Traditional soil modifiers such as cement and fly ash affect the surrounding environment.A new type of material,i.e.,lig...Unsaturated loess in natural sites loses stability as the overburden load continuously increases.Traditional soil modifiers such as cement and fly ash affect the surrounding environment.A new type of material,i.e.,lignin,is environmentally friendly and able to increase the strength of loess.However,the engineering characteristics of the improved loess under unsaturated conditions are not yet clear.In this study,the soil-water characteristic curves(SWCCs)of lignin-improved loess samples were determined from 0 kPa to 700 kPa using a pressure plate instrument,and then,they were fitted using the van Genuchten(VG)model and the Fredlund and Xing(FX)model.In addition,the effects of the lignin content and sample preparation methods on the SWCCs were investigated to determine the optimal lignin content and a suitable sample preparation method for loess foundations.As the lignin content increases,the matric suction and residual water content of the improved loess increase.The suction stress increases with the increasing lignin contents of 1%–2%.At lignin contents of 3%–4%,the suction stress begins to decrease and the samples prepared using the slurry method has a lower suction stress than that prepared using the wet mixing method.The air entry value(AEV)increases with increasing lignin content.In addition,scanning electron microscopy(SEM)was used to investigate the microstructural variations.It was found that after the addition of lignin,the entrapment of the loess particles by the lignin fibers created some larger particles and smaller pore diameters,which in turn led to poor connectivity of the loess pores.These changes cause the matric suction of the modified loess to increase.展开更多
An improved analytical method to determine the content of 52 major, minor and trace elements in marine geological samples, using a HF-HCl-HNO_3 acid system with a high-pressure closed digestion method（HPCD）, is stud...An improved analytical method to determine the content of 52 major, minor and trace elements in marine geological samples, using a HF-HCl-HNO_3 acid system with a high-pressure closed digestion method（HPCD）, is studied by an inductively coupled plasma optical emission spectrometry（ICP-OES） and an inductively coupled plasma mass spectrometry（ICP-MS）. The operating parameters of the instruments are optimized, and the optimal analytical parameters are determined. The influences of optical spectrum and mass spectrum interferences, digestion methods and acid systems on the analytical results are investigated. The optimal spectral lines and isotopes are chosen, and internal standard element of rhodium is selected to compensate for matrix effects and analytical signals drifting. Compared with the methods of an electric heating plate digestion and a microwave digestion, a high-pressure closed digestion method is optimized with less acid, complete digestion,less damage for digestion process. The marine geological samples are dissolved completely by a HF-HCl-HNO_3 system, the relative error（RE） for the analytical results are all less than 6.0%. The method detection limits are 2–40μg/g by the ICP-OES, and 6–80 ng/g by ICP-MS. The methods are used to determine the marine sediment reference materials（GBW07309, GBW07311, GBW07313）, rock reference materials（GBW07103, GBW07104,GBW07105）, and cobalt-rich crust reference materials（GBW07337, GBW07338, GBW07339）, the obtained analytical results are in agreement with the certified values, and both of the relative standard deviation（RSD） and the relative error（RE） are less than 6.0%. The analytical method meets the requirements for determining 52 elements contents of bulk marine geological samples.展开更多
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
Landslide susceptibility mapping(LSM) is crucial for reducing disaster risk in complex mountainous regions. This study evaluated the impact of various sampling methods on the accuracy of LSM over the next decade in Bi...Landslide susceptibility mapping(LSM) is crucial for reducing disaster risk in complex mountainous regions. This study evaluated the impact of various sampling methods on the accuracy of LSM over the next decade in Bijie City, Guizhou Province, China. Datasets were collected from 614 landslides and 500 non-landslides, and four sampling methods were proposed. Recurrent Neural Network(RNN), Gated Recurrent Unit(GRU), K-Nearest Neighbor(KNN), and Extreme Gradient Boosting(XGB) models were assessed utilising 15 metrics(Elevation, Slope, Aspect, Plan curvature, Profile curvature, Stream Power Index, Sediment Transport Index, Vector Ruggedness Measurement, Topographic Roughness Index, Lithology, Land use, Normalized Difference Vegetation Index(NDVI), Rainfall, Distance from Road, Distance from River). The results demonstrated that the GRU model combined with a 5-m sample boundary from the interior of the landslide and non-landslide areas exhibited superior performance with F1, Accuracy, and Area Under Curve(AUC) scores of 0.9700, 0.9450, and 0.8925, respectively. LSM will be projected for the next decade by coupling the Geophysical Fluid Dynamics Laboratory Earth System Model version 4(GFDLESM4) with the Shared Socioeconomic Pathway(SSP119). This study provides valuable insights into landslide risk management in landslide-prone areas.展开更多
This paper proposes a non-intrusive computational method for mechanical dynamic systems involving a large-scale of interval uncertain parameters,aiming to reduce the computational costs and improve accuracy in determi...This paper proposes a non-intrusive computational method for mechanical dynamic systems involving a large-scale of interval uncertain parameters,aiming to reduce the computational costs and improve accuracy in determining bounds of system response.The screening method is firstly used to reduce the scale of active uncertain parameters.The sequential high-order polynomials surrogate models are then used to approximate the dynamic system’s response at each time step.To reduce the sampling cost of constructing surrogate model,the interaction effect among uncertain parameters is gradually added to the surrogate model by sequentially incorporating samples from a candidate set,which is composed of vertices and inner grid points.Finally,the points that may produce the bounds of the system response at each time step are searched using the surrogate models.The optimization algorithm is used to locate extreme points,which contribute to determining the inner points producing system response bounds.Additionally,all vertices are also checked using the surrogate models.A vehicle nonlinear dynamic model with 72 uncertain parameters is presented to demonstrate the accuracy and efficiency of the proposed uncertain computational method.展开更多
Unmanned Aerial Vehicles(UAVs)play a vital role in military warfare.In a variety of battlefield mission scenarios,UAVs are required to safely fly to designated locations without human intervention.Therefore,finding a ...Unmanned Aerial Vehicles(UAVs)play a vital role in military warfare.In a variety of battlefield mission scenarios,UAVs are required to safely fly to designated locations without human intervention.Therefore,finding a suitable method to solve the UAV Autonomous Motion Planning(AMP)problem can improve the success rate of UAV missions to a certain extent.In recent years,many studies have used Deep Reinforcement Learning(DRL)methods to address the AMP problem and have achieved good results.From the perspective of sampling,this paper designs a sampling method with double-screening,combines it with the Deep Deterministic Policy Gradient(DDPG)algorithm,and proposes the Relevant Experience Learning-DDPG(REL-DDPG)algorithm.The REL-DDPG algorithm uses a Prioritized Experience Replay(PER)mechanism to break the correlation of continuous experiences in the experience pool,finds the experiences most similar to the current state to learn according to the theory in human education,and expands the influence of the learning process on action selection at the current state.All experiments are applied in a complex unknown simulation environment constructed based on the parameters of a real UAV.The training experiments show that REL-DDPG improves the convergence speed and the convergence result compared to the state-of-the-art DDPG algorithm,while the testing experiments show the applicability of the algorithm and investigate the performance under different parameter conditions.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
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
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
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
Target tracking is one of the most important issues in computer vision and has been applied in many fields of science, engineering and industry. Because of the occlusion during tracking, typical approaches with single...Target tracking is one of the most important issues in computer vision and has been applied in many fields of science, engineering and industry. Because of the occlusion during tracking, typical approaches with single classifier learn much of occluding background information which results in the decrease of tracking performance, and eventually lead to the failure of the tracking algorithm. This paper presents a new correlative classifiers approach to address the above problem. Our idea is to derive a group of correlative classifiers based on sample set method. Then we propose strategy to establish the classifiers and to query the suitable classifiers for the next frame tracking. In order to deal with nonlinear problem, particle filter is adopted and integrated with sample set method. For choosing the target from candidate particles, we define a similarity measurement between particles and sample set. The proposed sample set method includes the following steps. First, we cropped positive samples set around the target and negative samples set far away from the target. Second, we extracted average Haar-like feature from these samples and calculate their statistical characteristic which represents the target model. Third, we define the similarity measurement based on the statistical characteristic of these two sets to judge the similarity between candidate particles and target model. Finally, we choose the largest similarity score particle as the target in the new frame. A number of experiments show the robustness and efficiency of the proposed approach when compared with other state-of-the-art trackers.展开更多
The forming limit curve （FLC） can be obtained by means of curve fitting the limit strain points of different strain paths. The theory of percent regression analysis is applied to the curve fitting of forming limit e...The forming limit curve （FLC） can be obtained by means of curve fitting the limit strain points of different strain paths. The theory of percent regression analysis is applied to the curve fitting of forming limit experimental data.Forecast intervals of FLC percentiles can be calculated. Thus reliability and confidence level can be considered. The theoretical method to get the limits of limit strain points distributing region is presented, and the FLC position can be adjusted according to practical requirement. Method for establishing FLC with high reliability using small samples is presented at the same time. This method can make full use of the current experimental data and the previous data.Compared with the traditional method that can only use current experimental data, fewer specimens are required in the present method to obtain the same precision and the result is more accurate with the same number of specimens.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, 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
This paper presents an artificial neural network（ANN）-based response surface method that can be used to predict the failure probability of c-φslopes with spatially variable soil.In this method,the Latin hypercube s...This paper presents an artificial neural network（ANN）-based response surface method that can be used to predict the failure probability of c-φslopes with spatially variable soil.In this method,the Latin hypercube sampling technique is adopted to generate input datasets for establishing an ANN model;the random finite element method is then utilized to calculate the corresponding output datasets considering the spatial variability of soil properties;and finally,an ANN model is trained to construct the response surface of failure probability and obtain an approximate function that incorporates the relevant variables.The results of the illustrated example indicate that the proposed method provides credible and accurate estimations of failure probability.As a result,the obtained approximate function can be used as an alternative to the specific analysis process in c-φslope reliability analyses.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
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
The spacecraequipment layout optimization design(SELOD)problems with complicated performance con-straints and diversity are studied in this paper.The previous literature uses the gradient-based algorithm to obtain op...The spacecraequipment layout optimization design(SELOD)problems with complicated performance con-straints and diversity are studied in this paper.The previous literature uses the gradient-based algorithm to obtain optimized non-overlap layout schemes from randomly initialized cases eectively.However,these local optimal solutions are too dicult to jump out of their current relative geometry relationships,signicantly limiting their further improvement in performance indicators.Therefore,considering the geometric diversity of layout schemes is put forward to alleviate this limitation.First,similarity measures,including modied cosine similarity and gaussian kernel function similarity,are introduced into the layout optimization process.Then the optimization produces a set of feasible layout candidates with the most remarkable dierence in geometric distribution and the most representative schemes are sampled.Finally,these feasible geometric solutions are used as initial solutions to optimize the physical performance indicators of the spacecra,and diversied layout schemes of spacecraequipment are generated for the engineering practice.The validity and eectiveness of the proposed methodology are demonstrated by two SELOD applications.展开更多
基金The Strategic Priority Research Program of the Chinese Academy of Sciences,No.XDB03030500National Key Technology Research and Development Program,No.2013BAC04B02+1 种基金Key Foundation Project of Basic Work of the Ministry of Science and Technology of China,No.2012FY111400National Natural Science Foundation of China,No.41171080,No.41201095
文摘Twenty-one typical coupled large samples were chosen from areas within and surrounding nature reserves on the Tibetan Plateau using the large sample comparison method(LSCM).To evaluate the effectiveness of the nature reserves in protecting the ecological environment,the alpine grassland net primary production(NPP) of these coupled samples were compared and the differences between them before and after their establishment as protected areas were analyzed.The results showed that:(1) With respect to the alpine grassland NPP,the ecological and environmental conditions of most nature reserves were more fragile than those of the surrounding areas and also lower than the average values for the Tibetan Plateau.(2) Of the 11 typical nature reserves selected,the positive trend in the NPP for Manzetang was the most significant,whereas there was no obvious trend in Taxkorgan.With the exception of Selincuo,the annual NPP growth rate in the nature reserves covered by alpine meadow and wetland was higher than that in nature reserves consisting of alpine steppe and alpine desert.(3) There were notable findings in 21 typical coupled samples:(a) After the establishment of the nature reserves,the annual rate of increase in the NPP in 76% of samples inside nature reserves and 82% of samples inside national nature reserves was higher than that of the corresponding samples outside nature reserves.(b) The effectiveness of ecological protection of the Mid-Kunlun,Changshagongma,Zoige and Selincuo(Selin Co) nature reserves was significant; the effectiveness of protection was relatively sig-nificant in most parts of the Sanjiangyuan and Qiangtang nature reserves,whereas in south-east Manzetang and north Taxkorgan the protection effectiveness was not obvious.(c) The ecological protection effectiveness was significant in nature reserves consisting of alpine meadow,but was weak in nature reserves covered by alpine steppe.This study also shows that the advantage of large sample comparison method in evaluating regional ecology change.Careful design of the samples used,to ensure comparability between the samples,is crucial to the success of this LSCM.
基金funded by the Natural Science Foundation of the Inner Mongolia Autonomous Region(Grant No.2020BS04003)the Project of High-Level Talent Research in Inner Mongolia University(Grant No.12000-15031942)the National Natural Science Foundation of China(Grant No.51778590,51879131).
文摘Unsaturated loess in natural sites loses stability as the overburden load continuously increases.Traditional soil modifiers such as cement and fly ash affect the surrounding environment.A new type of material,i.e.,lignin,is environmentally friendly and able to increase the strength of loess.However,the engineering characteristics of the improved loess under unsaturated conditions are not yet clear.In this study,the soil-water characteristic curves(SWCCs)of lignin-improved loess samples were determined from 0 kPa to 700 kPa using a pressure plate instrument,and then,they were fitted using the van Genuchten(VG)model and the Fredlund and Xing(FX)model.In addition,the effects of the lignin content and sample preparation methods on the SWCCs were investigated to determine the optimal lignin content and a suitable sample preparation method for loess foundations.As the lignin content increases,the matric suction and residual water content of the improved loess increase.The suction stress increases with the increasing lignin contents of 1%–2%.At lignin contents of 3%–4%,the suction stress begins to decrease and the samples prepared using the slurry method has a lower suction stress than that prepared using the wet mixing method.The air entry value(AEV)increases with increasing lignin content.In addition,scanning electron microscopy(SEM)was used to investigate the microstructural variations.It was found that after the addition of lignin,the entrapment of the loess particles by the lignin fibers created some larger particles and smaller pore diameters,which in turn led to poor connectivity of the loess pores.These changes cause the matric suction of the modified loess to increase.
基金The China Ocean Mineral Resources Research and Development Association Research Program of the State Oceanic Administration of China under contract No.DY125-13-R-07the National Natural Science Foundation of China under contract Nos 41322036 and 41230960+1 种基金the Shandong Provincial Natural Science Foundation of China under contract No.ZR2014DP009the Special Basic Research Funds for Central Public Research Institutes for The First Institute of Oceanography,State Oceanic Administration of China under contract Nos GY0213G06 and GY02-2012G35
文摘An improved analytical method to determine the content of 52 major, minor and trace elements in marine geological samples, using a HF-HCl-HNO_3 acid system with a high-pressure closed digestion method（HPCD）, is studied by an inductively coupled plasma optical emission spectrometry（ICP-OES） and an inductively coupled plasma mass spectrometry（ICP-MS）. The operating parameters of the instruments are optimized, and the optimal analytical parameters are determined. The influences of optical spectrum and mass spectrum interferences, digestion methods and acid systems on the analytical results are investigated. The optimal spectral lines and isotopes are chosen, and internal standard element of rhodium is selected to compensate for matrix effects and analytical signals drifting. Compared with the methods of an electric heating plate digestion and a microwave digestion, a high-pressure closed digestion method is optimized with less acid, complete digestion,less damage for digestion process. The marine geological samples are dissolved completely by a HF-HCl-HNO_3 system, the relative error（RE） for the analytical results are all less than 6.0%. The method detection limits are 2–40μg/g by the ICP-OES, and 6–80 ng/g by ICP-MS. The methods are used to determine the marine sediment reference materials（GBW07309, GBW07311, GBW07313）, rock reference materials（GBW07103, GBW07104,GBW07105）, and cobalt-rich crust reference materials（GBW07337, GBW07338, GBW07339）, the obtained analytical results are in agreement with the certified values, and both of the relative standard deviation（RSD） and the relative error（RE） are less than 6.0%. The analytical method meets the requirements for determining 52 elements contents of bulk marine geological samples.
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 Technological Innovation Center of Geological Disaster Prevention and ecological Restoration in the western region of the Ministry of Natural Resources opened the fund (Grant No.TICGP2023K003)the Project of Sichuan Disaster Economic Research Center (Grant No.ZHJJ2024YJS004)。
文摘Landslide susceptibility mapping(LSM) is crucial for reducing disaster risk in complex mountainous regions. This study evaluated the impact of various sampling methods on the accuracy of LSM over the next decade in Bijie City, Guizhou Province, China. Datasets were collected from 614 landslides and 500 non-landslides, and four sampling methods were proposed. Recurrent Neural Network(RNN), Gated Recurrent Unit(GRU), K-Nearest Neighbor(KNN), and Extreme Gradient Boosting(XGB) models were assessed utilising 15 metrics(Elevation, Slope, Aspect, Plan curvature, Profile curvature, Stream Power Index, Sediment Transport Index, Vector Ruggedness Measurement, Topographic Roughness Index, Lithology, Land use, Normalized Difference Vegetation Index(NDVI), Rainfall, Distance from Road, Distance from River). The results demonstrated that the GRU model combined with a 5-m sample boundary from the interior of the landslide and non-landslide areas exhibited superior performance with F1, Accuracy, and Area Under Curve(AUC) scores of 0.9700, 0.9450, and 0.8925, respectively. LSM will be projected for the next decade by coupling the Geophysical Fluid Dynamics Laboratory Earth System Model version 4(GFDLESM4) with the Shared Socioeconomic Pathway(SSP119). This study provides valuable insights into landslide risk management in landslide-prone areas.
基金supported by the National Natural Science Foundation of China(Grant No.12272142)Fundamental Research Funds for the Central Universities(Grant No.2172021XXJS048)。
文摘This paper proposes a non-intrusive computational method for mechanical dynamic systems involving a large-scale of interval uncertain parameters,aiming to reduce the computational costs and improve accuracy in determining bounds of system response.The screening method is firstly used to reduce the scale of active uncertain parameters.The sequential high-order polynomials surrogate models are then used to approximate the dynamic system’s response at each time step.To reduce the sampling cost of constructing surrogate model,the interaction effect among uncertain parameters is gradually added to the surrogate model by sequentially incorporating samples from a candidate set,which is composed of vertices and inner grid points.Finally,the points that may produce the bounds of the system response at each time step are searched using the surrogate models.The optimization algorithm is used to locate extreme points,which contribute to determining the inner points producing system response bounds.Additionally,all vertices are also checked using the surrogate models.A vehicle nonlinear dynamic model with 72 uncertain parameters is presented to demonstrate the accuracy and efficiency of the proposed uncertain computational method.
基金co-supported by the National Natural Science Foundation of China(Nos.62003267,61573285)the Aeronautical Science Foundation of China(ASFC)(No.20175553027)Natural Science Basic Research Plan in Shaanxi Province of China(No.2020JQ-220)。
文摘Unmanned Aerial Vehicles(UAVs)play a vital role in military warfare.In a variety of battlefield mission scenarios,UAVs are required to safely fly to designated locations without human intervention.Therefore,finding a suitable method to solve the UAV Autonomous Motion Planning(AMP)problem can improve the success rate of UAV missions to a certain extent.In recent years,many studies have used Deep Reinforcement Learning(DRL)methods to address the AMP problem and have achieved good results.From the perspective of sampling,this paper designs a sampling method with double-screening,combines it with the Deep Deterministic Policy Gradient(DDPG)algorithm,and proposes the Relevant Experience Learning-DDPG(REL-DDPG)algorithm.The REL-DDPG algorithm uses a Prioritized Experience Replay(PER)mechanism to break the correlation of continuous experiences in the experience pool,finds the experiences most similar to the current state to learn according to the theory in human education,and expands the influence of the learning process on action selection at the current state.All experiments are applied in a complex unknown simulation environment constructed based on the parameters of a real UAV.The training experiments show that REL-DDPG improves the convergence speed and the convergence result compared to the state-of-the-art DDPG algorithm,while the testing experiments show the applicability of the algorithm and investigate the performance under different parameter conditions.
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.
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.
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.
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.
基金supported by the National Science Foundation of China(61472289)National Key Research and Development Project(2016YFC0106305)The Key Technology R&D Program of Hubei Provence(2014BAA153)
文摘Target tracking is one of the most important issues in computer vision and has been applied in many fields of science, engineering and industry. Because of the occlusion during tracking, typical approaches with single classifier learn much of occluding background information which results in the decrease of tracking performance, and eventually lead to the failure of the tracking algorithm. This paper presents a new correlative classifiers approach to address the above problem. Our idea is to derive a group of correlative classifiers based on sample set method. Then we propose strategy to establish the classifiers and to query the suitable classifiers for the next frame tracking. In order to deal with nonlinear problem, particle filter is adopted and integrated with sample set method. For choosing the target from candidate particles, we define a similarity measurement between particles and sample set. The proposed sample set method includes the following steps. First, we cropped positive samples set around the target and negative samples set far away from the target. Second, we extracted average Haar-like feature from these samples and calculate their statistical characteristic which represents the target model. Third, we define the similarity measurement based on the statistical characteristic of these two sets to judge the similarity between candidate particles and target model. Finally, we choose the largest similarity score particle as the target in the new frame. A number of experiments show the robustness and efficiency of the proposed approach when compared with other state-of-the-art trackers.
文摘The forming limit curve （FLC） can be obtained by means of curve fitting the limit strain points of different strain paths. The theory of percent regression analysis is applied to the curve fitting of forming limit experimental data.Forecast intervals of FLC percentiles can be calculated. Thus reliability and confidence level can be considered. The theoretical method to get the limits of limit strain points distributing region is presented, and the FLC position can be adjusted according to practical requirement. Method for establishing FLC with high reliability using small samples is presented at the same time. This method can make full use of the current experimental data and the previous data.Compared with the traditional method that can only use current experimental data, fewer specimens are required in the present method to obtain the same precision and the result is more accurate with the same number of specimens.
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, 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financially supported by the National Natural Science Foundation of China(Grant No.51278217)
文摘This paper presents an artificial neural network（ANN）-based response surface method that can be used to predict the failure probability of c-φslopes with spatially variable soil.In this method,the Latin hypercube sampling technique is adopted to generate input datasets for establishing an ANN model;the random finite element method is then utilized to calculate the corresponding output datasets considering the spatial variability of soil properties;and finally,an ANN model is trained to construct the response surface of failure probability and obtain an approximate function that incorporates the relevant variables.The results of the illustrated example indicate that the proposed method provides credible and accurate estimations of failure probability.As a result,the obtained approximate function can be used as an alternative to the specific analysis process in c-φslope reliability analyses.
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.
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 Aerospace Frontier Inspiration Project (Grant No.KY0505072113) from College of Aerospace Science and Engineering,NUDT,which are gratefully acknowledged by the authors.
文摘The spacecraequipment layout optimization design(SELOD)problems with complicated performance con-straints and diversity are studied in this paper.The previous literature uses the gradient-based algorithm to obtain optimized non-overlap layout schemes from randomly initialized cases eectively.However,these local optimal solutions are too dicult to jump out of their current relative geometry relationships,signicantly limiting their further improvement in performance indicators.Therefore,considering the geometric diversity of layout schemes is put forward to alleviate this limitation.First,similarity measures,including modied cosine similarity and gaussian kernel function similarity,are introduced into the layout optimization process.Then the optimization produces a set of feasible layout candidates with the most remarkable dierence in geometric distribution and the most representative schemes are sampled.Finally,these feasible geometric solutions are used as initial solutions to optimize the physical performance indicators of the spacecra,and diversied layout schemes of spacecraequipment are generated for the engineering practice.The validity and eectiveness of the proposed methodology are demonstrated by two SELOD applications.
