This paper focuses on the methods and process of spatial aggregation based on semantic and geometric characteristics of spatial objects and relations among the objects with the help of spatial data structure (Formal D...This paper focuses on the methods and process of spatial aggregation based on semantic and geometric characteristics of spatial objects and relations among the objects with the help of spatial data structure (Formal Data Structure),the Local Constrained Delaunay Triangulations and semantic hierarchy.The adjacent relation among connected objects and unconnected objects has been studied through constrained triangle as elementary processing unit in aggregation operation.The hierarchical semantic analytical matrix is given for analyzing the similarity between objects types and between objects.Several different cases of aggregation have been presented in this paper.展开更多
Many monitoring measures were used in the production field for predicting rockburst.However, predicting rock burst according to complicated observation data is alwaysa pressing problem in this research field.Though th...Many monitoring measures were used in the production field for predicting rockburst.However, predicting rock burst according to complicated observation data is alwaysa pressing problem in this research field.Though the critical value method gets extensiveapplication in practice, it stresses only on the superficial change of data and overlooks alot of features of rock burst and useful information that is concealed and hidden in the observationtime series.Pattern recognition extracts the feature value of time domain, frequencydomain and wavelet domain in observation time series to form Multi-Feature vectors,using Euclidean distance measure as the separable criterion between the same typeand different type to compress and transform feature vectors.It applies neural network asa tool to recognize the danger of rock burst, and uses feature vectors being compressedto carry out training and studying.It is proved by test samples that predicting precisionshould be prior to such traditional predicting methods as pattern recognition and critical indicatormethod.展开更多
Interpolation methods in ArcGIS_ESRI Geostatistical Analyst tool allow obtaining unknown values at unsampled points from observed data and generating continuous surfaces. In this paper, forest data variables as tree h...Interpolation methods in ArcGIS_ESRI Geostatistical Analyst tool allow obtaining unknown values at unsampled points from observed data and generating continuous surfaces. In this paper, forest data variables as tree height and diameter measured in two plots in Central Mountains in Spain. These data were georeferenced to obtain maps that can visualize the spatial variability of these forest variables. In order to evaluate the best interpolation method that could adequately explain the spatial variability of those variables, two interpolation methods were studied： inverse results was made by means of statistical methods to analyze distance weighted （IDW） and Ordinary Kriging （OK）. A comparison of residuals. Results with the kriging method were slightly better.展开更多
The aspect sensitivity is the main problem in radar automatic target recognition using high resolution range profile (HRRP). In the traditional viewpoint,HRRPs are assumed to be highly similar if the aspect variation ...The aspect sensitivity is the main problem in radar automatic target recognition using high resolution range profile (HRRP). In the traditional viewpoint,HRRPs are assumed to be highly similar if the aspect variation is not enough to cause range migration. However,some experiments in anechoic chambers don’t agree with the assumption. Particularly,some abnormal HRRPs often occur in the measured data. Based on the scattering center model,this paper focuses on the reason of abnormal HRRP,which is named as the speckle. The theoretical model of speckle is established and the "spurious dual peaks" feature of the speckled HRRP is analyzed. Then the occurrence condition of speckle is concluded,and so is the relationship between the speckle probability in HRRP and radar carrier frequency. At last,the experiment in an anechoic chamber is used to verify all the analyses about the speckle.展开更多
文摘This paper focuses on the methods and process of spatial aggregation based on semantic and geometric characteristics of spatial objects and relations among the objects with the help of spatial data structure (Formal Data Structure),the Local Constrained Delaunay Triangulations and semantic hierarchy.The adjacent relation among connected objects and unconnected objects has been studied through constrained triangle as elementary processing unit in aggregation operation.The hierarchical semantic analytical matrix is given for analyzing the similarity between objects types and between objects.Several different cases of aggregation have been presented in this paper.
文摘Many monitoring measures were used in the production field for predicting rockburst.However, predicting rock burst according to complicated observation data is alwaysa pressing problem in this research field.Though the critical value method gets extensiveapplication in practice, it stresses only on the superficial change of data and overlooks alot of features of rock burst and useful information that is concealed and hidden in the observationtime series.Pattern recognition extracts the feature value of time domain, frequencydomain and wavelet domain in observation time series to form Multi-Feature vectors,using Euclidean distance measure as the separable criterion between the same typeand different type to compress and transform feature vectors.It applies neural network asa tool to recognize the danger of rock burst, and uses feature vectors being compressedto carry out training and studying.It is proved by test samples that predicting precisionshould be prior to such traditional predicting methods as pattern recognition and critical indicatormethod.
文摘Interpolation methods in ArcGIS_ESRI Geostatistical Analyst tool allow obtaining unknown values at unsampled points from observed data and generating continuous surfaces. In this paper, forest data variables as tree height and diameter measured in two plots in Central Mountains in Spain. These data were georeferenced to obtain maps that can visualize the spatial variability of these forest variables. In order to evaluate the best interpolation method that could adequately explain the spatial variability of those variables, two interpolation methods were studied： inverse results was made by means of statistical methods to analyze distance weighted （IDW） and Ordinary Kriging （OK）. A comparison of residuals. Results with the kriging method were slightly better.
文摘The aspect sensitivity is the main problem in radar automatic target recognition using high resolution range profile (HRRP). In the traditional viewpoint,HRRPs are assumed to be highly similar if the aspect variation is not enough to cause range migration. However,some experiments in anechoic chambers don’t agree with the assumption. Particularly,some abnormal HRRPs often occur in the measured data. Based on the scattering center model,this paper focuses on the reason of abnormal HRRP,which is named as the speckle. The theoretical model of speckle is established and the "spurious dual peaks" feature of the speckled HRRP is analyzed. Then the occurrence condition of speckle is concluded,and so is the relationship between the speckle probability in HRRP and radar carrier frequency. At last,the experiment in an anechoic chamber is used to verify all the analyses about the speckle.
