To improve the performance of the traditional map matching algorithms in freeway traffic state monitoring systems using the low logging frequency GPS （global positioning system） probe data, a map matching algorithm ...To improve the performance of the traditional map matching algorithms in freeway traffic state monitoring systems using the low logging frequency GPS （global positioning system） probe data, a map matching algorithm based on the Oracle spatial data model is proposed. The algorithm uses the Oracle road network data model to analyze the spatial relationships between massive GPS positioning points and freeway networks, builds an N-shortest path algorithm to find reasonable candidate routes between GPS positioning points efficiently, and uses the fuzzy logic inference system to determine the final matched traveling route. According to the implementation with field data from Los Angeles, the computation speed of the algorithm is about 135 GPS positioning points per second and the accuracy is 98.9%. The results demonstrate the effectiveness and accuracy of the proposed algorithm for mapping massive GPS positioning data onto freeway networks with complex geometric characteristics.展开更多
Clustering, in data mining, is a useful technique for discovering interesting data distributions and patterns in the underlying data, and has many application fields, such as statistical data analysis, pattern recogni...Clustering, in data mining, is a useful technique for discovering interesting data distributions and patterns in the underlying data, and has many application fields, such as statistical data analysis, pattern recognition, image processing, and etc. We combine sampling technique with DBSCAN algorithm to cluster large spatial databases, and two sampling based DBSCAN (SDBSCAN) algorithms are developed. One algorithm introduces sampling technique inside DBSCAN, and the other uses sampling procedure outside DBSCAN. Experimental results demonstrate that our algorithms are effective and efficient in clustering large scale spatial databases.展开更多
Presented a study on the design and implementation of spatial data modelingand application in the spatial data organization and management of a coalfield geologicalenvironment database.Based on analysis of a number of...Presented a study on the design and implementation of spatial data modelingand application in the spatial data organization and management of a coalfield geologicalenvironment database.Based on analysis of a number of existing data models and takinginto account the unique data structure and characteristic, methodology and key techniquesin the object-oriented spatial data modeling were proposed for the coalfield geological environment.The model building process was developed using object-oriented technologyand the Unified Modeling Language (UML) on the platform of ESRI geodatabase datamodels.A case study of spatial data modeling in UML was presented with successful implementationin the spatial database of the coalfield geological environment.The modelbuilding and implementation provided an effective way of representing the complexity andspecificity of coalfield geological environment spatial data and an integrated managementof spatial and property data.展开更多
文摘To improve the performance of the traditional map matching algorithms in freeway traffic state monitoring systems using the low logging frequency GPS （global positioning system） probe data, a map matching algorithm based on the Oracle spatial data model is proposed. The algorithm uses the Oracle road network data model to analyze the spatial relationships between massive GPS positioning points and freeway networks, builds an N-shortest path algorithm to find reasonable candidate routes between GPS positioning points efficiently, and uses the fuzzy logic inference system to determine the final matched traveling route. According to the implementation with field data from Los Angeles, the computation speed of the algorithm is about 135 GPS positioning points per second and the accuracy is 98.9%. The results demonstrate the effectiveness and accuracy of the proposed algorithm for mapping massive GPS positioning data onto freeway networks with complex geometric characteristics.
基金Supported by the Open Researches Fund Program of L IESMARS(WKL(0 0 ) 0 30 2 )
文摘Clustering, in data mining, is a useful technique for discovering interesting data distributions and patterns in the underlying data, and has many application fields, such as statistical data analysis, pattern recognition, image processing, and etc. We combine sampling technique with DBSCAN algorithm to cluster large spatial databases, and two sampling based DBSCAN (SDBSCAN) algorithms are developed. One algorithm introduces sampling technique inside DBSCAN, and the other uses sampling procedure outside DBSCAN. Experimental results demonstrate that our algorithms are effective and efficient in clustering large scale spatial databases.
基金Supported by the Natural Science Foundation of Shanxi Province(2008011028-2)
文摘Presented a study on the design and implementation of spatial data modelingand application in the spatial data organization and management of a coalfield geologicalenvironment database.Based on analysis of a number of existing data models and takinginto account the unique data structure and characteristic, methodology and key techniquesin the object-oriented spatial data modeling were proposed for the coalfield geological environment.The model building process was developed using object-oriented technologyand the Unified Modeling Language (UML) on the platform of ESRI geodatabase datamodels.A case study of spatial data modeling in UML was presented with successful implementationin the spatial database of the coalfield geological environment.The modelbuilding and implementation provided an effective way of representing the complexity andspecificity of coalfield geological environment spatial data and an integrated managementof spatial and property data.
