Incremental data mining is an attractive goal for many kinds of mining in large databases or data warehouses. A new incremental updating algorithm rule growing algorithm (RGA) is presented for efficient maintenance di...Incremental data mining is an attractive goal for many kinds of mining in large databases or data warehouses. A new incremental updating algorithm rule growing algorithm (RGA) is presented for efficient maintenance discovered association rules when new transaction data is added to a transaction database. The algorithm RGA makes use of previous association rules as seed rules. By RGA, the seed rules whether are strong or not can be confirmed without scanning all the transaction DB in most cases. If the distributing of item of transaction DB is not uniform, the inflexion of robustness curve comes very quickly, and RGA gets great efficiency, saving lots of time for I/O. Experiments validate the algorithm and the test results showed that this algorithm is efficient.展开更多
In data mining from transaction DB, the relationships between the attributes have been focused, but the relationships between the tuples have not been taken into account. In spatial database, there are relationships b...In data mining from transaction DB, the relationships between the attributes have been focused, but the relationships between the tuples have not been taken into account. In spatial database, there are relationships between the attributes and the tuples, and most of the associations occur between the tuples, such as adjacent, intersection, overlap and other topological relationships. So the tasks of spatial data association rules mining include mining the relationships between attributes of spatial objects, which are called as vertical direction DM, and the relationships between the tuples, which are called as horizontal direction DM. This paper analyzes the storage models of spatial data, uses for reference the technologies of data mining in transaction DB, defines the spatial data association rule, including vertical direction association rule, horizontal direction association rule and two-direction association rule, discusses the measurement of spatial association rule interestingness, and puts forward the work flows of spatial association rule data mining. During two-direction spatial association rules mining, an algorithm is proposed to get non-spatial itemsets. By virtue of spatial analysis, the spatial relations were transferred into non-spatial associations and the non-spatial itemsets were gotten. Based on the non-spatial itemsets, the Apriori algorithm or other algorithms could be used to get the frequent itemsets and then the spatial association rules come into being. Using spatial DB, the spatial association rules were gotten to validate the algorithm, and the test results show that this algorithm is efficient and can mine the interesting spatial rules.展开更多
Microstructures and critical phase-transformation temperature of boron-nickel added Nb-treated high strength low alloy （HSLA） H-beams cooled at different cooling rate, with different deformation were investigated. C...Microstructures and critical phase-transformation temperature of boron-nickel added Nb-treated high strength low alloy （HSLA） H-beams cooled at different cooling rate, with different deformation were investigated. Continuous cooling transformation （CCT） diagram of this new type of steel was obtained by using Gleeble 1500 ther- momechanical simulator. Microstructures and hardness, especially micro-hardness of the experimental steel were in- vestigated by optical microscopy （OM）, scanning electron microscope （SEM）, Rockwell and Vickers hardness tests. Phase analysis was also studied by X^ray diffraction （XRD）. The results indicated that with increase of cooling rate, microstructures of continuous cooled specimens gradually transformed from polygonal ferrite and pearlite, grain boundary ferrite and bainite, bainite and martensite to single martensite. The CCT diagram revealed that slow cool- ing was needed to avoid austenite-bainite transformation to ensure toughness of this steel. By plastic deformation of 40%, austenite-ferrite transformation temperature increased by 46℃, due to deformation induced ferrite transfor- mation during continuous cooling, but Rockwell hardness has little change.展开更多
基金The work is supported by Chongqing Municipal Education Commission Science Research Program( No.KJ060511)
文摘Incremental data mining is an attractive goal for many kinds of mining in large databases or data warehouses. A new incremental updating algorithm rule growing algorithm (RGA) is presented for efficient maintenance discovered association rules when new transaction data is added to a transaction database. The algorithm RGA makes use of previous association rules as seed rules. By RGA, the seed rules whether are strong or not can be confirmed without scanning all the transaction DB in most cases. If the distributing of item of transaction DB is not uniform, the inflexion of robustness curve comes very quickly, and RGA gets great efficiency, saving lots of time for I/O. Experiments validate the algorithm and the test results showed that this algorithm is efficient.
基金The work is supported by Natural Science Foundatiion of Chongqing (No .CSTC 2005BB2065)
文摘In data mining from transaction DB, the relationships between the attributes have been focused, but the relationships between the tuples have not been taken into account. In spatial database, there are relationships between the attributes and the tuples, and most of the associations occur between the tuples, such as adjacent, intersection, overlap and other topological relationships. So the tasks of spatial data association rules mining include mining the relationships between attributes of spatial objects, which are called as vertical direction DM, and the relationships between the tuples, which are called as horizontal direction DM. This paper analyzes the storage models of spatial data, uses for reference the technologies of data mining in transaction DB, defines the spatial data association rule, including vertical direction association rule, horizontal direction association rule and two-direction association rule, discusses the measurement of spatial association rule interestingness, and puts forward the work flows of spatial association rule data mining. During two-direction spatial association rules mining, an algorithm is proposed to get non-spatial itemsets. By virtue of spatial analysis, the spatial relations were transferred into non-spatial associations and the non-spatial itemsets were gotten. Based on the non-spatial itemsets, the Apriori algorithm or other algorithms could be used to get the frequent itemsets and then the spatial association rules come into being. Using spatial DB, the spatial association rules were gotten to validate the algorithm, and the test results show that this algorithm is efficient and can mine the interesting spatial rules.
文摘Microstructures and critical phase-transformation temperature of boron-nickel added Nb-treated high strength low alloy （HSLA） H-beams cooled at different cooling rate, with different deformation were investigated. Continuous cooling transformation （CCT） diagram of this new type of steel was obtained by using Gleeble 1500 ther- momechanical simulator. Microstructures and hardness, especially micro-hardness of the experimental steel were in- vestigated by optical microscopy （OM）, scanning electron microscope （SEM）, Rockwell and Vickers hardness tests. Phase analysis was also studied by X^ray diffraction （XRD）. The results indicated that with increase of cooling rate, microstructures of continuous cooled specimens gradually transformed from polygonal ferrite and pearlite, grain boundary ferrite and bainite, bainite and martensite to single martensite. The CCT diagram revealed that slow cool- ing was needed to avoid austenite-bainite transformation to ensure toughness of this steel. By plastic deformation of 40%, austenite-ferrite transformation temperature increased by 46℃, due to deformation induced ferrite transfor- mation during continuous cooling, but Rockwell hardness has little change.
