Title :
The establishment and data mining of meteorological data warehouse
Author :
Lei Shao ; Jun Liu ; Guoling Dong ; Yi Mu ; Peng Guo
Author_Institution :
Tianjin Key Lab. for Control Theor. & Applic. in Complicated Syst., Tianjin Univ. of Technol., Tianjin, China
Abstract :
Along with the continuous development of the modernization level of meteorological service, meteorological data has been steadily on the increase, which results in a higher and higher demand of meteorological department for meteorological data storage, management, and read. Through analyzing the framework of Distributed File System, Data Warehouse Tool Hive of the open source cloud platform - Hadoop, the Build Process of the Hadoop meteorological cloud platform is studied. Based on Naïve Bayes algorithm research, a kind of method which can transplant it to the Hadoop platform is found.
Keywords :
Bayes methods; cloud computing; data mining; data warehouses; file organisation; Hadoop meteorological cloud platform; data mining; data warehouse tool Hive; distributed file system; meteorological data storage; meteorological data warehouse; meteorological service; naïve Bayes algorithm; open source cloud platform; Automation; Conferences; Mechatronics; HDFS; Hadoop; Hive; Meteorological data warehouse; Naïve Bayes;
Conference_Titel :
Mechatronics and Automation (ICMA), 2014 IEEE International Conference on
Conference_Location :
Tianjin
Print_ISBN :
978-1-4799-3978-7
DOI :
10.1109/ICMA.2014.6886019