The Experts below are selected from a list of 312 Experts worldwide ranked by ideXlab platform
Mei Yuan - One of the best experts on this subject based on the ideXlab platform.
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The Design of Meteorological Data Warehouse and Multidimensional Data Report
2010 Second International Conference on Information Technology and Computer Science, 2010Co-Authors: Mei Yuan, He ZhouAbstract:The paper designs and implements the Meteorological Data warehouse as well as the Meteorological Data report based on the Microsoft SQL Server. The purpose is to apply Data warehouse technology in the Meteorological research area. Using On-Line Analysis Processing(OLAP) and the multidimensional report, we get the beneficial Data. The system generates Meteorological Data report, which can publish the report to the browser. The research is beneficial for Meteorological phenomena studies.
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OWB-based construction of Meteorological Data warehouse
2010 International Conference on Computer Application and System Modeling (ICCASM 2010), 2010Co-Authors: Xinna Shang, Mei YuanAbstract:Based on Meteorological information background and ideology of Data warehouse construction, this article analyzes multiple Meteorological Data sources, designs the Meteorological Data warehouse architecture, target Data model and ETL process. The system have been deployed on ORACLE-OWB platform, a better result has been achieved.
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Iceberg model based on Meteorological Data mining
2010 International Conference on Computer Application and System Modeling (ICCASM 2010), 2010Co-Authors: Mei YuanAbstract:The mining efficient is not only about the designation of the mining algorithm, but also relating to the character of the Data we want to explore. Different Data, different focus. This paper is talking about a mining method on the Meteorological Data. Through building a iceberg model, and then dig the model, getting the frequent itemset out further, it is important to get clear about the association rules of the weather's Data.
Xie Jian - One of the best experts on this subject based on the ideXlab platform.
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Multi-format real-time Meteorological Data analysis and application
Journal of Computer Applications, 2020Co-Authors: Xie JianAbstract:Real-time Meteorological Data is not only the basis of short-term Meteorological forecasts,but also the key Data to effectively monitor,forecast,early warn,and assess Meteorological disasters.There are many kinds of Meteorological messages and their formats vary.As the analysis,cleaning and screening of Meteorological Data is very complex and inflexible,real-time query is very slow.This paper mainly studied unified message analytical technology and Data stream processing technology to design and implement a real safe,feasible,fast,flexible,real-time Meteorological Data acquisition system.
Jürgen Seib - One of the best experts on this subject based on the ideXlab platform.
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Towards Large-Scale Meteorological Data Services: A Case Study
Datenbank-Spektrum, 2012Co-Authors: Dimitar Misev, Peter Baumann, Jürgen SeibAbstract:Meteorological Data contribute significantly to “Big Data”, handling multi-dimensional raster Data cubes up to 5-D and with single cubes up to multi-Petabyte sizes. Due to the lack of support for raster Data, traditionally file-based implementations have been used for serving such Data to the community, rather than Databases. Array Databases overcome this by providing storage and query support. In this paper, we present a case study conducted by Deutscher Wetterdienst (DWD) where extraction and processing of gridded Meteorological Data sets has been investigated hands-on. Following a brief introduction of the rasdaman DBMS used, we present the Database schema used and a series of array queries, selected according to their practical importance in weather forecast services. We discuss several issues that have come up, such as null values and time modeling, and how they have been addressed. To the best of our knowledge, this is the first non-academic deployment of an array Database for up to 5-D Data sets.
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Towards Large-Scale Meteorological Data Services: A Case Study
Datenbank-Spektrum, 2012Co-Authors: Dimitar Misev, Peter Baumann, Jürgen SeibAbstract:Abstract. Meteorological Data contribute significantly to “Big Data”, handling multi-dimensional raster Data cubes up to 5-D and with single cubes up to multi-Petabyte sizes. Due to the lack of support for raster Data, traditionally file-based implementations have been used for serving such Data to the community, rather than Databases. Array Databases overcome this by providing storage and query support. In this contribution, we present a case study conducted by Deutscher Wetterdienst (DWD) where extraction and processing of gridded Meteorological Data sets has been investigated hands-on. Following a brief introduction of the rasdaman DBMS used, we present the Database schema used and a series of array queries, selected according to their practical importance in weather forecast services. We discuss several issues that have come up, such as null values and time modeling, and how they have been addressed. To the best of our knowledge, this is the first non-academic deployment of an array Database for up to 5-D Data sets.
Yi Mu - One of the best experts on this subject based on the ideXlab platform.
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The establishment and Data mining of Meteorological Data warehouse
2014 IEEE International Conference on Mechatronics and Automation, 2014Co-Authors: Lei Shao, Guoling Dong, Yi MuAbstract: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.
Li Zhonglong - One of the best experts on this subject based on the ideXlab platform.
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Review of Quality Control Methods of Surface Real Time Meteorological Data
Journal of Arid Meteorology, 2020Co-Authors: Li ZhonglongAbstract:Quality control of real time Meteorological Data is an indispensable link to ensure high quality of weather forecast and climate prediction.This paper introduced the domestic and foreign Meteorological Data quality control methods,and found that the traditional method is still main important tool of real time Meteorological Data quality control.Real time quality control system can be more effective to combine automatic control with experience judgment.In the future,it still need to strengthen research of station-level quality control,statistical test methods and space quality control methods,as well as comprehensive criterion and information identification of quality control.
