Global wind data are increasingly used in many applications and research fields because it provides global coverage of ocean surface winds with an unprecedented view, and data are available at a sufficiently large spatial scale and high temporal resolution. NoSQL databases are increasingly used in Big Data applications due to its simplicity and flexibility of the data models design, the effectiveness of recoveries, the control over the system availability, and their horizontal scaling. Thus, the integration of heterogeneous data sources in only one NoSQL database repository, to select and recover diverse regions of interest of geospatial wind data, to analyze them via Data Mining applications, and to visualized their results, are the main objectives of this work.
Data Mining algorithms
• Hardware: Processor: i3 ,i5 RAM: 4GB Hard disk: 16 GB • Software: operating System : Windws2000/XP/7/8/10 Anaconda,jupyter,spyder,flask Frontend :-python Backend:- MYSQL
₹10000 (INR)
2018