Disaster forecasting using convex hull & K-median approach
| Autor: | Monpreet Roy, Ritika Nath, Anurag Ghosh, Debjit Mukherjee, Shankhadip Mallick, Ratul Dey |
|---|---|
| Rok vydání: | 2016 |
| Předmět: |
Median approach
Convex hull Computer science 0208 environmental biotechnology Unstructured data 02 engineering and technology computer.software_genre 020801 environmental engineering Large set (Ramsey theory) 0202 electrical engineering electronic engineering information engineering Clustered data 020201 artificial intelligence & image processing Data mining Natural disaster computer Protocol (object-oriented programming) |
| Zdroj: | 2016 IEEE 7th Annual Information Technology, Electronics and Mobile Communication Conference (IEMCON). |
| DOI: | 10.1109/iemcon.2016.7746254 |
| Popis: | Data mining is a concept to find knowledge from a large set of data. In this proposed model initially disaster, time, place from all over the world have been collected. Then the database has been divided into two parts - natural disaster and man-made disaster, then the outer region of the unstructured data using convex hull has been identified. According to month of occurrence, previous structural data are passed through K-median and the clustered data is passed through priority based protocol and then the resultant data can be used to predict natural disaster or man-made disaster by the analysis of the previous data. |
| Databáze: | OpenAIRE |
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