A density-based clustering algorithm for earthquake zoning
| Autor: | Sanja Scitovski |
|---|---|
| Rok vydání: | 2018 |
| Předmět: |
business.industry
Computer science Big data 02 engineering and technology 010502 geochemistry & geophysics 01 natural sciences Physics::Geophysics 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing Computers in Earth Sciences business Zoning Cluster analysis Density based clustering Value (mathematics) Algorithm 0105 earth and related environmental sciences Information Systems |
| Zdroj: | Computers & Geosciences. 110:90-95 |
| ISSN: | 0098-3004 |
| DOI: | 10.1016/j.cageo.2017.08.014 |
| Popis: | A possibility of applying the density-based clustering algorithm Rough-DBSCAN for earthquake zoning is considered in the paper. By using density-based clustering for earthquake zoning it is possible to recognize nonconvex shapes, what gives much more realistic results. Special attention is thereby paid to the problem of determining the corresponding value of the parameter ɛ in the algorithm. The size of the parameter ɛ significantly influences the recognizing number and configuration of earthquake zones. A method for selecting the parameter ɛ in the case of big data is also proposed. The method is applied to the problem of earthquake data zoning in a wider area of the Republic of Croatia. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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