Abstract
In this paper, we present a knowledge discovery process applied to hydrological data. To achieve this objective, we combine successive methods to extract knowledge on data collected at stations located along several rivers. Firstly, data is pre processed in order to obtain diffierent spatial proximities. Later, we apply two algorithms to extract spatiotemporal patterns and compare them. Such elements can be used to assess spatialized indicators to assist the interpretation of ecological and rivers monitoring pressure data.
Original language | English |
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State | Published - 1 Jan 2013 |
Externally published | Yes |
Event | CEUR Workshop Proceedings - Duration: 1 Jan 2017 → … |
Conference
Conference | CEUR Workshop Proceedings |
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Period | 1/01/17 → … |
Keywords
- Data mining
- Sequential patterns
- Spatiotemporal data