Optimal Sensor Placement Using Learning Models—A Mediterranean Case Study
In this paper, we discuss different approaches to optimal sensor placement and propose that an optimal sensor location can be selected using unsupervised learning methods such as self-organising maps, neural gas or the K-means algorithm. We show how each of the algorithms can be used for this purpos...
| Autori principali: | , , |
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| Natura: | Articolo |
| Lingua: | English |
| Pubblicazione: |
MDPI AG
2022-06-01
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| Serie: | Remote Sensing |
| Soggetti: | |
| Accesso online: | https://www.mdpi.com/2072-4292/14/13/2989 |