Artikel,

Virtual Calibration of Cosmic Ray Sensor: Using Supervised Ensemble Machine Learning

.
International Journal of Advanced Computer Science and Applications(IJACSA), (2013)

Zusammenfassung

In this paper an ensemble of supervised machine learning methods has been investigated to virtually and dynamically calibrate the cosmic ray sensors measuring area wise bulk soil moisture. Main focus of this study was to find an alternative to the currently available field calibration method; based on expensive and time consuming soil sample collection methodology. Data from the Australian Water Availability Project (AWAP) database was used as independent soil moisture ground truth and results were compared against the conventionally estimated soil moisture using a Hydroinnova CRS-1000 cosmic ray probe deployed in Tullochgorum, Australia. Pre…(mehr)

Tags

Nutzer

  • @thesaiorg

Kommentare und Rezensionen