Machine learning approach to restoration, prediction and quality control of oceanographic data from IMOS Moorings (Old ID 24926)
AIMS@JCU
Role
Supervisor
Description
This project investigates a machine learning approach to increasing the value of oceanographic data. The full collection of IMOS Moorings data will be available for use in developing and training algorithms. Much of this data has already been flagged by heuristic quality control routines, and manually annotated by domain experts.
Date
12 Mar 2018 - 22 Mar 2022
Project Type
GRANT
Keywords
Machine Learning;missing data imputation;oceanographic data;time-series forecasting
Funding Body
AIMS@JCU
Amount
20204
Project Team
Ricardo Gabrielli Barreto Campello;Ickjai Lee