At the Ocean Science Meeting 2020 held in San Diego, U.S.A. on February 16, Kalpesh Patil, a post doctoral researcher at Iiyama Laboratory Kyoto University, presented a poster entitled “Residual prediction to improve the methodological based sea surface temperature forecasts using ANN”.
Potential fishing regions (PFR) are largely dependent on local sea surface temperature (SST) pattern, to plan an optimal trip to PFR accurate SST predictions are inevitable. This study features SST prediction near Tohoku region in Japan at short (1Hr), mid-short (8Hr) and long-term (24Hr) horizons using artificial neural network (ANN) with meteorological parameters as input and observed SST as targets.
The poster is available at the following link:
Residual prediction to improve the meteorological based sea surface temperature forecasts using ANNA
Dr. Kalpesh Patil