Optimization of Deep Learning Precipitation Models Using Categorical Binary Metrics

Optimization of Deep Learning Precipitation Models Using Categorical Binary Metrics

Abstract This work introduces a methodology for optimizing neural network models using a combination of continuous and categorical binary indices in the context of precipitation forecasting. Probability of detection and false alarm rate are popular metrics used in the verification of precipitation m...

Full description

Bibliographic Details
Main Authors: Pablo R. Larraondo, Luigi J. Renzullo, Albert I. J. M. Van Dijk, Inaki Inza, Jose A. Lozano
Format: Article
Language:English
Published: American Geophysical Union (AGU) 2020-05-01
Series:Journal of Advances in Modeling Earth Systems
Subjects:
precipitation verification
machine learning
categorical indexes
neural networks
modeling
Online Access:https://doi.org/10.1029/2019MS001909

Internet

https://doi.org/10.1029/2019MS001909

Similar Items