3 papers
cs.SI2020
Client Network: An Interactive Model for Predicting New Clients
Massimiliano Mattetti, Akihiro Kishimoto, Adi Botea +4
Understanding prospective clients becomes increasingly important as companies aim to enlarge their market bases. Traditional approaches typically treat each client in isolation, ei…
physics.ao-ph2019
Statistical and machine learning ensemble modelling to forecast sea surface temperature
Stefan Wolff, Fearghal O'Donncha, Bei Chen
In situ and remotely sensed observations have potential to facilitate data-driven predictive models for oceanography. A suite of machine learning models, including regression, deci…
physics.ao-ph2018
Ensemble model aggregation using a computationally lightweight machine-learning model to forecast ocean waves
Fearghal O'Donncha, Yushan Zhang, Bei Chen +1
This study investigated an approach to improve the accuracy of computationally lightweight surrogate models by updating forecasts based on historical accuracy relative to sparse ob…