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Fearghal O'Donncha
Fearghal O'Donncha
IBM Research
Verified email at ie.ibm.com - Homepage
Title
Cited by
Cited by
Year
A machine learning framework to forecast wave conditions
SC James, Y Zhang, F O'Donncha
Coastal Engineering 137, 1-10, 2018
3302018
Characterizing observed circulation patterns within a bay using HF radar and numerical model simulations
F O’Donncha, M Hartnett, S Nash, L Ren, E Ragnoli
Journal of Marine Systems 142, 96-110, 2015
722015
Physical and numerical investigation of the hydrodynamic implications of aquaculture farms
F O’Donncha, M Hartnett, S Nash
Aquacultural engineering 52, 14-26, 2013
672013
Statistical and machine learning ensemble modelling to forecast sea surface temperature
S Wolff, F O'Donncha, B Chen
Journal of Marine Systems 208 (103347), 2020
652020
Precision aquaculture
F O'donncha, J Grant
IEEE Internet of Things Magazine 2 (4), 26-30, 2019
632019
Using Deep Learning to Extend the Range of Air-Pollution Monitoring and Forecasting
P Haehnel, J Marecek, J Monteil, F O'Donncha
Journal of Computational Physics 408 (1), 109278, 2020
572020
An integrated framework that combines machine learning and numerical models to improve wave-condition forecasts
F O’Donncha, Y Zhang, B Chen, SC James
Journal of Marine Systems 186, 29-36, 2018
522018
Ensemble model aggregation using a computationally lightweight machine-learning model to forecast ocean waves
F O’Donncha, Y Zhang, B Chen, SC James
Journal of Marine Systems 199 (1), 103206, 2019
392019
Parallelisation study of a three-dimensional environmental flow model
F O'Donncha, E Ragnoli, F Suits
Computers & Geosciences 64, 96-103, 2014
292014
Data driven insight into fish behaviour and their use for precision aquaculture
F O'Donncha, CL Stockwell, SR Planellas, G Micallef, P Palmes, C Webb, ...
Frontiers in Animal Science 2, 695054, 2021
262021
Modelling study of the effects of suspended aquaculture installations on tidal stream generation in Cobscook Bay
F O'Donncha, SC James, E Ragnoli
Renewable Energy 102, 65-76, 2017
262017
A spatio-temporal LSTM model to forecast across multiple temporal and spatial scales
F O'Donncha, Y Hu, P Palmes, M Burke, R Filgueira, J Grant
Ecological Informatics 69, 101687, 2022
24*2022
Parameterizing suspended canopy effects in a three-dimensional hydrodynamic model
F O'Donncha, M Hartnett, DR Plew
Journal of Hydraulic Research 53 (6), 714-727, 2015
232015
An optimal interpolation scheme for assimilation of HF radar current data into a numerical ocean model
E Ragnoli, F O'Donncha, S Zhuk, F Suits, M Hartnett
Oceans, 2012, 1-5, 2012
122012
On the efficiency of executing hydro-environmental models on cloud
F O’Donncha, E Ragnoli, S Venugopal, SC James, K Katrinis
Procedia Engineering 154, 199-206, 2016
112016
Designing environmentally efficient aquafeeds through the use of multicriteria decision support tools
R Cooney, AHL Wan, F O'Donncha, E Clifford
Current Opinion in Environmental Science & Health 23, 100276, 2021
102021
Drag coefficient parameter estimation for aquaculture systems
SC James, F O’Donncha
Environmental Fluid Mechanics 19 (1), 989–1003, 2019
102019
Parallelisation of hydro-environmental model for simulating marine current devices
F O'Donncha, SC James, N O'brien, E Ragnoli
OCEANS 2015-MTS/IEEE Washington, 1-7, 2015
92015
Dynamic adaption of vessel trajectory using machine learning models
F O'donncha, E Ragnoli, C Sutherland
US Patent 11,119,250, 2021
82021
Surrogate modeling and risk-based analysis for solute transport simulations
E Arandia, F O’Donncha, S McKenna, S Tirupathi, E Ragnoli
Stochastic environmental research and risk assessment 33 (11), 1907-1921, 2019
82019
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