Prati
Evdokia Tapoglou
Evdokia Tapoglou
Potvrđena adresa e-pošte na ec.europa.eu
Naslov
Citirano
Citirano
Godina
A spatio-temporal hybrid neural network-Kriging model for groundwater level simulation
E Tapoglou, GP Karatzas, IC Trichakis, EA Varouchakis
Journal of hydrology 519, 3193-3203, 2014
1202014
Groundwater-level forecasting under climate change scenarios using an artificial neural network trained with particle swarm optimization
E Tapoglou, IC Trichakis, Z Dokou, IK Nikolos, GP Karatzas
Hydrological Sciences Journal 59 (6), 1225-1239, 2014
632014
Hydrodynamic studies of floating structures: Comparison of wave-structure interaction modelling
W Sheng, E Tapoglou, X Ma, CJ Taylor, RM Dorrell, DR Parsons, ...
Ocean Engineering 249, 110878, 2022
472022
Integrated use of satellite remote sensing, artificial neural networks, field spectroscopy, and GIS in estimating crucial soil parameters in terms of soil erosion
DD Alexakis, E Tapoglou, AEK Vozinaki, IK Tsanis
Remote Sensing 11 (9), 1106, 2019
462019
Winter North Atlantic Oscillation impact on European precipitation and drought under climate change
I Tsanis, E Tapoglou
Theoretical and Applied Climatology 135, 323-330, 2019
392019
Satellite data for the offshore renewable energy sector: synergies and innovation opportunities
E Medina-Lopez, D McMillan, J Lazic, E Hart, S Zen, A Angeloudis, ...
Remote Sensing of Environment 264, 112588, 2021
302021
Climate change impact on the frequency of hydrometeorological extremes in the island of Crete
E Tapoglou, AE Vozinaki, I Tsanis
Water 11 (3), 587, 2019
262019
Hydrometeorological impact of climate change in two Mediterranean basins
AEK Vozinaki, E Tapoglou, IK Tsanis
International Journal of River Basin Management 16 (2), 245-257, 2018
202018
Time-domain implementation and analyses of multi-motion modes of floating structures
W Sheng, E Tapoglou, X Ma, CJ Taylor, R Dorrell, DR Parsons, G Aggidis
Journal of Marine Science and Engineering 10 (5), 662, 2022
172022
Machine learning for satellite-based sea-state prediction in an offshore windfarm
E Tapoglou, RM Forster, RM Dorrell, D Parsons
Ocean Engineering 235, 109280, 2021
162021
Hydraulic head uncertainty estimations of a complex artificial intelligence model using multiple methodologies
E Tapoglou, EA Varouchakis, IC Trichakis, GP Karatzas
Journal of Hydroinformatics 22 (1), 205-218, 2020
122020
The EU blue economy report 2024
A Borriello, A Calvo Santos, L Codina López, L Feyen, N Gaborieau, ...
62024
Clean Energy Technology Observatory: Ocean Energy in the European Union–2022 Status Report on Technology Development, Trends, Value Chains and Markets
E TAPOGLOU, A GEORGAKAKI, S LETOUT, A KUOKKANEN, ...
62022
Groundwater level forecasting using an artificial neural network trained with particle swarm optimization
E Tapoglou, IC Trichakis, Z Dokou, GP Karatzas
Proc. Geophysical Research, 2012
42012
Uncertainty estimations in different components of a hybrid ANN–Fuzzy–Kriging model for water table level simulation
E Tapoglou, EA Varouchakis, GP Karatzas
HIC 2018, 13th International Conference on Hydroinformatics, 2042-2050, 2018
32018
Comparison of a black-box model to a traditional numerical model for hydraulic head prediction.
E Tapoglou, A Chatzakis, GP Karatzas
32016
Temporal and Spatial prediction of groundwater levels using Artificial Neural Networks, Fuzzy logic and Kriging interpolation.
E Tapoglou, GP Karatzas, IC Trichakis, EA Varouchakis
EGU General Assembly Conference Abstracts, 773, 2014
32014
Wave power resource dynamics for the period 1980-2021 in Atlantic Europe's Northwest seas
IG Rizaev, RM Dorrell, CLG Oikonomou, E Tapoglou, C Hall, GA Aggidis, ...
ISOPE International Ocean and Polar Engineering Conference, ISOPE-I-23-093, 2023
22023
Clean Energy Technology Observatory: Wind energy in the European Union-2023 Status Report on Technology Development, Trends, Value Chains and Markets
E TAPOGLOU, J TATTINI, A SCHMITZ, A GEORGAKAKI, M DŁUGOSZ, ...
22023
Prévision du niveau des eaux souterraines dans les scénarios de changement climatique utilisant un réseau de neurones artificiels formé avec optimisation par essaim de particules
E Tapoglou, IC Trichakis, Z Dokou, IK Nikolos, GP Karatzas
Hydrol Sci J 59, 1225-1239, 2014
22014
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