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Riccardo Taormina
Riccardo Taormina
Assistant Professor, Department of Water Management, TU Delft
Verified email at tudelft.nl - Homepage
Title
Cited by
Cited by
Year
Artificial neural network simulation of hourly groundwater levels in a coastal aquifer system of the Venice lagoon
R Taormina, K Chau, R Sethi
Engineering Applications of Artificial Intelligence 25 (8), 1670-1676, 2012
4612012
Data-driven input variable selection for rainfall–runoff modeling using binary-coded particle swarm optimization and Extreme Learning Machines
R Taormina, KW Chau
Journal of hydrology 529, 1617-1632, 2015
3232015
Neural network river forecasting through baseflow separation and binary-coded swarm optimization
R Taormina, KW Chau, B Sivakumar
Journal of Hydrology 529, 1788-1797, 2015
2272015
ANN-based interval forecasting of streamflow discharges using the LUBE method and MOFIPS
R Taormina, KW Chau
Engineering Applications of Artificial Intelligence 45, 429-440, 2015
2172015
Battle of the attack detection algorithms: Disclosing cyber attacks on water distribution networks
R Taormina, S Galelli, NO Tippenhauer, E Salomons, A Ostfeld, ...
Journal of Water Resources Planning and Management 144 (8), 04018048, 2018
1722018
Characterizing cyber-physical attacks on water distribution systems
R Taormina, S Galelli, NO Tippenhauer, E Salomons, A Ostfeld
Journal of Water Resources Planning and Management 143 (5), 04017009, 2017
1652017
A review of cybersecurity incidents in the water sector
A Hassanzadeh, A Rasekh, S Galelli, M Aghashahi, R Taormina, ...
Journal of Environmental Engineering 146 (5), 03120003, 2020
1612020
Neural network river forecasting with multi-objective fully informed particle swarm optimization
R Taormina, K Chau
Journal of Hydroinformatics 17 (1), 99-113, 2015
1362015
Deep-learning approach to the detection and localization of cyber-physical attacks on water distribution systems
R Taormina, S Galelli
Journal of Water Resources Planning and Management 144 (10), 04018065, 2018
942018
Deep learning methods for flood mapping: a review of existing applications and future research directions
R Bentivoglio, E Isufi, SN Jonkman, R Taormina
Hydrology and Earth System Sciences 26 (16), 4345-4378, 2022
832022
Identifying (quasi) equally informative subsets in feature selection problems for classification: a max-relevance min-redundancy approach
G Karakaya, S Galelli, SD Ahipaşaoğlu, R Taormina
IEEE transactions on cybernetics 46 (6), 1424-1437, 2015
582015
A toolbox for assessing the impacts of cyber-physical attacks on water distribution systems
R Taormina, S Galelli, HC Douglas, NO Tippenhauer, E Salomons, ...
Environmental modelling & software 112, 46-51, 2019
572019
Constrained concealment attacks against reconstruction-based anomaly detectors in industrial control systems
A Erba, R Taormina, S Galelli, M Pogliani, M Carminati, S Zanero, ...
Annual Computer Security Applications Conference, 480-495, 2020
492020
Machine Learning‐Based Surrogate Modeling for Urban Water Networks: Review and Future Research Directions
A Garzón, Z Kapelan, J Langeveld, R Taormina
Water Resources Research 58 (5), e2021WR031808, 2022
432022
Beyond image analysis in processing archaeomagnetic geophysical data: case studies of chamber tombs with dromos
S Piro, L Sambuelli, A Godio, R Taormina
Near Surface Geophysics 5 (6), 405-414, 2007
382007
Battle of the leakage detection and isolation methods
SG Vrachimis, DG Eliades, R Taormina, Z Kapelan, A Ostfeld, S Liu, ...
Journal of Water Resources Planning and Management 148 (12), 04022068, 2022
262022
Real-time evasion attacks with physical constraints on deep learning-based anomaly detectors in industrial control systems
A Erba, R Taormina, S Galelli, M Pogliani, M Carminati, S Zanero, ...
arXiv preprint arXiv:1907.07487, 2019
232019
An information theoretic approach to select alternate subsets of predictors for data-driven hydrological models
R Taormina, S Galelli, G Karakaya, SD Ahipasaoglu
Journal of Hydrology 542, 18-34, 2016
232016
On the value of ENSO state for urban water supply system operators: Opportunities, trade‐offs, and challenges
CP Libisch‐Lehner, HTT Nguyen, R Taormina, HP Nachtnebel, S Galelli
Water Resources Research 55 (4), 2856-2875, 2019
222019
Deep learning for detecting macroplastic litter in water bodies: A review
T Jia, Z Kapelan, R de Vries, P Vriend, EC Peereboom, I Okkerman, ...
Water Research, 119632, 2023
202023
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