R. Taormina

发表

An information theoretic approach to select alternate subsets of predictors for data-driven hydrological models

S. Galelli, R. Taormina, G. Karakaya, 2016 .

Artificial Neural Network simulation of hourly 3 groundwater levels in a coastal aquifer system of the 4 Venice lagoon

K. Chau, R. Taormina, R. Sethi, 2012 .

A toolbox for assessing the impacts of cyber-physical attacks on water distribution systems

Avi Ostfeld, Elad Salomons, Nils Ole Tippenhauer, 2019, Environ. Model. Softw..

Co-Simulating Physical Processes and Network Data for High-Fidelity Cyber-Security Experiments

Nils Ole Tippenhauer, Andrés Murillo, S. Galelli, 2020 .

Artificial Neural Network simulation of hourly

K. Chau, R. Taormina, R. Sethi, 2012 .

A Review of Cybersecurity Incidents in the Water Sector pdf

Avi Ostfeld, Amin Rasekh, Riccardo Taormina, 2020, ArXiv.

Deep Learning Methods for Flood Mapping: A Review of Existing Applications and Future Research Directions

R. Taormina, E. Isufi, Roberto Bentivoglio, 2021, Hydrology and Earth System Sciences.

Machine Learning‐Based Surrogate Modeling for Urban Water Networks: Review and Future Research Directions

R. Taormina, Z. Kapelan, J. Langeveld, 2022, Water Resources Research.

Deep learning methods for ﬂood mapping: a review of existing applications and future research directions

R. Taormina, E. Isufi, Roberto Bentivoglio, 2022 .

Assessing the Effect of Cyber-Physical Attacks on Water Distribution Systems

Avi Ostfeld, Elad Salomons, Nils Ole Tippenhauer, 2016 .

Simulation of Cyber-Physical Attacks on Water Distribution Systems with EPANET

Avi Ostfeld, Elad Salomons, Nils Ole Tippenhauer, 2016, SG-CRC.

BattLeDIM: Battle of the Leakage Detection and Isolation Methods

Demetrios G. Eliades, Eliades, Stelios G. Vrachimis, 2020 .

A Review of Cybersecurity Incidents in the Water Sector

S. Galelli, R. Taormina, A. Rasekh, 2020, Journal of Environmental Engineering.

Artificial neural network simulation of hourly groundwater levels in a coastal aquifer system of the Venice lagoon

Rajandrea Sethi, Kwok-Wing Chau, Riccardo Taormina, 2012, Eng. Appl. Artif. Intell..

On the Value of ENSO State for Urban Water Supply System Operators: Opportunities, Trade‐Offs, and Challenges

H. P. Nachtnebel, S. Galelli, S. Galelli, 2019, Water Resources Research.

Deep learning for detecting macroplastic litter in water bodies: A review.

E. Peereboom, R. Taormina, Z. Kapelan, 2023, Water research.

Characterizing Cyber-Physical Attacks on Water Distribution Systems

Avi Ostfeld, Elad Salomons, Nils Ole Tippenhauer, 2017 .

Beyond image analysis in processing archaeomagnetic geophysical data: case studies of chamber tombs with dromos.

R. Taormina, S. Piro, L. Sambuelli, 2007 .

Battle of the Attack Detection Algorithms: Disclosing Cyber Attacks on Water Distribution Networks

Avi Ostfeld, Idel Montalvo, Enrique Campbell, 2018, Journal of Water Resources Planning and Management.

ANN-based interval forecasting of streamflow discharges using the LUBE method and MOFIPS

Kwok-Wing Chau, Riccardo Taormina, K. Chau, 2015, Eng. Appl. Artif. Intell..

Neural network river forecasting through baseflow separation and binary-coded swarm optimization

Bellie Sivakumar, Riccardo Taormina, Kwok-wing Chau, 2015 .

Data-driven input variable selection for rainfall-runoff modeling using binary-coded particle swarm optimization and Extreme Learning Machines

Kwok-wing Chau, Riccardo Taormina, K. Chau, 2015 .

Constrained Concealment Attacks against Reconstruction-based Anomaly Detectors in Industrial Control Systems

Stefano Zanero, Nils Ole Tippenhauer, Michele Carminati, 2020, ACSAC.

Deep-Learning Approach to the Detection and Localization of Cyber-Physical Attacks on Water Distribution Systems

Riccardo Taormina, Stefano Galelli, S. Galelli, 2018, Journal of Water Resources Planning and Management.

The Role of Water Vapor Observations in Satellite Rainfall Detection Highlighted by a Deep Learning Approach

R. Taormina, N. C. van de Giesen, Marie-claire ten Veldhuis, 2023, Atmosphere.

RainRunner The role of water vapor observations in satellite-based rainfall information highlighted by a Deep Learning approach

R. Taormina, Fabio Curzi, M. E. Camarena, 2022 .

Identifying (Quasi) Equally Informative Subsets in Feature Selection Problems for Classification: A Max-Relevance Min-Redundancy Approach

Selin Damla Ahipasaoglu, Riccardo Taormina, Stefano Galelli, 2016, IEEE Transactions on Cybernetics.

Predicting streamflow with LSTM networks using global datasets

R. Taormina, M. Hrachowitz, Marie-claire ten Veldhuis, 2023, Frontiers in Water.

Disclosing Cyber Attacks on Water Distribution Systems. An Experimental Approach to the Sonification of Threats and Anomalous Data

Paolo Ciuccarelli, Riccardo Taormina, Stefano Galelli, 2019, Proceedings of the 25th International Conference on Auditory Display (ICAD 2019).

Machine learning-based surrogate modelling for Urban Water Networks: Review and future research directions

R. Taormina, Z. Kapelan, J. Langeveld, 2021 .

Smart Urban Water Networks: Solutions, Trends and Challenges

Enrico Creaco, Manuel Herrera, Dominic L. Boccelli, 2021 .

The Potential of Deep Learning for Satellite Rainfall Detection over Data-Scarce Regions, the West African Savanna

R. Taormina, M. Veldhuis, Mónica Estébanez-Camarena, 2023, Remote Sensing.

Graph-Time Convolutional Autoencoders

R. Taormina, A. Hanjalic, E. Isufi, 2022, LOG IN.

Generalizing rapid flood predictions to unseen urban catchments with conditional generative adversarial networks

R. Taormina, E. Mendiondo, M. Giacomoni, 2023, Journal of Hydrology.