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Ivan Pisa
Ivan Pisa
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Cited by
Cited by
Year
ANN-based soft sensor to predict effluent violations in wastewater treatment plants
I Pisa, I Santín, JL Vicario, A Morell, R Vilanova
Sensors 19 (6), 1280, 2019
872019
LSTM-based wastewater treatment plants operation strategies for effluent quality improvement
I Pisa, I Santin, A Morell, JL Vicario, R Vilanova
IEEE Access 7, 159773-159786, 2019
382019
Denoising autoencoders and LSTM-based artificial neural networks data processing for its application to internal model control in industrial environments—The wastewater …
I Pisa, A Morell, JL Vicario, R Vilanova
Sensors 20 (13), 3743, 2020
312020
A recurrent neural network for wastewater treatment plant effuents' prediction
I Pisa, I Santín, J Lopez Vicario, A Morell, R Vilanova
Actas de las XXXIX Jornadas de Automática, Badajoz, 5-7 de Septiembre de 2018, 2018
222018
Adaptive beaconing for RSU-based intersection assistance systems: Protocols analysis and enhancement
G Boquet, I Pisa, JL Vicario, A Morell, J Serrano
Vehicular communications 14, 1-14, 2018
152018
Transfer learning in wastewater treatment plant control design: From conventional to long short-term memory-based controllers
I Pisa, A Morell, R Vilanova, JL Vicario
Sensors 21 (18), 6315, 2021
142021
Vaima: A v2v based intersection traffic management algorithm
I Pisa, G Boquet, JL Vicario, A Morell, J Serrano
2018 14th Annual Conference on Wireless On-demand Network Systems and …, 2018
132018
ANN-based Internal Model Control strategy applied in the WWTP industry
I Pisa, A Morell, JL Vicario, R Vilanova
2019 24th IEEE International Conference on Emerging Technologies and Factory …, 2019
122019
Data preprocessing for ANN-based industrial time-series forecasting with imbalanced data
I Pisa, I Santín, JL Vicario, A Morell, R Vilanova
2019 27th European Signal Processing Conference (EUSIPCO), 1-5, 2019
122019
Transfer learning approach for the design of basic control loops in wastewater treatment plants
I Pisa, A Morell, JL Vicario, R Vilanova
2021 26th IEEE International Conference on Emerging Technologies and Factory …, 2021
102021
Noisy Signals in Wastewater Treatment Plants data-driven control: Spectral Analysis approach for the design of ANN-IMC controllers
I Pisa, A Morell, R Vilanova, JL Vicario
2020 IEEE Conference on Industrial Cyberphysical Systems (ICPS) 1, 320-325, 2020
72020
Artificial neural networks application to support plant operation in the wastewater industry
I Pisa, R Vilanova, I Santín, JL Vicario, A Morell
Technological Innovation for Industry and Service Systems: 10th IFIP WG 5.5 …, 2019
72019
Analysis of adaptive beaconing protocols for intersection assistance systems
G Boquet, I Pisa, JL Vicario, A Morell, J Serrano
2018 14th Annual Conference on Wireless On-demand Network Systems and …, 2018
72018
LSTM-based IMC approach applied in Wastewater Treatment Plants: performance and stability analysis
I Pisa, A Morell, JL Vicario, R Vilanova
IFAC-PapersOnLine 53 (2), 16569-16574, 2020
62020
Transfer learning in wastewater treatment plants control: Measuring the transfer suitability
I Pisa, A Morell, JL Vicario, R Vilanova
Journal of Process Control 124, 36-53, 2023
42023
Industrial Control under Non-Ideal Measurements: Data-Based Signal Processing as an Alternative to Controller Retuning
I Pisa, A Morell, R Vilanova, JL Vicario
Sensors 21 (4), 1237, 2021
42021
Transfer Learning Suitability Metric for ANN-based Industrial Controllers
I Pisa, A Morell, JL Vicario, R Vilanova
2022 IEEE 27th International Conference on Emerging Technologies and Factory …, 2022
32022
A Mutual-Information based Transfer Suitability Metric for Industrial Control
JL Vicario, I Pisa, A Morell, R Vilanova
2023 IEEE 28th International Conference on Emerging Technologies and Factory …, 2023
12023
Artificial Neural Networks in the Wastewater Industry. From Conventional to Data-based Industrial Control
I Pisa
12022
On the generalization of Deep Learning models for AoA estimation in bluetooth indoor scenarios
I Pisa, G Boquet, X Vilajosana, B Martinez
Internet of Things, 101152, 2024
2024
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