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Jérôme Mendes
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2020 – today
- 2024
- [j12]Rui Queiroz
, Tiago Cruz
Container-based Virtualization for Real-time Industrial Systems - A Systematic Review. ACM Comput. Surv. 56(3): 59:1-59:38 (2024) - [j11]Jorge Pereira
Metaheuristic algorithms for calibration of two-dimensional wildfire spread prediction model. Eng. Appl. Artif. Intell. 136: 108928 (2024) - 2023
- [j10]Jorge Sampaio Silveira Junior
Survey on Deep Fuzzy Systems in Regression Applications: A View on Interpretability. Int. J. Fuzzy Syst. 25(7): 2568-2589 (2023) - [c26]Jorge Alves, Pedro Sousa, Bárbara Matos, Jérôme Mendes
Modular Cyber-Physical System for Smart Industry: a case study on energy load disaggregation. ICCAD 2023: 1-6 - [c25]Joana Leiria, Rodrigo Salles, Jérôme Mendes
Soft Sensors for Industrial Applications: Comparison of Variables Selection Methods and Regression Models. ICCAD 2023: 1-6 - [c24]Jorge Sampaio Silveira Junior, Jérôme Mendes
Hybrid LSTM-Fuzzy System to Model a Sulfur Recovery Unit. ICINCO (2) 2023: 281-288 - [c23]Nuno Mendes
Federated Learning Optimization for Energy Communities in Smart Cities. ISC2 2023: 1-7 - 2022
- [j9]Manuel Gonçalves, Pedro Angelo Morais de Sousa, Jérôme Mendes
Real-Time Event-Driven Learning in Highly Volatile Systems: A Case for Embedded Machine Learning for SCADA Systems. IEEE Access 10: 50794-50806 (2022) - [j8]Jorge Sampaio Silveira Junior
Automatic forest fire danger rating calibration: Exploring clustering techniques for regionally customizable fire danger classification. Expert Syst. Appl. 193: 116380 (2022) - [c22]Ricardo Maia, Jérôme Mendes
Electric Vehicle Physical Parameters Identification. IECON 2022: 1-7 - [c21]Jorge Pereira, Jérôme Mendes
Wildfire Spread Prediction Model Calibration Using Metaheuristic Algorithms. IECON 2022: 1-6 - [c20]Rodrigo Salles, Jérôme Mendes
Dynamic Setpoint Optimization Using Metaheuristic Algorithms for Wastewater Treatment Plants. IECON 2022: 1-6 - [c19]Rodrigo Salles, Jérôme Mendes
Prediction of Key Variables in Wastewater Treatment Plants Using Machine Learning Models. IJCNN 2022: 1-9 - [c18]Nuno Mendes
Federated Learning Enabled Prediction of Energy Consumption in Transactive Energy Communities. ISGT-Europe 2022: 1-5 - [c17]Rodrigo Salles, Jérôme Mendes
Fault Detection in Wastewater Treatment Plants: Application of Autoencoders Models with Streaming Data. PKDD/ECML Workshops (1) 2022: 55-70 - [i1]Jorge Sampaio Silveira Junior, Jérôme Mendes, Francisco Souza, Cristiano Premebida:
Survey on Deep Fuzzy Systems in regression applications: a view on interpretability. CoRR abs/2209.04230 (2022) - 2021
- [c16]Jorge Sampaio Silveira Junior
Novelty Detection for Iterative Learning of MIMO Fuzzy Systems. INDIN 2021: 1-7 - 2020
- [j7]Ricardo Maia
Regenerative braking system modeling by fuzzy Q-Learning. Eng. Appl. Artif. Intell. 93: 103712 (2020) - [c15]Jorge Sampaio Silveira Junior
Automatic Calibration of Forest Fire Weather Index For Independent Customizable Regions Based on Historical Records. AIKE 2020: 1-8
2010 – 2019
- 2019
- [j6]Jérôme Mendes
Neo-fuzzy neuron learning using backfitting algorithm. Neural Comput. Appl. 31(8): 3609-3618 (2019) - [c14]Jérôme Mendes
Iterative Learning of Multiple Univariate Zero-Order T-S Fuzzy Systems. IECON 2019: 3803-3808 - 2018
- [c13]Jérôme Mendes
Intelligent Controller for Industrial Processes Applied to a Distributed Two-Tank System. AI4I 2018: 39-43 - [c12]Carlos Alberto Belchior, Rui Araújo, Jérôme Mendes
H∞ Adaptive Fuzzy Control Approach Applied to Antilock-Braking Systems Over a CAN Network. ETFA 2018: 910-917 - 2017
- [j5]Saeid Rastegar
A novel robust control scheme for LTV systems using output integral discrete-time synergetic control theory. Eur. J. Control 34: 39-48 (2017) - [c11]Jérôme Mendes
Online evolving fuzzy control design: An application to a CSTR plant. INDIN 2017: 218-225 - 2014
- [j4]Jérôme Mendes
Automatic extraction of the fuzzy control system by a hierarchical genetic algorithm. Eng. Appl. Artif. Intell. 29: 70-78 (2014) - [c10]Tiago Matias
Adaptive identification and predictive control using an improved on-line sequential extreme learning machine. IECON 2014: 58-64 - [c9]Jérôme Mendes
Evolutionary learning of a fuzzy controller for industrial processes. IECON 2014: 139-145 - [c8]Saeid Rastegar
Self-adaptive Takagi-Sugeno model identification methodology for industrial control processes. IECON 2014: 281-287 - 2013
- [j3]Jérôme Mendes
Adaptive fuzzy identification and predictive control for industrial processes. Expert Syst. Appl. 40(17): 6964-6975 (2013) - [c7]Luís Osório, Jérôme Mendes
A comparison of adaptive PID methodologies controlling a DC motor with a varying load. ETFA 2013: 1-6 - 2012
- [j2]Jérôme Mendes
Genetic fuzzy system for data-driven soft sensors design. Appl. Soft Comput. 12(10): 3237-3245 (2012) - [c6]Jérôme Mendes
Evolutionary fuzzy models for nonlinear identification. ETFA 2012: 1-8 - [c5]Jérôme Mendes
Fuzzy model predictive control for nonlinear processes. ETFA 2012: 1-8 - 2011
- [j1]Jérôme Mendes
An architecture for adaptive fuzzy control in industrial environments. Comput. Ind. 62(3): 364-373 (2011) - [c4]Jérôme Mendes
Stable indirect adaptive predictive fuzzy control for industrial processes. ETFA 2011: 1-8 - [c3]Jérôme Mendes
Automatic extraction of the fuzzy control system for industrial processes. ETFA 2011: 1-8 - [c2]Jérôme Mendes
Adaptive predictive control with recurrent fuzzy neural network for industrial processes. ETFA 2011: 1-8 - 2010
- [c1]Jérôme Mendes
Adaptive fuzzy generalized predictive control based on Discrete-Time T-S fuzzy model. ETFA 2010: 1-8
Coauthor Index
aka: Francisco Alexandre A. Souza
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