Idelfonso B. R. Nogueira

Orcid: 0000-0002-0963-6449

According to our database1, Idelfonso B. R. Nogueira authored at least 25 papers between 2016 and 2024.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of five.

Timeline

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Bibliography

2024
Adaptive digital twin for pressure swing adsorption systems: Integrating a novel feedback tracking system, online learning and uncertainty assessment for enhanced performance.
Eng. Appl. Artif. Intell., January, 2024

Molecule Generation and Optimization for Efficient Fragrance Creation.
CoRR, 2024

2023
Optimizing CO<sub>2</sub> Capture in Pressure Swing Adsorption Units: A Deep Neural Network Approach with Optimality Evaluation and Operating Maps for Decision-Making.
CoRR, 2023

Digital Twin Framework for Optimal and Autonomous Decision-Making in Cyber-Physical Systems: Enhancing Reliability and Adaptability in the Oil and Gas Industry.
CoRR, 2023

Identifying Systems with Symmetries using Equivariant Autoregressive Reservoir Computers.
CoRR, 2023

Dynamic financial processes identification using sparse regressive reservoir computers.
CoRR, 2023

PUFFIN: A Path-Unifying Feed-Forward Interfaced Network for Vapor Pressure Prediction.
CoRR, 2023

Efficient hybrid modeling and sorption model discovery for non-linear advection-diffusion-sorption systems: A systematic scientific machine learning approach.
CoRR, 2023

2022
A new Takagi-Sugeno-Kang model-based stabilizing explicit MPC formulation: An experimental case study with implementation embedded in a PLC.
Expert Syst. Appl., 2022

A Robust Scientific Machine Learning for Optimization: A Novel Robustness Theorem.
CoRR, 2022

A new Reinforcement Learning framework to discover natural flavor molecules.
CoRR, 2022

A Robust Learning Methodology for Uncertainty-aware Scientific Machine Learning models.
CoRR, 2022

A long short-term memory based Quasi-Virtual Analyzer for dynamic real-time soft sensing of a Simulated Moving Bed unit.
Appl. Soft Comput., 2022

2021
Optimal fragrances formulation using a deep learning neural network architecture: A novel systematic approach.
Comput. Chem. Eng., 2021

2020
Transient analysis of true/simulated moving bed reactors: A case study on the synthesis of n-Propyl propionate.
Comput. Chem. Eng., 2020

A robustly model predictive control strategy applied in the control of a simulated industrial polyethylene polymerization process.
Comput. Chem. Eng., 2020

2019
Chromatographic studies of n-Propyl Propionate, Part II: Synthesis in a fixed bed adsorptive reactor, modelling and uncertainties determination.
Comput. Chem. Eng., 2019

Optimization strategies for chiral separation by true moving bed chromatography using Particles Swarm Optimization (PSO) and new Parallel PSO variant.
Comput. Chem. Eng., 2019

Optimization of a True Moving Bed unit and determination of its feasible operating region using a novel Sliding Particle Swarm Optimization.
Comput. Ind. Eng., 2019

2018
Chromatographic studies of n-Propyl Propionate: Adsorption equilibrium, modelling and uncertainties determination.
Comput. Chem. Eng., 2018

A quasi-virtual online analyser based on an artificial neural networks and offline measurements to predict purities of raffinate/extract in simulated moving bed processes.
Appl. Soft Comput., 2018

2017
Dynamic response to process disturbances - A comparison between TMB/SMB models in transient regime.
Comput. Chem. Eng., 2017

Parameter estimation with estimability analysis applied to an industrial scale polymerization process.
Comput. Chem. Eng., 2017

A model-based approach to quality monitoring of a polymerization process without online measurement of product specifications.
Comput. Ind. Eng., 2017

2016
Dynamics of a True Moving Bed separation process: Effect of operating variables on performance indicators using orthogonalization method.
Comput. Chem. Eng., 2016


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