Rui Araújo – Softwares
Repositories
Below there are some links to softwares associated to research works and publications.
• Mixture partial least square experts (Mix-PLS)
The Mix-PLS is a mixture of experts models based on the partial least squares (PLS) algorithm. It was designed to be applied in prediction settings composed by multiple operating modes and/or non-linear carachteristics. The MIX-PLS can be downloaded below.
Mix-PLS Toolbox source code (Matlab implementation)
In case of publication please cite the original paper: Francisco A. A. Souza and Rui Araújo. Mixture of partial least squares experts and application in prediction settings with multiple operating modes. Chemometrics and Intelligent Laboratory Systems, 130:192–202, January 2014. [ bib | DOI | .pdf ].
• Eigenvalue decay for neural network regularization
A toolbox for neural network regularization.
Source code (Matlab implementation)
In case of publication please cite the paper: Oswaldo Ludwig, Urbano Nunes, and Rui Araújo. Eigenvalue decay: a new method for neural network regularization. Neurocomputing, 124:33–42, January 2014. [ bib | DOI | .pdf ].
• Optimized extreme learning machine (O-ELM)
The O-ELM is a extreme learning machine (ELM) based model where the input connections and the hidden layers are selected based on genetic algorithms in a way to optmize the ELM model performance. The O-ELM-PLS can be downloaded below.
O-ELM Toolbox source code (Matlab implementation)
In case of publication please cite the paper: Tiago Matias, Francisco Souza, Rui Araújo, and Carlos Henggeler Antunes. Learning of a single-hidden layer feedforward neural network using an optimized extreme learning machine. Neurocomputing, 129:428–436, April 2014. [ bib | DOI | .pdf ].
• Online mixture of univariate linear regression models (MULRM)
The MULRM is an online mixture of univariate models for regression.
MULRM Toolbox source code (Matlab implementation)
In case of publication please cite the paper: Francisco Souza and Rui Araújo. Online mixture of univariate linear regression models for adaptive soft sensors. IEEE Transactions on Industrial Informatics, 10(2):937–945, May 2014. [ bib | DOI | .pdf ].
• Fuzzy logic model for regenerative braking (FLmRB)
A fuzzy logic toolbox for modeling vehicle regenerative braking.
FLmRB Toolbox source code (Matlab implementation)
In case of publication please cite the paper: Ricardo Maia, Marco Silva, Rui Araújo, and Urbano Nunes. Electrical vehicle modeling: A fuzzy logic model for regenerative braking. Expert Systems with Applications, 42(22):8504–8519, December 2015. [ bib | DOI | .pdf ].
• On-line weighted ensemble (OWE) of regressor models to handle concept drifts
A toolbox of an on-line weighted ensemble (OWE) of regressor models to handle concept drifts.
OWE Toolbox source code (Matlab implementation)
In case of publication please cite the paper: Symone Gomes Soares and Rui Araújo. An on-line weighted ensemble of regressor models to handle concept drifts. Engineering Applications of Artificial Intelligence, 37:392–406, January 2015. [ bib | DOI | .pdf ].
• Dynamic and on-line ensemble regression (DOER) for changing environments
A toolbox for dynamic and on-line ensemble regression (DOER) for changing environments.
DOER Toolbox source code (Matlab implementation)
In case of publication please cite the paper: Symone G. Soares and Rui Araújo. A dynamic and on-line ensemble regression for changing environments. Expert Systems with Applications, 42(6):2935–2948, April 2015. [ bib | DOI | .pdf ].
• Adaptive ensemble of on-line extreme learning machines (OEOA)
A toolbox of an adaptive ensemble of on-line extreme learning machines (OEOA) for non-stationary, time-varying, system prediction.
OEOA Toolbox source code (Matlab implementation)
In case of publication please cite the paper: Symone G. Soares and Rui Araújo. An adaptive ensemble of on-line extreme learning machines with variable forgetting factor for dynamic system prediction. Neurocomputing, 171:693–707, January 2016. [ bib | DOI | .pdf ].
• The SEDFLC Toolbox
A toolbox to self-evolve an online fuzzy logic controller, associated to the paper below.
The SEDFLC Toolbox source code (Matlab implementation)
In case of publication please cite the paper: Jérôme Mendes, Francisco Souza, and Rui Araújo, Online evolving fuzzy control design: An application to a CSTR plant. Proc. IEEE 15th International Conference on Industrial Informatics (INDIN 2017), pp. 218-225, Emden, Germany, July 24-26, 2017. [ bib | DOI | .pdf ].
• The Self-Tuning PID Controllers Toolbox
A toolbox of self-tuning PID controllers associated to the paper below.
The Self-Tuning PID Controllers Toolbox source code (Scilab implementation)
In case of publication please cite the paper: Jérôme Mendes, Luís Osório, and Rui Araújo. Self-tuning pid controllers in pursuit of plug and play capacity. Control Engineering Practice, 69:73–84, December 2017. [ bib | DOI | .pdf ].
• The GAM-ZOTS Toolbox
A toolbox for learning multiple univariate additive models for identification purposes, associated to the paper below.
The GAM-ZOTS Toolbox source code (Matlab implementation)
In case of publication please cite the paper: Jérôme Mendes, Francisco Souza, Rui Araújo, and Saeid Rastegar. Neo-fuzzy neuron learning using backfitting algorithm. Neural Computing and Applications, 31(8):3609–3618, August 2019. [ bib | DOI | .pdf ].
• The iMU-ZOTS Toolbox
A toolbox for iterative learning of multiple univariate zero-order t-s fuzzy systems, associated to the paper below.
The GAM-ZOTS Toolbox source code (Matlab implementation)
In case of publication please cite the paper: Jérôme Mendes, Francisco A. A. Souza, Ricardo Maia, and Rui Araújo. Iterative learning of multiple univariate zero-order t-s fuzzy systems. In Proc. of the The IEEE 45th Annual Conference of the Industrial Electronics Society (IECON 2019), pages 3657–3662, Lisbon, Portugal, October 14-17 2019. [ bib | DOI | .pdf ].
• The uSelf-FLC Toolbox
A toolbox for self-evolving fuzzy controllers composed of univariate fuzzy control rules, associated to the paper below.
The uSelf-FLC Toolbox source code (Matlab implementation)
In case of publication please cite the paper: Jérôme Mendes, Ricardo Maia, Rui Araújo, and Francisco A. A. Souza. Self-evolving fuzzy controller composed of univariate fuzzy control rules, Applied Sciences, 10(17):5836, August 2020. [ bib | DOI | .pdf ].
