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About

About

E. J. Solteiro Pires received the B.Sc. degree in electrical engineering from the University of Coimbra, Coimbra, Portugal, in 1994, the M.Sc. degree in electrical and computer engineering from the University of Porto, Porto, Portugal, in 1999, and the Ph.D. degree from the University of Trás-os-Montes and Alto Douro (UTAD), Vila Real, Portugal, in 2006. He is currently an Auxiliary Professor with UTAD. His current research interests include evolutionary computation, soft computing, multiobjective problems, and robotics.

Interest
Topics
Details

Details

Publications

2020

Review of nature and biologically inspired metaheuristics for greenhouse environment control

Authors
Oliveira, PM; Solteiro Pires, EJ; Boaventura Cunha, J; Pinho, TM;

Publication
Transactions of the Institute of Measurement and Control

Abstract
A significant number of search and optimisation techniques whose principles seek inspiration from nature and biology phenomena have been proposed in the last decades. These methods have been successfully applied to solve a wide range of engineering problems. This is also the case of greenhouse environment control, which has been incorporating this type of techniques into its design. This paper addresses evolutionary and bio-inspired methods in the context of greenhouse environment control. Algorithm principles for reference techniques are reviewed, namely: simulated annealing, genetic algorithm, differential evolution and particle swarm optimisation. The last three techniques are considered using single and multiple objective formulations. A review of these algorithms within greenhouse environment control applications is presented, considering single and multiple objective problems, as well as their current trends. © The Author(s) 2020.

2019

Dynamic shannon performance in a multiobjective particle swarm optimization

Authors
Solteiro Pires, EJS; Tenreiro Machado, JAT; de Moura Oliveira, PBD;

Publication
Entropy

Abstract
Particle swarm optimization (PSO) is a search algorithm inspired by the collective behavior of flocking birds and fishes. This algorithm is widely adopted for solving optimization problems involving one objective. The evaluation of the PSO progress is usually measured by the fitness of the best particle and the average fitness of the particles. When several objectives are considered, the PSO may incorporate distinct strategies to preserve nondominated solutions along the iterations. The performance of the multiobjective PSO (MOPSO) is usually evaluated by considering the resulting swarm at the end of the algorithm. In this paper, two indices based on the Shannon entropy are presented, to study the swarm dynamic evolution during the MOPSO execution. The results show that both indices are useful for analyzing the diversity and convergence of multiobjective algorithms. © 2019 by the authors.

2019

Genetic algorithm applied to remove noise in DICOM images

Authors
Saraiva, AA; de Oliveira, MS; de Moura Oliveira, PBD; Solteiro Pires, EJS; Fonseca Ferreira, NMF; Valente, A;

Publication
Journal of Information and Optimization Sciences

Abstract

2019

Breast Cancer Diagnosis using a Neural Network

Authors
Ribeiro, V; Solteiro Pires, EJS; de Moura Oliveira, PBD;

Publication
2019 6TH IEEE PORTUGUESE MEETING IN BIOENGINEERING (ENBENG)

Abstract
This work presents a neural network used to diagnosis patients with benign or malignant breast cancer. The study is carried out using the Breast Cancer Wisconsin dataset. To solve the problem a feedforward neural network (NN) with multilayers was used. In the work, the implementation was made in Python, using two different libraries (sklearn and keras). Experimental results were obtained by performing simulations in both developed applications, and the performance of the neural classifier was evaluated through the performance measures of the classification systems and the ROC curve. The results were promising, since the NN was able to discriminate with high accuracy the two separable sets discriminating the benign or malignant tumor patients.

2018

Stability of multidimensional systems using bio-inspired meta-heuristics

Authors
Solteiro Pires, EJS; de Moura Oliveira, PBD; Tenreiro Machado, JAT;

Publication
International Journal of Control

Abstract

Supervised
thesis

2019

Chat Bot -o diagmóstico de bolso

Author
Duarte Rui Afonso Gomes Tavares do Amaral

Institution
UTAD

2019

ADAPT – Plataforma Adaptativa de Ensino à Distância

Author
Eduardo Jorge Dinis Pratas

Institution
UTAD

2018

Diagnóstico Automático no Cancro da Mama

Author
Vera Susana Ribeiro

Institution
UTAD

2018

Sistemas Baseados em casos: Aplicação à Saúde

Author
Stéfanie Maria da Costa Alves

Institution
UTAD

2018

Análise da variabilidade da frequência cardíaca em indivíduos saudáveis e doentes

Author
Cristina Monteiro Pinto

Institution
UTAD