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Details

  • Name

    Pedro Campos
  • Cluster

    Computer Science
  • Role

    Senior Researcher
  • Since

    01st January 2010
001
Publications

2022

Selection of features in reinforcement learning applied to energy consumption forecast in buildings according to different contexts

Authors
Ramos, D; Faria, P; Gomes, L; Campos, P; Vale, Z;

Publication
ENERGY REPORTS

Abstract
The management of buildings responsible for the energy storage and control can be optimized with the support of forecasting techniques. These are essential on the finding of load consumption patterns being these last involved in decisions that analyze which forecasting technique results in more accurate predictions in each context. This paper considers two forecasting methods known as artificial neural network and k-nearest neighbor involved in the prediction of consumption of a building composed by devices recording consumption and sensors data. The forecasts are performed in five minutes periods with the forecasting technique taken into account as a potential to improve the accuracy of predictions. The decision making considers the Multi-armed Bandit in reinforcement learning context to find the best suitable algorithm in each five minutes period thus improving the predictions accuracy in forecasting. The reinforcement learning has been tested in upper confidence bound and greedy algorithms with several exploration alternatives. In the case-study, three contexts have been analyzed. (C) 2022 The Author(s). Published by Elsevier Ltd.

2021

EMOS reloaded: Unlock the future of education in official statistics with a new partnership with Universities

Authors
Pratesi M.; Campos P.;

Publication
Statistical Journal of the IAOS

Abstract
After 12 years of EMOS experience it is time to open the discussion on the future of EMOS. This papers briefly describes the experience from the perspective of the Universities, trying also to describe the needs and role of the NSIs, Banks and other possible actors to join the network, and unlock the future. EMOS should reload (or evolute) to stay current and attractive. Statistical 'thinking' evolved and a major change and challenge for EMOS is to pick up this trend in its cooperation with the universities.

2020

Determinants of university employee intrapreneurial behavior: The case of Latvian universities

Authors
Valka, K; Roseira, C; Campos, P;

Publication
INDUSTRY AND HIGHER EDUCATION

Abstract
As the ongoing evolution in the higher education sector changes the roles of universities, entrepreneurial practices become more prominent in their agendas. The literature on academic entrepreneurship focuses predominantly on the commercialization of research and less on other intrapreneurial activities—namely those performed by non-academic employees. To fill this gap, this study aims to provide a comprehensive understanding of the factors that influence universities’ faculty members and non-academic staff to engage in intrapreneurial activities. The article analyzes Latvian university employees’ perceptions of 13 organizational, individual, and environmental factors and how they influence intrapreneurial behavior. Regarding the organizational factors, the results show that higher trust in managers, more available resources for innovative ideas, less formal rules and procedures, and greater freedom in decision-making can lead to higher levels of intrapreneurial behavior. With regard to individual factors, intrapreneurial behavior is associated with an employee’s initiative, but is not correlated with risk-taking and personal initiative. As to external factors, while environmental munificence is positively correlated with innovativeness, dynamism and unfavorable change influence employees’ engagement in intrapreneurial activities.

2020

Evolution of Business Collaboration Networks: An Exploratory Study Based on Multiple Factor Analysis

Authors
Duarte, P; Campos, P;

Publication
Advances in Intelligent Systems and Computing

Abstract

2020

New contributions for the comparison of community detection algorithms in attributed networks

Authors
Vieira, AR; Campos, P; Brito, P;

Publication
JOURNAL OF COMPLEX NETWORKS

Abstract
Community detection techniques use only the information about the network topology to find communities in networks Similarly, classic clustering techniques for vector data consider only the information about the values of the attributes describing the objects to find clusters. In real-world networks, however, in addition to the information about the network topology, usually there is information about the attributes describing the vertices that can also be used to find communities. Using both the information about the network topology and about the attributes describing the vertices can improve the algorithms' results. Therefore, authors started investigating methods for community detection in attributed networks. In the past years, several methods were proposed to uncover this task, partitioning a graph into sub-graphs of vertices that are densely connected and similar in terms of their descriptions. This article focuses on the analysis and comparison of some of the proposed methods for community detection in attributed networks. For that purpose, several applications to both synthetic and real networks are conducted. Experiments are performed on both weighted and unweighted graphs. The objective is to establish which methods perform generally better according to the validation measures and to investigate their sensitivity to changes in the networks' structure and homogeneity.

Supervised
thesis

2021

Sistema de Recomendação baseado em Reinforcement Learning: uma prova de conceito aplicada ao Video on Demand

Author
Daniel Carvalho Marques

Institution
UP-FEP

2021

content based image retrieval as a computer aided diagnosis tool for radiologists

Author
José Ricardo Ferreira de Castro Ramos

Institution
UP-FEUP

2021

Análise Multicamada com Atributos da Rede de Comércio da União Europeia

Author
Vanessa Correia Pinto

Institution
UP-FEP

2021

Previsão de investimentos com base em informação esparsa

Author
João Pedro Espírito Santo Almeida

Institution
UP-FEUP

2021

A internacionalização para mercados não desenvolvidos: motivações e barreiras

Author
Jonathan Bastos Lampaça

Institution
UP-FEP