307 documents found, page 1 of 31
A Benchmark of Automated Multivariate Time Series Forecasting Tools for Smart C...
Pereira, Pedro José; Costa, Nuno; Mestre, Pedro; Cortez, PauloMost Smart Cities data come from multiple related sensors. Within this context, multivariate Automated Time Series Forecasting (AutoTSF) tools are valuable for providing predictive analytics for citizens and city rulers. In this paper, we benchmark seven multivariate open-source AutoTSF tools (AutoARIMAX, AutoGluon, FlaML, AutoTS, MFEDOT and HyperTS) and one univariate AutoTSF tool (FEDOT), measuring both their...
A context-aware decision support system for selecting explainable artificial in...
Reis, Marcelo I.; Gonçalves, João N. C.; Cortez, Paulo; Carvalho, Maria Sameiro; Fernandes, João M.Explainable Artificial Intelligence (XAI) methods are valuable tools for promoting understanding, trust, and efficient use of Artificial Intelligence (AI) systems in business organizations. However, the question of how organizations should select suitable XAI methods for a given task and business context remains a challenge, particularly when the number of methods available in the literature continues to increa...
PrivateCTGAN: adapting GAN for privacy-aware tabular data sharing
Lopes, Frederico; Soares, Carlos; Cortez, PauloThis research addresses the challenge of generating synthetic data that resembles real-world data while preserving privacy. With privacy laws protecting sensitive information such as healthcare data, accessing sufficient training data becomes difficult, resulting in an increased difficulty in training Machine Learning models and in overall worst models. Recently, there has been an increased interest in the usag...
A data drift approach to update deployed energy prediction machine learning models
Teixeira, Hélder; Matta, Arthur; Pilastri, André; Ferreira, Luís; Pereira, Pedro José; Gonçalves, Carlos; Cortez, PauloWhile there is an increasing interest in Machine Learning (ML) based solutions, scarce research has been devoted to the deployment and monitoring of ML models. In this work, we address this research gap by proposing a new data drift ML update strategy that only considers changes in the input features. Using the realistic Growing Window (GW) and Rolling Window (RW) ML deployment simulation schemes, we propose tw...
Efeito de diferentes substratos na taxa de crescimento de Quercus suber L.
Gusmão, Andressa Griebler; Toloto, Matheus; Segatelli, Ana Beatriz; Fonseca, Felícia; Cortez, Paulo; Figueiredo, Tomás de; Hernández, ZulimarEm 2013, um incêndio em Picões (Trás-os-Montes, Portugal) destruiu mais de 2,57 km² de florestas de sobreiro (Quercus suber L.). A regeneração dessa espécie tornou-se um desafio devido à topografia (com declives superiores a 25%) e ao estado de degradação do solo, caracterizado pela erosão acelerada e pela perda de matéria orgânica. Para enfrentar esse desafio, o Projeto ForestWaterUp visa reflorestar 0,32 km² ...
A context-aware decision support system for selecting explainable artificial in...
Reis, Marcelo I.; Gonçalves, João N. C.; Cortez, Paulo; Carvalho, M. Sameiro; Fernandes, João M.Explainable Artificial Intelligence (XAI) methods are valuable tools for promoting understanding, trust, and efficient use of Artificial Intelligence (AI) systems in business organizations. However, the question of how organizations should select suitable XAI methods for a given task and business context remains a challenge, particularly when the number of methods available in the literature continues to increa...
Ahead of time prediction of decorated particleboard production disruptions and ...
Matta, Arthur; Matos, Luís Miguel; Pilastri, André; Silva, Jorge Miguel; Gomes, Miguel Bastos; Cortez, PauloThis paper proposes a Machine Learning (ML) approach to perform an Ahead-of-Time (AoT) prediction of decorated particleboard production disruptions and defects. We worked with a Portuguese company that is adopting the Industry 4.0 concept aiming to improve their decorated particleboard production planning (e.g., reducing production time and waste of materials). This company's business needs are addressed in ter...
Proactive prevention of work-related musculoskeletal disorders using a motion c...
Matos, Luís Miguel; Dias, Paula; Matta, Arthur; Machado, Dário; Sampaio, Rosane; Pilastri, André; Cortez, PauloIn this paper, we propose a proactive method to prevent Work-related MusculoSkeletal Disorders (WMSDs) in manufacturing industries. The integrated method includes a Motion Capture System (MCS) for data collection, a Time Series Forecasting (TSF) module using Machine Learning (ML) algorithms, a WMSD risk assessment module based on ergonomic standards, and a safety mechanism (e.g., alarm sound). We evaluated the ...
Towards a news recommendation system to increase reader engagement through news...
Fernandes, Elizabeth; Moro, Sergio; Cortez, PauloIn the big data era, recommendation systems (RS) play a pivotal role to overcome information overload. In the digital landscape publishers need to optimize their editorial strategies to increase reader engagement and digital revenue. Newsletters emerged as an important conversion channel to engage readers as they provide a personalized experience by building habits. However, the lack of human resources and the ...
Using machine learning to predict wine quality and prices: a demonstrative case...
Moreira, Diogo Oliveira; Reis, L. P.; Cortez, PauloThe wine industry is currently experiencing a worldwide growing interest, playing a substantial role in the economy of numerous countries. In this paper, we address the prediction of both wine quality and price, which is a valuable tool for several wine stakeholders, including producers, sellers and consumers. In particular, we explore a large worldwide tabular database that was retrieved from the Vivino platfo...