Multi-step Ultraviolet Index Forecasting Using Long Short-Term Memory Networks. - Pedro Oliveira 005; Bruno Fernandes 002; Cesar Analide; Paulo Novais (DCAI, 2020)

A Deep Learning Approach to Forecast the Influent Flow in Wastewater Treatment Plants. - Pedro Oliveira 005; Bruno Fernandes 002; Francisco Aguiar; Maria Alcina Pereira; Cesar Analide; Paulo Novais (IDEAL (1), 2020)

A Tree-Based Approach to Forecast the Total Nitrogen in Wastewater Treatment Plants. - Carlos Faria; Pedro Oliveira 005; Bruno Fernandes 002; Francisco Aguiar; Maria Alcina Pereira; Paulo Novais (DCAI (1), 2021)

Unsupervised Learning Approach for pH Anomaly Detection in Wastewater Treatment Plants. - Diogo Gigante; Pedro Oliveira 005; Bruno Fernandes 002; Frederico Lopes; Paulo Novais (HAIS, 2021)

Using Machine Learning to Forecast Air and Water Quality. - Carolina Silva; Bruno Fernandes 002; Pedro Oliveira 005; Paulo Novais (ICAART (2), 2021)

Evaluating Unidimensional Convolutional Neural Networks to Forecast the Influent pH of Wastewater Treatment Plants. - Pedro Oliveira 005; Bruno Fernandes 002; Francisco Aguiar; Maria Alcina Pereira; Paulo Novais (IDEAL, 2021)

Cost-Sensitive Learning and Threshold-Moving Approach to Improve Industrial Lots Release Process on Imbalanced Datasets. - Armindo Lobo; Pedro Oliveira 005; Paulo Sampaio; Paulo Novais (DCAI (1), 2022)

Applying Anomaly Detection Models in Wastewater Management: A Case Study of Nitrates Concentration in the Effluent. - Pedro Oliveira 005; M. Salomé Duarte; Paulo Novais (IBERAMIA, 2022)

A Self-Organizing Map Clustering Approach to Support Territorial Zoning. - Marcos Aurélio Santos da Silva; Pedro V. de A. Barreto; Leonardo N. Matos; Gastão Florêncio Miranda Jr.; Márcia H. G. Dompieri; Fábio R. de Moura; Fabrícia K. S. Resende; Paulo Novais; Pedro Oliveira 005 (CIARP, 2023)

Image Classification Understanding with Model Inspector Tool. - Flávio Arthur O. Santos; Maynara Donato de Souza; Pedro Oliveira 005; Leonardo Nogueira Matos; Paulo Novais; Cleber Zanchettin (HAIS, 2023)

Using Deep Learning Models to Predict the Electrical Conductivity of the Influent in a Wastewater Treatment Plant. - João Pereira; Pedro Oliveira 005; M. Salomé Duarte; Gilberto Martins; Paulo Novais (IDEAL, 2023)

A Framework for Representing, Building and Reusing Novel State-of-the-Art Three-Dimensional Object Detection Models in Point Clouds Targeting Self-Driving Applications. - António Linhares Silva 004; Pedro Oliveira 005; Dalila Durães; Duarte Fernandes; Rafael Névoa; João Monteiro 001; Pedro Melo-Pinto; José Machado 001; Paulo Novais (Sensors, 2023)

Geothermal Heat Exchanger's Temperature Input Sensor Prediction Based on Deep Learning Modelling Technique. - Pedro Oliveira 005; Paula Arcano-Bea; Francisco Supino Marcondes; José Luís Calvo-Rolle; Paulo Novais; Esteban Jove (DCAI (4), 2024)

Efficiency of the Transformer Model in Time Series Forecasting: A Case Study in Wastewater Treatment Plants. - Gonçalo Medeiros; Francisco Supino Marcondes; Pedro Oliveira 005; José Machado 001; Paulo Novais (IBERAMIA, 2024)

Employing Explainable AI Techniques for Air Pollution: An Ante-Hoc and Post-Hoc Approach in Dioxide Nitrogen Forecasting. - Pedro Oliveira 005; Francisco Franco; Afonso Bessa; Dalila Durães; Paulo Novais (IDEAL (1), 2024)

A Deep Learning-Based Model to Predict Nitrogen Dioxide in Urban Environments. - Pedro Oliveira 005; Antonio Díaz-Longueira; Francisco Supino Marcondes; Dalila Durães; José Luís Calvo-Rolle; Esteban Jove; Paulo Novais (ISAmI, 2024)

Assessment of LSTM and GRU Models to Predict the Electricity Production from Biogas in a Wastewater Treatment Plant. - Pedro Oliveira 005; Francisco Supino Marcondes; M. Salomé Duarte; Dalila Durães; Gilberto Martins; Paulo Novais (WorldCIST (2), 2024)

Conception and evaluation of anomaly detection models for monitoring analytical parameters in wastewater treatment plants. - Pedro Oliveira 005; M. Salomé Duarte; Paulo Novais (AI Commun., 2024)