Pedro Oliveira

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University of Minho

Portugal

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About

Pedro Oliveira is a Professor at the University of Minho in Portugal. His research primarily focuses on applying deep learning techniques in environmental engineering, particularly pertaining to wastewater treatment and air pollution forecasting. Recent publications highlight topics such as hybrid architecture proposals for energy prediction and the efficiency of AI models in environmental monitoring.

Recent Grants

Grant: Close

Anomaly Detection Models to improve the Sustainability of Water Companies

Open Date: 2023-01-01

Close Date:

Grant: Close

Predictive and Analytic Models for the Optimization of Multi-municipal Water Systems

Open Date: 2020-04-01

Close Date: 2022-12-01

Articles (21)

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University of Minho

PORTUGAL

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Pedro Oliveira

Research Interests

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About

Recent Grants

Articles (21)

Incdualpathnet : a hybrid architecture proposal for predicting energy production in a wastewater treatment plants

Incdualpathnet : a hybrid architecture proposal for predicting energy production in a wastewater treatment plants

A Deep Learning-Based Model to Predict Nitrogen Dioxide in Urban Environments

Efficiency of the Transformer Model in Time Series Forecasting: A Case Study in Wastewater Treatment Plants

Employing Explainable AI Techniques for Air Pollution: An Ante-Hoc and Post-Hoc Approach in Dioxide Nitrogen Forecasting

Assessment of LSTM and GRU Models to Predict the Electricity Production from Biogas in a Wastewater Treatment Plant

Next-Generation Surveillance: Exploring the Intersection of Artificial Intelligence and Security

Conception and evaluation of anomaly detection models for monitoring analytical parameters in wastewater treatment plants

Geothermal Heat Exchanger's Temperature Input Sensor Prediction Based on Deep Learning Modelling Technique

A Review of Computational Modeling in Wastewater Treatment Processes

A Framework for Representing, Building and Reusing Novel State-of-the-Art Three-Dimensional Object Detection Models in Point Clouds Targeting Self-Driving Applications

Cost-Sensitive Learning and Threshold-Moving Approach to Improve Industrial Lots Release Process on Imbalanced Datasets

Conception and evaluation of anomaly detection models for monitoring analytical parameters in wastewater treatment plants

Image Classification Understanding with Model Inspector Tool

A Tree-Based Approach to Forecast the Total Nitrogen in Wastewater Treatment Plants

Applying Anomaly Detection Models in Wastewater Management: A Case Study of Nitrates Concentration in the Effluent

Forecasting Energy Consumption of Wastewater Treatment Plants with a Transfer Learning Approach for Sustainable Cities

Forecasting Energy Consumption of Wastewater Treatment Plants with a Transfer Learning Approach for Sustainable Cities

Evaluating Unidimensional Convolutional Neural Networks to Forecast the Influent pH of Wastewater Treatment Plants

Multi-step Ultraviolet Index Forecasting Using Long Short-Term Memory Networks

Unsupervised Learning Approach for pH Anomaly Detection in Wastewater Treatment Plants

Collaborators (7)

Pedro Melo-Pinto

Paulo Novais

Dalila Duraes

José Manuel Ferreira Machado

Cesar Analide

Eugénio C. Ferreira

Bruno Fernandes

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