20 citations · 47 across the 7 of their papers we have counts for
7 papers
An Adaptive Hydropower Management Approach for Downstream Ecosystem Preservation
C. Coelho, M. Jing, M. Fernanda P. Costa +1
Hydropower plants play a pivotal role in advancing clean and sustainable energy production, contributing significantly to the global transition towards renewable energy sources. Ho…
A Two-Stage Training Method for Modeling Constrained Systems With Neural Networks
C. Coelho, M. Fernanda P. Costa, L. L. Ferrás
Real-world systems are often formulated as constrained optimization problems. Techniques to incorporate constraints into Neural Networks (NN), such as Neural Ordinary Differential…
Neural Fractional Differential Equations
C. Coelho, M. Fernanda P. Costa, L. L. Ferrás
Fractional Differential Equations (FDEs) are essential tools for modelling complex systems in science and engineering. They extend the traditional concepts of differentiation and i…
The Influence of Neural Networks on Hydropower Plant Management in Agriculture: Addressing Challenges and Exploring Untapped Opportunities
C. Coelho, M. Fernanda P. Costa, L. L. Ferrás
Hydropower plants are crucial for stable renewable energy and serve as vital water sources for sustainable agriculture. However, it is essential to assess the current water managem…
Enhancing Continuous Time Series Modelling with a Latent ODE-LSTM Approach
C. Coelho, M. Fernanda P. Costa, L. L. Ferrás
Due to their dynamic properties such as irregular sampling rate and high-frequency sampling, Continuous Time Series (CTS) are found in many applications. Since CTS with irregular s…
Neural Chronos ODE: Unveiling Temporal Patterns and Forecasting Future and Past Trends in Time Series Data
C. Coelho, M. Fernanda P. Costa, L. L. Ferrás
This work introduces Neural Chronos Ordinary Differential Equations (Neural CODE), a deep neural network architecture that fits a continuous-time ODE dynamics for predicting the ch…
A Self-Adaptive Penalty Method for Integrating Prior Knowledge Constraints into Neural ODEs
C. Coelho, M. Fernanda P. Costa, L. L. Ferrás
The continuous dynamics of natural systems has been effectively modelled using Neural Ordinary Differential Equations (Neural ODEs). However, for accurate and meaningful prediction…