2023
Authors
Jozi, A; Pinto, T; Gomes, L; Marreiros, G; Vale, Z;
Publication
Progress in Artificial Intelligence - 22nd EPIA Conference on Artificial Intelligence, EPIA 2023, Faial Island, Azores, September 5-8, 2023, Proceedings, Part II
Abstract
2023
Authors
Teixeira, B; Faia, R; Pinto, T; Vale, Z;
Publication
Distributed Computing and Artificial Intelligence, Special Sessions I, 20th International Conference, Guimaraes, Portugal, 12-14 July 2023.
Abstract
2023
Authors
Carvalho, J; Pinto, T; Home Ortiz, JM; Teixeira, B; Vale, Z; Romero, R;
Publication
Distributed Computing and Artificial Intelligence, Special Sessions I, 20th International Conference, Guimaraes, Portugal, 12-14 July 2023.
Abstract
2023
Authors
Mehmood, R; Alves, V; Praça, I; Wikarek, J; Domínguez, JP; Loukanova, R; Miguel, Id; Pinto, T; Nunes, R; Ricca, M;
Publication
DCAI (2)
Abstract
2023
Authors
Santos, G; Pinto, T; Ramos, C; Corchado, JM;
Publication
FRONTIERS IN ENERGY RESEARCH
Abstract
[No abstract available]
2023
Authors
Teixeira, B; Carvalhais, L; Pinto, T; Vale, Z;
Publication
2023 IEEE CONFERENCE ON ARTIFICIAL INTELLIGENCE, CAI
Abstract
The structural changes in the energy sector caused by renewable sources and digitization have resulted in an increased use of Artificial Intelligence (AI), including Machine Learning (ML) models. However, these models' black-box nature and complexity can create issues with transparency and trust, thereby hindering their interpretability. The use of Explainable AI (XAI) can offer a solution to these challenges. This paper explores the application of an XAI-based framework to analyze and evaluate a photovoltaic energy generation forecasting problem and contribute to the trustworthiness of ML solutions.
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