| Using decision tree to select forecasting algorithms in distinct electricity consumption context of an office building D Ramos, P Faria, A Morais, Z Vale Energy Reports 8, 417-422, 2022 | 43 | 2022 |
| Industrial facility electricity consumption forecast using artificial neural networks and incremental learning D Ramos, P Faria, Z Vale, J Mourinho, R Correia Energies 13 (18), 4774, 2020 | 36 | 2020 |
| Load forecasting in an office building with different data structure and learning parameters D Ramos, M Khorram, P Faria, Z Vale Forecasting 3 (1), 242-255, 2021 | 31 | 2021 |
| Short time electricity consumption forecast in an industry facility D Ramos, P Faria, Z Vale, R Correia IEEE Transactions on Industry Applications 58 (1), 123-130, 2021 | 18 | 2021 |
| Use of sensors and analyzers data for load forecasting: A two stage approach D Ramos, B Teixeira, P Faria, L Gomes, O Abrishambaf, Z Vale Sensors 20 (12), 3524, 2020 | 14 | 2020 |
| Demonstration of an energy consumption forecasting system for energy management in buildings A Jozi, D Ramos, L Gomes, P Faria, T Pinto, Z Vale Progress in Artificial Intelligence: 19th EPIA Conference on Artificial …, 2019 | 14 | 2019 |
| A contextual reinforcement learning approach for electricity consumption forecasting in buildings D Ramos, P Faria, L Gomes, Z Vale IEEE Access 10, 61366-61374, 2022 | 12 | 2022 |
| Using diverse sensors in load forecasting in an office building to support energy management D Ramos, B Teixeira, P Faria, L Gomes, O Abrishambaf, Z Vale Energy Reports 6, 182-187, 2020 | 12 | 2020 |
| Green computing: a realistic evaluation of energy consumption for building load forecasting computation Z Vale, L Gomes, D Ramos, P Faria J Smart Environ Green Comput 2, 34-45, 2022 | 7 | 2022 |
| Selection of features in reinforcement learning applied to energy consumption forecast in buildings according to different contexts D Ramos, P Faria, L Gomes, P Campos, Z Vale Energy Reports 8, 423-429, 2022 | 6 | 2022 |
| Intelligent simulation and emulation platform for energy management in buildings and microgrids T Pinto, L Gomes, P Faria, Z Vale, N Teixeira, D Ramos Machine Learning for Smart Environments/Cities: An IoT Approach, 167-181, 2022 | 3 | 2022 |
| Electricity consumption forecast in an industry facility to support production planning update in short time D Ramos, P Faria, Z Vale, R Correia 2020 IEEE International Conference on Environment and Electrical Engineering …, 2020 | 3 | 2020 |
| A learning approach to improve the selection of forecasting algorithms in an office building in different contexts D Ramos, P Faria, L Gomes, P Campos, Z Vale EPIA Conference on Artificial Intelligence, 271-281, 2022 | 2 | 2022 |
| Energy forecast in buildings addressing computation consumption in a green computing approach D Ramos, P Faria, L Gomes, Z Vale 2022 IEEE International Conference on Environment and Electrical Engineering …, 2022 | 2 | 2022 |
| Computational approaches for green computing of energy consumption forecasting on non-working periods in an office building D Ramos, P Faria, L Gomes, Z Vale Energy Informatics Academy Conference, 83-91, 2023 | 1 | 2023 |
| CPU computation influence on energy consumption forecasting activities of a building D Ramos, P Faria, L Gomes, Z Vale International Workshop on Soft Computing Models in Industrial and …, 2022 | 1 | 2022 |
| Reinforcement Learning of a Multi Agent System for the Forecasting of Electricity Consumption DC do Vale Ramos | 1 | 2021 |
| Comparison of Inputs Correlation and Explainable Artificial Intelligence Recommendations for Neural Networks Forecasting Electricity Consumption D Ramos, P Faria, Z Vale Energy Informatics Academy Conference, 51-62, 2023 | | 2023 |
| Production Scheduling for Total Energy Cost and Machine Longevity Optimization Through a Genetic Algorithm B Mota, D Ramos, P Faria, C Ramos EPIA Conference on Artificial Intelligence, 182-194, 2023 | | 2023 |
| Building Energy Consumption Forecast under Different Anticipations on a Green Computation Perspective D Ramos, P Faria, L Gomes, Z Vale IFAC-PapersOnLine 56 (2), 10923-10928, 2023 | | 2023 |
Pedro FariaGECAD, Polytechnic of PortoVerified email at isep.ipp.pt
