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Title: | Designing Robust Forecasting Ensembles of Data-Driven Models with a Multi-Objective Formulation: An Application to Home Energy Management Systems | Authors: | Ruano, Antonio Ruano, Maria da Graça |
Keywords: | multi-objective genetic algorithms; forecasting models; ensemble models; prediction intervals; robust models; probabilistic forecasting; home energy management systems | Issue Date: | 2023 | Publisher: | MDPI | Project: | Operational Program Portugal 2020 and Operational Program CRESC Algarve 2020, grant number 72581/2020 UID/EMS/50022/2020 UIDB/00326/2020 or project code UIDP/00326/2020 |
Serial title, monograph or event: | Inventions | Volume: | 8 | Issue: | 4 | Abstract: | This work proposes a procedure for the multi-objective design of a robust forecasting ensemble of data-driven models. Starting with a data-selection algorithm, a multi-objective genetic algorithm is then executed, performing topology and feature selection, as well as parameter estimation. From the set of non-dominated or preferential models, a smaller sub-set is chosen to form the ensemble. Prediction intervals for the ensemble are obtained using the covariance method. This procedure is illustrated in the design of four different models, required for energy management systems. Excellent results were obtained by this methodology, superseding the existing alternatives. Further research will incorporate a robustness criterion in MOGA, and will incorporate the prediction intervals in predictive control techniques. | URI: | https://hdl.handle.net/10316/112172 | ISSN: | 2411-5134 | DOI: | 10.3390/inventions8040096 | Rights: | openAccess |
Appears in Collections: | I&D CISUC - Artigos em Revistas Internacionais |
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Designing-Robust-Forecasting-Ensembles-of-DataDriven-Models-with-a-MultiObjective-Formulation-An-Application-to-Home-Energy-Management-SystemsInventions.pdf | 6.61 MB | Adobe PDF | View/Open |
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