Comparison of Inputs Correlation and Explainable Artificial Intelligence Recommendations for Neural Networks Forecasting Electricity Consumption - researchr publication related

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Daniel Ramos, Pedro Faria, Zita Vale. Comparison of Inputs Correlation and Explainable Artificial Intelligence Recommendations for Neural Networks Forecasting Electricity Consumption. In Bo Nørregaard Jørgensen, Luiz Carlos Pereira da Silva, Zheng Ma 0002, editors, Energy Informatics - Third Energy Informatics Academy Conference, EI.A 2023, Campinas, Brazil, December 6-8, 2023, Proceedings, Part II. Volume 14468 of Lecture Notes in Computer Science, pages 51-62, Springer, 2023. [doi]

The following publications are possibly variants of this publication:

Explainable Artificial Intelligence for Definition of Inputs in Neural Networks and K-nearest Neighbors Forecasting of Electricity ConsumptionDaniel Ramos, Pedro Faria, Zita Vale. isgteurope 2023: 1-5 [doi]

Electricity Price Forecast for Futures Contracts with Artificial Neural Network and Spearman Data CorrelationJoão Nascimento, Tiago Pinto, Zita A. Vale. dcai 2019: 12-20 [doi]

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