Fuzzy-based weighting long short-term memory network for demand forecasting

One of the main challenges in short-term electrical load forecasting is extraction of nonlinear relationships and complex dependencies among different time instances of the load time series. To deal with this difficulty, a hybrid forecasting method is proposed in this paper that uses the fuzzy exper...

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Bibliographic Details
Published in:	The Journal of supercomputing Vol. 79; no. 1; pp. 435 - 460
Main Author:	Imani, Maryam
Format:	Journal Article
Language:	English
Published:	New York Springer US 01.01.2023 Springer Nature B.V
Subjects:	Artificial intelligence Compilers Computer Science Deep learning Electrical loads Expert systems Forecasting Genetic algorithms Interpreters Mathematics Methods Neural networks Power Processor Architectures Programming Languages Time series Wavelet transforms Fuzzy logic LSTM Load forecasting Weather conditions
ISSN:	0920-8542, 1573-0484
Online Access:	Get full text
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