EVNN-GRFN integrated with BFGS-ARMA for rainfall prediction in Bangladesh

Earth Science Informatics, Год журнала: 2025, Номер 18(2)

Опубликована: Фев. 1, 2025

Язык: Английский

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A Wind Speed Prediction Method Based on Signal Decomposition Technology Deep Learning Model

Energies, Год журнала: 2025, Номер 18(5), С. 1136 - 1136

Опубликована: Фев. 25, 2025

Accurate and reliable wind speed prediction plays a significant role in ensuring the reasonable scheduling of power resources. However, sequences often exhibit complex characteristics such as instability volatility, which create substantial challenges for prediction. In order to cope with these challenges, multi-step method based on secondary decomposition (SD) techniques deep learning models is proposed this paper. First, original signal was decomposed into multiple by using two techniques, multi-scale wavelet spectrum analysis (MWPSA) variational mode (VMD). Second, model constructed combining convolutional neural networks (CNNs), bidirectional long short-term memory (BiLSTM) networks, attention mechanism perform predicting each sequence, parameters were optimized particle swarm optimization (PSO) algorithm. Ultimately, results from all combined generate final The predictive performance evaluated real data collected farm China. Experimental show that significantly outperforms other comparison prediction, highlights its accuracy reliability.

Язык: Английский

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Change point-driven interrupted time series and machine learning models for forecasting indian food grain production

Discover Food, Год журнала: 2025, Номер 5(1)

Опубликована: Март 20, 2025

Язык: Английский

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Hybrid modelling of ruble exchange rates amidst the Russo-Ukrainian conflict using swarm and fuzzy neural networks

Engineering Applications of Artificial Intelligence, Год журнала: 2025, Номер 153, С. 110854 - 110854

Опубликована: Апрель 26, 2025

Язык: Английский

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