Multivariate wind speed forecasting based on multi-objective feature selection approach and hybrid deep learning model

Energy, Journal Year: 2022, Volume and Issue: 263, P. 126100 - 126100

Published: Nov. 14, 2022

Language: Английский

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Two-stage distributionally robust optimization model of integrated energy system group considering energy sharing and carbon transfer

Applied Energy, Journal Year: 2022, Volume and Issue: 331, P. 120426 - 120426

Published: Dec. 9, 2022

Language: Английский

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Short-term wind power prediction based on two-layer decomposition and BiTCN-BiLSTM-attention model

Energy, Journal Year: 2023, Volume and Issue: 285, P. 128762 - 128762

Published: Aug. 14, 2023

Language: Английский

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Wind speed prediction by a swarm intelligence based deep learning model via signal decomposition and parameter optimization using improved chimp optimization algorithm

Energy, Journal Year: 2023, Volume and Issue: 276, P. 127526 - 127526

Published: April 14, 2023

Language: Английский

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A dual-optimization wind speed forecasting model based on deep learning and improved dung beetle optimization algorithm

Energy, Journal Year: 2023, Volume and Issue: 286, P. 129604 - 129604

Published: Nov. 7, 2023

Language: Английский

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Short-term photovoltaic power point-interval forecasting based on double-layer decomposition and WOA-BiLSTM-Attention and considering weather classification

Energy, Journal Year: 2023, Volume and Issue: 275, P. 127348 - 127348

Published: April 6, 2023

Language: Английский

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Short-term wind power forecasting based on multivariate/multi-step LSTM with temporal feature attention mechanism

Applied Soft Computing, Journal Year: 2023, Volume and Issue: 150, P. 111050 - 111050

Published: Nov. 14, 2023

Language: Английский

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A hybrid deep learning model based on parallel architecture TCN-LSTM with Savitzky-Golay filter for wind power prediction

Energy Conversion and Management, Journal Year: 2024, Volume and Issue: 302, P. 118122 - 118122

Published: Jan. 25, 2024

Language: Английский

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Advanced hybrid LSTM-transformer architecture for real-time multi-task prediction in engineering systems

Scientific Reports, Journal Year: 2024, Volume and Issue: 14(1)

Published: Feb. 28, 2024

In the field of engineering systems-particularly in underground drilling and green stormwater management-real-time predictions are vital for enhancing operational performance, ensuring safety, increasing efficiency. Addressing this niche, our study introduces a novel LSTM-transformer hybrid architecture, uniquely specialized multi-task real-time predictions. Building on advancements attention mechanisms sequence modeling, model integrates core strengths LSTM Transformer architectures, offering superior alternative to traditional predictive models. Further enriched with online learning, architecture dynamically adapts variable conditions continuously incorporates new data. Utilizing knowledge distillation techniques, we efficiently transfer insights from larger, pretrained networks, thereby achieving high accuracy without sacrificing computational resources. Rigorous experiments sector-specific datasets validate robustness effectiveness approach. Notably, exhibits clear advantages over existing methods terms accuracy, adaptability, This work contributes pioneering framework targeted applications, actionable into.

Language: Английский

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Ultra-short-term wind power probabilistic forecasting based on an evolutionary non-crossing multi-output quantile regression deep neural network

Energy Conversion and Management, Journal Year: 2024, Volume and Issue: 301, P. 118062 - 118062

Published: Jan. 13, 2024

Language: Английский

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