Application of Meta-Heuristic Algorithms for Training Neural Networks and Deep Learning Architectures: A Comprehensive Review

Neural Processing Letters, Год журнала: 2022, Номер 55(4), С. 4519 - 4622

Опубликована: Окт. 31, 2022

Язык: Английский

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Short-term multi-step wind power forecasting based on spatio-temporal correlations and transformer neural networks

Energy Conversion and Management, Год журнала: 2023, Номер 283, С. 116916 - 116916

Опубликована: Март 16, 2023

Язык: Английский

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Ultra-short-term forecasting of wind power based on multi-task learning and LSTM

International Journal of Electrical Power & Energy Systems, Год журнала: 2023, Номер 149, С. 109073 - 109073

Опубликована: Март 5, 2023

Язык: Английский

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A novel DWTimesNet-based short-term multi-step wind power forecasting model using feature selection and auto-tuning methods

Energy Conversion and Management, Год журнала: 2024, Номер 301, С. 118045 - 118045

Опубликована: Янв. 5, 2024

Язык: Английский

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An ensemble method for short-term wind power prediction considering error correction strategy

Applied Energy, Год журнала: 2022, Номер 322, С. 119475 - 119475

Опубликована: Июнь 22, 2022

Язык: Английский

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A Novel IoT-Enabled Healthcare Monitoring Framework and Improved Grey Wolf Optimization Algorithm-Based Deep Convolution Neural Network Model for Early Diagnosis of Lung Cancer

Sensors, Год журнала: 2023, Номер 23(6), С. 2932 - 2932

Опубликована: Март 8, 2023

Lung cancer is a high-risk disease that causes mortality worldwide; nevertheless, lung nodules are the main manifestation can help to diagnose at an early stage, lowering workload of radiologists and boosting rate diagnosis. Artificial intelligence-based neural networks promising technologies for automatically detecting employing patient monitoring data acquired from sensor technology through Internet-of-Things (IoT)-based system. However, standard rely on manually features, which reduces effectiveness detection. In this paper, we provide novel IoT-enabled healthcare platform improved grey-wolf optimization (IGWO)-based deep convulution network (DCNN) model The Tasmanian Devil Optimization (TDO) algorithm utilized select most pertinent features diagnosing nodules, convergence grey wolf (GWO) modified, resulting in GWO algorithm. Consequently, IGWO-based DCNN trained optimal obtained IoT platform, findings saved cloud doctor's judgment. built Android with DCNN-enabled Python libraries, evaluated against cutting-edge detection models.

Язык: Английский

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Wind power forecasting: A hybrid forecasting model and multi-task learning-based framework

Energy, Год журнала: 2023, Номер 278, С. 127864 - 127864

Опубликована: Май 19, 2023

Язык: Английский

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Short-term wind power prediction based on modal reconstruction and CNN-BiLSTM

Energy Reports, Год журнала: 2023, Номер 9, С. 6449 - 6460

Опубликована: Июнь 16, 2023

Accurate prediction of short-term wind power plays an important role in the safe operation and economic dispatch grid. In response to current single algorithm that cannot further improve accuracy, this study proposes a combined model based on data processing, signal decomposition, deep learning. First, outliers original can affect accuracy. This detects by Z-score method fills them with cubic spline interpolation ensure integrity data. Second, for volatility power, time series is decomposed using complete ensemble empirical modal decomposition adaptive noise (CEEMDAN). The component complexity calculated sample entropy (SE), components are reconstructed according SE size Finally, traditional convolutional neural network (CNN) structure improved bi-directional long memory (BiLSTM) used extract feature links between superimpose results each obtain final value. experimental demonstrate hybrid proposed has better performance terms performance.

Язык: Английский

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The ultra-short-term wind power point-interval forecasting model based on improved variational mode decomposition and bidirectional gated recurrent unit improved by improved sparrow search algorithm and attention mechanism

Energy, Год журнала: 2023, Номер 288, С. 129714 - 129714

Опубликована: Ноя. 20, 2023

Язык: Английский

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RDERL: Reliable deep ensemble reinforcement learning-based recommender system

Knowledge-Based Systems, Год журнала: 2023, Номер 263, С. 110289 - 110289

Опубликована: Янв. 11, 2023

Язык: Английский

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