Advances in Sparrow Search Algorithm: A Comprehensive Survey

Archives of Computational Methods in Engineering, Journal Year: 2022, Volume and Issue: 30(1), P. 427 - 455

Published: Aug. 22, 2022

Language: Английский

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Risk assessment of cardiovascular disease based on SOLSSA-CatBoost model

Expert Systems with Applications, Journal Year: 2023, Volume and Issue: 219, P. 119648 - 119648

Published: Feb. 3, 2023

Language: Английский

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A hybrid wind speed forecasting model with two-stage data processing based on adaptive neuro-fuzzy inference systems and deep learning algorithms

Earth Science Informatics, Journal Year: 2025, Volume and Issue: 18(1)

Published: Jan. 1, 2025

Language: Английский

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Artificial Neural Networks Hidden Unit and Weight Connection Optimization by Quasi-Refection-Based Learning Artificial Bee Colony Algorithm

IEEE Access, Journal Year: 2021, Volume and Issue: 9, P. 169135 - 169155

Published: Jan. 1, 2021

Artificial neural networks are one of the most commonly used methods in machine learning. Performance network highly depends on learning method. Traditional algorithms prone to be trapped local optima and have slow convergence. At other hand, nature-inspired optimization proven very efficient complex problems solving due derivative-free solutions. Addressing issues traditional algorithms, this study, an enhanced version artificial bee colony metaheuristics is proposed optimize connection weights hidden units networks. Proposed improved method incorporates quasi-reflection-based guided best solution bounded mechanisms original approach manages conquer its deficiencies. First, tested a recent challenging CEC 2017 benchmark function set, then applied for training five well-known medical datasets. Further, devised algorithm compared metaheuristics-based methods. The efficiency measured by metrics - accuracy, specificity, sensitivity, geometric mean, area under curve. Simulation results prove that outperforms terms accuracy convergence speed. improvement over different datasets between 0.03% 12.94%. quasi-refection-based mechanism significantly improves speed together with bounded, exploitation capability enhanced, which better accuracy.

Language: Английский

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A novel prediction model for wind power based on improved long short-term memory neural network

Energy, Journal Year: 2022, Volume and Issue: 265, P. 126283 - 126283

Published: Dec. 3, 2022

Language: Английский

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Quaternion convolutional long short-term memory neural model with an adaptive decomposition method for wind speed forecasting: North aegean islands case studies

Energy Conversion and Management, Journal Year: 2022, Volume and Issue: 259, P. 115590 - 115590

Published: April 11, 2022

Language: Английский

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Energy forecasting model based on CNN-LSTM-AE for many time series with unequal lengths

Engineering Applications of Artificial Intelligence, Journal Year: 2022, Volume and Issue: 113, P. 104998 - 104998

Published: June 2, 2022

Language: Английский

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A Wind Power Forecasting Model Using LSTM Optimized by the Modified Bald Eagle Search Algorithm

Energies, Journal Year: 2022, Volume and Issue: 15(6), P. 2031 - 2031

Published: March 10, 2022

High-precision forecasting of short-term wind power (WP) is integral for farms, the safe dispatch systems, and stable operation grid. Currently, data related to maintenance farms mainly comes from Supervisory Control Data Acquisition (SCADA) with certain information about operating characteristics turbines being readable in SCADA data. In WP forecasting, Long Short-Term Memory (LSTM) a commonly used in-depth learning method. present study, an optimized LSTM based on modified bald eagle search (MBES) algorithm was established construct MBES-LSTM model, model make predictions, so as address problem that selection hyperparameters may affect results. After preprocessing acquired by SCADA, forecast WP. The experimental results reveal that, compared PSO-RBF, PSO-SVM, LSTM, PSO-LSTM, BES-LSTM models, could effectively improve accuracy farms.

Language: Английский

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An improved temporal convolutional network with attention mechanism for photovoltaic generation forecasting

Engineering Applications of Artificial Intelligence, Journal Year: 2023, Volume and Issue: 123, P. 106273 - 106273

Published: April 17, 2023

Language: Английский

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A novel air quality index prediction model based on variational mode decomposition and SARIMA-GA-TCN

Process Safety and Environmental Protection, Journal Year: 2024, Volume and Issue: 184, P. 961 - 992

Published: Feb. 10, 2024

Language: Английский

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