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2181
Adaptive drive-based integration technique for predicting rheological and mechanical properties of fresh gangue backfill slurry
Published 2025-07-01“…Analysis demonstrates that the particle swarm optimal (PSO) algorithm based on adaptive adjustment strategy can effectively optimize the hyperparameters of support vector regression (SVR), and the MC-PSO-SVR model exhibits better predictive capability (R2> 0.88) and lower error coefficients (MAE, RSE, and RMSE values approaching 0) and narrower widths of 95 % confidence intervals for yield stress, plastic viscosity, fluidity, and UCS. …”
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2182
Carbon emission prediction method for expressway construction period based on PSO-BP neural network
Published 2025-06-01“…To solve the problem of inaccurate carbon emissions prediction during the highway construction period, a method of optimizing the back propagation(BP) neural network by particle swarm optimization (PSO) algorithm was proposed to predict carbon emissions. …”
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2183
Machine Learning and Metaheuristics Approach for Individual Credit Risk Assessment: A Systematic Literature Review
Published 2025-05-01“…It categorizes the use of machine learning algorithms, feature selection methods, and metaheuristic optimization techniques, including genetic algorithms, particle swarm optimization, and biogeography-based optimization. …”
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2184
Enhancing Hajj and Umrah Services Through Predictive Social Media Classification
Published 2025-01-01“…To improve the effectiveness of this classification model, we introduce a predictive optimization strategy that employs a deep neural network as the learning module and utilizes particle swarm optimization to refine the weighting parameters. …”
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2185
Protection scheme of flexible MTDC transmission line based on ISSA-BiLSTM
Published 2025-04-01“…Based on wavelet transform technology, the characteristics of transmission line faults are extracted as model input to train the model; the original sparrow search algorithm is improved by using Sine chaotic mapping, learning particle swarm algorithm strategy, and introducing Gaussian disturbance term. …”
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2186
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2187
A Day-Ahead Economic Dispatch Method for Renewable Energy Systems Considering Flexibility Supply and Demand Balancing Capabilities
Published 2024-10-01“…This approach establishes a dual-layer optimized scheduling model. The upper-layer model focuses on the economic efficiency of unit start-up and shut-down, utilizing a particle swarm algorithm to identify unit combinations that comply with minimum start-up and shut-down time constraints. …”
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2188
Design and Analysis of a Hybrid MPPT Method for PV Systems Under Partial Shading Conditions
Published 2025-06-01“…In this study, a novel hybrid MPPT method based on Perturb & Observe and Particle Swarm Optimization that mainly aims to determine global operating point, is proposed. …”
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2189
Early Remaining Useful Life Prediction for Lithium-Ion Batteries Using a Gaussian Process Regression Model Based on Degradation Pattern Recognition
Published 2025-06-01“…The model hyperparameters are further optimized through the particle swarm optimization (PSO) algorithm to improve the adaptability and generalization capability of the predictive models. …”
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2190
Estimation and Reduction of CO₂ Emissions From Fossil Fuel Power Plants in Bangladesh
Published 2025-01-01“…The paper presents Matpower Interior Point Solver (MIPS), and Dynamic Non-Linear Particle Swarm Optimization (DNPSO) algorithms to solve combined economic emission dispatch (CEED) to optimize generation dispatch and minimize emissions. …”
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2191
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2192
Downhole Pressure Pulse Signal Recognition Based on SSA-CNN-LSTM
Published 2025-06-01“…It is found that the SSA-CNN-LSTM algorithm model outperforms traditional LSTM, CNN-LSTM, and PSO (particle swarm optimization) -CNN-LSTM models in terms of both fitting ability and prediction accuracy. …”
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2193
A photovoltaic power forecasting method based on the LSTM-XGBoost-EEDA-SO model
Published 2025-08-01“…Experimental results demonstrate that the proposed model significantly outperforms standalone benchmark methods. In comparison with Particle Swarm Optimization (PSO), Sparrow Search Algorithm (SSA), and the equal-weight assignment approach for high- and low-frequency component forecasting, the proposed SO algorithm attains the lowest forecasting errors. …”
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2194
Electric Vehicle Cluster and Scheduling Strategy Based on Dynamic Game
Published 2023-04-01“…The upper layer takes the peak shaving demand and peak shaving cost of distribution system operator (DSO) as the optimization objectives, and uses an improved multi-objective particle swarm optimization algorithm to obtain the game strategy set of DSO. …”
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2195
Analysis of Sub-Synchronous Oscillation in Grid-Connected Wind Farm and Proposed Improved Solution
Published 2025-01-01“…Therefore, this paper proposes optimizing the internal control parameters of the RSC using meta-heuristic algorithms, including Particle Swarm Optimization (PSO), Cuckoo Search Algorithm (CSA), and Ant Colony Optimization (ACO). …”
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2196
Advanced Machine Learning Methodology for Earthquake Magnitude Forecasting Using Comprehensive Seismic Data
Published 2026-01-01“…Feature selection was performed using Genetic Algorithm, Particle Swarm Optimization, and Simulated Annealing, while ten machine learning models were implemented — ranging from Linear Regression and Decision Trees to Gradient Boosting, XGBoost, LightGBM, and Long Short-Term Memory (LSTM) networks. …”
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2197
A Method for Service Function Chain Migration Based on Server Failure Prediction in Mobile Edge Computing Environment
Published 2025-01-01“…Using a Long Short-Term Memory (LSTM) algorithm optimized by Super SAPSO (Simulated Annealing Particle Swarm Optimization), the model forecasts server failures with improved accuracy, reducing False Alarm Rates and improving Failure Detection Rates. …”
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2198
Blasting vibration velocity prediction of open pit mines based on GRA-EPSO-SVM model
Published 2025-07-01“…Based on the coal and rock blasting in Yuanbaoshan open-pit coal mine under different occurrence conditions, hole spacing, row spacing, hole depth, maximum charge in single section, minimum resistance line, blast center spacing, elevation difference and peak particle vibration velocity were selected as input parameters, and grey correlation analysis (GRA) was used to filter redundant factors affecting peak blasting vibration velocity (hole depth, maximum charge of single section, minimum resistance line, peak particle velocity); using integrated particle swarm optimization algorithm (EPSO) to optimize the key parameters C and g of SVM algorithm, and inputting the parameters into GRA-EPSO-SVM model for evaluation. …”
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2199
A novel multi-task learning model based on Transformer-LSTM for wind power forecasting
Published 2025-08-01Get full text
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2200