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4221
Deep Reinforcement Learning-Based Motion Control Optimization for Defect Detection System
Published 2025-04-01“…To address these challenges, this study proposes a deep reinforcement learning-based control scheme, leveraging DRL’s capabilities to optimize system performance. Specifically, the TD3 algorithm, featuring a dual-critic structure, is employed to enhance control precision within predefined state and action spaces. …”
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4222
Medium and short-term load forecasting based on NPMA-LSSVM algorithm in the case of unbalance and minority sample data
Published 2025-05-01“…Finally, the least square support vector machine (LSSVM) load forecasting model is established, and the improved mayfly algorithm with nonlinear inertia factor and polynomial variation is used to optimize the model parameters to achieve accurate load forecasts. …”
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4223
A Novel Hybrid Metaheuristic MPA-PSO to Optimize the Properties of Viscous Dampers
Published 2025-04-01“…Structural modeling and dynamic analyses are performed using OpenSees 3.5.0 software, and damper parameter optimization is performed through a new combination of two marine predator algorithms (MPA) and particle swarm optimization (PSO). …”
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4224
Towards few-shot learning with triplet metric learning and Kullback-Leibler optimization
Published 2025-06-01“…In training, the deep learning and expectation-maximization algorithm are used to optimize models. Intensive experiments have been conducted on three popular benchmark datasets, and the experimental results show that this method significantly improves the classification ability of few-shot learning tasks and obtains the most advanced performance.…”
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4225
Detection and Optimization of Photovoltaic Arrays’ Tilt Angles Using Remote Sensing Data
Published 2025-03-01“…The modules are grouped into arrays, and tilt angles are optimized using a Simulated Annealing (SA) algorithm, which maximizes simulated solar irradiance while accounting for shadowing, direct, and anisotropic diffuse irradiances. …”
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4226
Nanotechnology and LSTM machine learning algorithms in advanced fuel spray dynamics in CI engines with different bowl geometries
Published 2025-01-01“…Abstract This study explores the integration of nanotechnology and Long Short-Term Memory (LSTM) machine learning algorithms to enhance the understanding and optimization of fuel spray dynamics in compression ignition (CI) engines with varying bowl geometries. …”
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4227
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4228
Extraction of Optimal Measurements for Drowsy Driving Detection considering Driver Fingerprinting Differences
Published 2021-01-01“…Finally, we selected measurements calculated by IDBCPs that can distinguish drowsy driving to constitute individual drivers’ optimal drowsiness-detection measurement set. To verify the advantages of IDBCPs, the measurements calculated by UCPs and IDBCPs were, respectively, used to build driver-specific drowsiness-detection models: DF_U and DF_I based on the Fisher discriminant algorithm. …”
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4229
Grid structure optimization using slow coherency theory and holomorphic embedding method
Published 2025-03-01“…Simulation results show that the proposed optimization method effectively improves the synchrony clustering performance and voltage stability of the test systems, offering faster optimization speed and better results compared to other classical algorithms.…”
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4230
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4231
Improving Daily Precipitation Estimates by Merging Satellite and Reanalysis Data in Northeast China
Published 2024-12-01Get full text
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4232
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4233
StomachNet: Optimal Deep Learning Features Fusion for Stomach Abnormalities Classification
Published 2020-01-01“…These algorithms are implemented in parallel to obtain optimal feature vectors. …”
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4234
A Linear Regression Prediction-Based Dynamic Multi-Objective Evolutionary Algorithm with Correlations of Pareto Front Points
Published 2025-06-01“…Specifically, when the DMOP environment changes, this paper first constructs a spatio-temporal correlation model between various key points of the PF based on the linear regression algorithm; then, based on the constructed model, predicts a new location for each key point in the new environment; subsequently, constructs a sub-population by introducing the Gaussian noise into the predicted location to improve the generalization ability; and then, utilizes the idea of NSGA-II-B to construct another sub-population to further improve the population diversity; finally, combining the previous two sub-populations, re-initializing a new population to adapt to the new environment through a random replacement strategy. …”
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4235
Fault diagnosis of ZDJ7 railway point machine based on improved DCNN and SVDD classification
Published 2023-08-01“…Aiming at the unbalanced features of the railway point machine sample, an improved quantity learning algorithm for hypersphere coordinate mapping based on SVDD is proposed. …”
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4236
Synergizing GIS and genetic algorithms to enhance road management and fund allocation with a comprehensive case study approach
Published 2025-02-01“…This innovative approach combines a Geographic Information System (GIS)-based road management model with a fund allocation prioritization strategy, enhanced by an optimization engine via a genetic algorithm. …”
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4237
Committee Machine Learning for Electrofacies-Guided Well Placement and Oil Recovery Optimization
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4238
Artificial Bee Colony Algorithm Based on the Division Between Exploration and Exploitation and Its Application in Esophageal Cancer Prediction
Published 2025-07-01“…Simultaneously, a search equation is formulated for scout bees that incorporates both search experience and diversified optimal solution information. The proposed algorithm is compared to six other ABC algorithms across 80 benchmark functions, with its superiority evaluated in terms of solution quality, non-parametric tests, convergence speed, and time efficiency. …”
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4239
BSDR: A Data-Efficient Deep Learning-Based Hyperspectral Band Selection Algorithm Using Discrete Relaxation
Published 2024-12-01“…Hyperspectral band selection algorithms are crucial for processing high-dimensional data, which enables dimensionality reduction, improves data analysis, and enhances computational efficiency. …”
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4240
Personalized Human Thermal Sensation Prediction Based on Bayesian-Optimized Random Forest
Published 2025-07-01“…Finally, the best-performing model was further optimized using Bayesian methods to enhance hyperparameter tuning efficiency and improve the accuracy of personalized human thermal sensation prediction.…”
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