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141
Morphological Estimation of Primary Branch Inclination Angles in Jujube Trees Based on Improved PointNet++
Published 2025-05-01“…This study presents a primary branch IA estimation algorithm for jujube trees based on an improved PointNet++ network. …”
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142
A Novel Method of Self-Healing Concrete to Improve Durability and Extend the Service Life of Civil Infrastructure
Published 2023-01-01“…Moreover, a concrete durability prediction model based on particle swarm optimization-least squares support vector machine (PSO-LSSVM) and improved NSGA-II (nondominated sorting genetic algorithm II) algorithm was proposed to quickly and accurately determine the optimization scheme of self-healing concrete mix proportion. …”
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143
Dynamic response force control of electrohydraulic servo actuator of active suspension based on intelligent optimization algorithm.
Published 2025-01-01“…To address these challenges, a fractional-order PID (FOPID) controller optimization method based on the Multi-Strategy Improved Beluga Whale Optimization (MSIBWO) algorithm is proposed. …”
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144
First-principle modeling of parallel-flow regenerative kilns and their optimization with genetic algorithm and gradient-based method
Published 2024-12-01“…Finally, we use a genetic algorithm to optimize the feed mass flows such that the conversion and the fuel efficiency are improved in a Pareto-optimal manner. …”
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145
Optimization model of electricity metering management based on MOPSO
Published 2025-06-01“…Abstract In response to the difficulty of balancing economy and accuracy in traditional energy metering management methods, an improved particle swarm optimization model is designed to optimize energy metering management based on multi-objective particle swarm optimization, thereby achieving optimal resource allocation and maximizing management efficiency. …”
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146
Comparative Performance of Autoencoders and Traditional Machine Learning Algorithms in Clinical Data Analysis for Predicting Post-Staged GKRS Tumor Dynamics
Published 2024-09-01“…<b>Objectives:</b> The primary objective of this study is to assess whether integrating autoencoder-derived features into traditional ML models can improve their performance in predicting tumor dynamics three months post-GKRS in patients with brain metastases. …”
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147
An Intelligent 5G Unmanned Aerial Vehicle Path Optimization Algorithm for Offshore Wind Farm Inspection
Published 2025-01-01Get full text
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148
A Novel Black Widow Optimization Algorithm Based on Lagrange Interpolation Operator for ResNet18
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149
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150
Machine learning-based coalbed methane well production prediction and fracturing parameter optimization
Published 2025-04-01“…The model employs a random forest algorithm integrated with a multi-task learning strategy and utilizes a particle swarm optimization (PSO) algorithm to optimize fracturing parameters. …”
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151
Spatial–degree of freedom improvement of interference alignment in multi-input, multi-output interference channels
Published 2017-01-01“…As we know, the degree of freedom approximates the capacity of a network. To improve the achievable degree of freedom in the K -user interference network, we propose a rank minimization interference minimization algorithm. …”
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152
An adaptive hybrid framework for IIoT intrusion detection using neural networks and feature optimization using genetic algorithms
Published 2025-05-01“…Additionally, Genetic Algorithms were employed to optimize feature selection, further refining the ANN’s input space to improve computational efficiency without sacrificing predictive power. …”
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153
Parameter Extraction of Photovoltaic Cells and Panels Using a PID-Based Metaheuristic Algorithm
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154
A Data Resource Trading Price Prediction Method Based on Improved LightGBM Ensemble Model
Published 2025-01-01“…To address the key challenges of limited practical application, high implementation difficulty, and poor generalization capability in existing theoretical models for data resource pricing, this study employs generative adversarial network (GAN) to augment the dataset and constructs a DRV-LightGBM model based on a Bayesian parameter optimization algorithm that maximizes the coefficient of determination (<inline-formula> <tex-math notation="LaTeX">$R^{2}$ </tex-math></inline-formula>) to predict data resource transaction prices and provide post-hoc explanations for the prediction model. …”
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155
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156
Focused Crawler for Event Detection Using Metaheuristic Algorithms and Knowledge Extraction
Published 2023-07-01“…By integrating this method with machine learning algorithms, the proposed technique exhibits improvements in experiments, including decreased execution time and enhancements in metrics such as Root Mean Square Error (RMSE) and accuracy score. …”
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157
RELIABILITY OPTIMIZATION DESIGN ON SHEARER’S RANGING ARM GEAR TRANSMISSION SYSTEM
Published 2017-01-01“…In the process of design shearer ’s ranging arm gear transmission system,by using the method of reliability design theory,derived gear strength and stress assumed to obey normal distribution when tooth surface contact fatigue strength and tooth root bending fatigue strength were taken as constraint conditions,and the volume of gear system as objective function,then genetic algorithm optimization toolbox of MATLAB was used to solve the optimization mathematic model. …”
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158
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159
Algorithms and probabilistic models of parameters of operation of in-plant power supply
Published 2021-05-01“…To investigate the operability of low-voltage shop networks of radial, trunk and mixed structure in optimal operating conditions of the equipment when modeling the impact of external factors, such as the root-mean-square load factor of the equipment, the temperature of the shop room and the calculated time interval on the operating parameters of the system. …”
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160
DynaFusion-SLAM: Multi-Sensor Fusion and Dynamic Optimization of Autonomous Navigation Algorithms for Pasture-Pushing Robot
Published 2025-05-01“…The results indicate that when the RTAB-Map algorithm fuses with the multi-source odometry, its performance is significantly improved in the laboratory-simulated ranch scenario, the maximum absolute value of the error of the map measurement size is narrowed from 24.908 cm to 4.456 cm, the maximum absolute value of the relative error is reduced from 6.227% to 2.025%, and the absolute value of the error at each location is significantly reduced. …”
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