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Enhancing CO2 emissions prediction for electric vehicles using Greylag Goose Optimization and machine learning
Published 2025-05-01“…Finally, the study does a comparative analysis with some established optimization algorithms in hyperparameter tuning regarding an improved accuracy model. …”
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3942
A Modified Pareto Ant Colony Optimization Approach to Solve Biobjective Weapon-Target Assignment Problem
Published 2017-01-01“…Simulation results show that the proposed algorithm is successfully applied in the field of WTA which improves the performance of the traditional P-ACO algorithm effectively and produces better solutions than the two well-known multiobjective optimization algorithms NSGA-II and SPEA-II.…”
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3943
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3944
Prediction of Treatment Recommendations Via Ensemble Machine Learning Algorithms for Non-Small Cell Lung Cancer Patients in Personalized Medicine
Published 2024-10-01“…Methods: To accomplish our research goal, we implement ensemble learning algorithms, bagging with regularized Cox regression models and nonparametric tree-based models via Random Survival Forests. …”
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3945
Weight optimization of steel lattice transmission towers based on Differential Evolution and machine learning classification technique
Published 2021-12-01“…A classification model based on the Adaptive Boosting algorithm is developed in order to eliminate unpromising candidates during the optimization process. …”
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3946
A quasi affine transformation evolution algorithm with evolution matrix selection operation for parameter estimation of proton exchange membrane fuel cells
Published 2025-01-01“…It is challenging to find the best PEMFC parameters because the model is complex and the problem is nonlinear; not all optimization algorithms can solve this problem. …”
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3947
Optimal Configuration of Additional Heat Source for CHP System considering Demand Response Based on Comprehensive Benefits
Published 2024-01-01“…Furthermore, an improved memetic algorithm (IMA) combined with a hierarchical sequence method is designed to solve the optimization model characterized by multiple objectives, hierarchical levels, and nonlinearity. …”
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3948
Optimization of Bayesian Neural Networks using hybrid PSO and fuzzy logic approach for time series forecasting
Published 2025-07-01“…The results show that using Bayesian Neural Networks improves structural models and minimizes operational errors. …”
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3949
Control Optimization of a Hybrid Magnetic Suspension Blood Pump Controller Based on the Finite Element Method
Published 2025-06-01“…The results demonstrate that the improved PSO algorithm offers significant advantages over both the BP neural network and traditional manual PID tuning. …”
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3950
Alignment Optimization of Elastically Supported Submarine Propulsion Shafting Based on Dynamic Bearing Load Influence Numbers
Published 2025-04-01“…Taking the equivalent displacements of the bearings as variables, the alignment optimization of the shafting was achieved by combining the genetic algorithm and the response surfaces. …”
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3951
A multi-objective aerodynamic performance optimization of a centrifugal vacuum pump and the flow physics analysis
Published 2025-04-01“…The numerical results reveal that compared with the baseline model, the two optimized models improve πtt by 1.009% and 1.863%, respectively, and the absolute magnitude of η by 1.206% and 1.019%, respectively. …”
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3952
An Optimized Spline-Based Registration of a 3D CT to a Set of C-Arm Images
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3953
Linear Active Disturbance Rejection Control System for the Travel Speed of an Electric Reel Sprinkling Irrigation Machine
Published 2024-09-01“…To enhance the robustness of the control system, it is necessary to investigate new disturbance rejection control algorithms and their effects. Therefore, a kinematic model of the reel sprinkling irrigation machine and a brushless DC (BLDC) motor model were established, and a linear active disturbance rejection control (LADRC) strategy based on improved particle swarm optimization (IPSO) was proposed. …”
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3954
Retinal imaging based glaucoma detection using modified pelican optimization based extreme learning machine
Published 2024-11-01“…The combined feature reduction techniques named as principal component analysis and linear discriminant analysis, have been applied to generate prominent features and decrease the feature vector dimension. Lastly, a newly improved learning algorithm encompasses a modified pelican optimization algorithm (MOD-POA) and an extreme learning machine (ELM) for classification tasks. …”
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3955
Multi-objective optimization of 200 kW air centripetal turbine based on artificial neural networks
Published 2025-06-01“…Then, after optimizing the artificial neural network model with a genetic algorithm, the total -total efficiency of the air centrifugal turbine was improved by 1.479 %, while the axial thrust was reduced by 1.07 %.…”
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3956
Key Role and Optimization Dispatch Research of Technical Virtual Power Plants in the New Energy Era
Published 2024-11-01“…For each method, this review presents its mathematical models and solution algorithms. This review highlights the significance of TVPPs in enhancing power system flexibility, improving renewable energy integration, and providing ancillary services. …”
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3957
Optimal location and size of electric vehicle charging and discharging stations in distribution networks with integrated distributed generations
Published 2025-03-01“…In this study, we propose a computational model to determine the optimal location and size of EVCS applying V2G technique in a distribution network integrating distributed generation sources (DG) with the goal of minimizing active power loss, using an improved method combining the firefly algorithm with the quantum-inspired evolutionary algorithm (QBFA) to find solutions for the problem. …”
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3958
Optimal location and size of electric vehicle charging and discharging stations in distribution networks with integrated distributed generations
Published 2025-03-01“…In this study, we propose a computational model to determine the optimal location and size of EVCS applying V2G technique in a distribution network integrating distributed generation sources (DG) with the goal of minimizing active power loss, using an improved method combining the firefly algorithm with the quantum-inspired evolutionary algorithm (QBFA) to find solutions for the problem. …”
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