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1921
Incorporating echo state network and sand cat swarm optimization algorithm based on quantum for named entity recognition
Published 2025-05-01“…The main contribution of this study is the combination of QSCSO with ESN, which improves the model’s capacity to comprehend long-term dependencies and effectively optimize hyperparameters. …”
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1922
Enhanced Prediction and Evaluation of Hydraulic Concrete Compressive Strength Using Multiple Soft Computing and Metaheuristic Optimization Algorithms
Published 2024-10-01“…In the initial stage, several classic machine learning models are selected as base models, and the optimal parameters of these models are obtained using the improved metaheuristic-based gray wolf algorithm. …”
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1923
Fast-Charging Optimization Method for Lithium-Ion Battery Packs Based on Deep Deterministic Policy Gradient Algorithm
Published 2025-05-01“…The model employs the deep deterministic policy gradient (DDPG) algorithm integrated with reward centralization and entropy regularization mechanisms, aiming to dynamically adjust the charging current to achieve an optimal balance between fast charging and battery health. …”
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1924
Multi-Population Optimization Framework Based on Plant Evolutionary Strategy and Its Application to Engineering Design Problems
Published 2025-05-01“…It outperforms other state-of-the-art optimization algorithms, demonstrating significant improvements in global optimization, solution accuracy, and convergence speed. …”
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1925
Optimal power scheduling in real-time distribution systems using crow search algorithm for enhanced microgrid performance
Published 2024-12-01“…The main contributions of this work include: (1) developing a new meta-heuristic approach for power scheduling in microgrids using the crow search algorithm, (2) achieving optimal power flow and load scheduling to minimize TOC and improve VR, and (3) successfully implementing the proposed methodology in a real-time distribution system using ETAP. …”
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1926
Optimization of Dynamic Vibration Absorber on Ambulance Stretchers Using the Genetic Algorithm Method Based on ISO 2631 Standards
Published 2025-02-01“…The optimization of parameters such as the distance between the stretcher’s center of gravity and the DVA, spring constants, damping coefficients, and mass is carried out using a genetic algorithm (GA). …”
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1927
S-EPSO: A Socio-Emotional Particle Swarm Optimization Algorithm for Multimodal Search in Low-Dimensional Engineering Applications
Published 2025-06-01“…S-EPSO performed best with the most challenging 5D functions of the benchmark. These results clearly illustrate the potential of S-EPSO when it comes to dealing with practical engineering optimization problems limited to five dimensions.…”
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1928
An Efficient Multisensor Hybrid Data Fusion Approach Based on Artificial Neural Networks and Particle Swarm Optimization Algorithms
Published 2024-01-01“…The preprocessing stage of data is also included in the suggested technique, which starts with the design of the data-collecting device and ends with a hybrid model algorithm. Particle swarm optimization and artificial neural network methods are combined in the hybrid algorithm. …”
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1929
Optimal Design Method of a Hybrid CSP-PV Plant Based on Genetic Algorithm Considering the Operation Strategy
Published 2018-01-01“…In this paper, the operation strategy of the CSP-PV system is proposed for parabolic trough CSP system and PV system which are now commercially operated. Genetic algorithm is used to optimize the design of the system and calculate PV-installed capacity, battery capacity, and storage capacity of CSP system, making the system to achieve the lowest cost of electricity generation. …”
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1930
Study on PID gain parameter optimization for a quadcopter under static wind turbulence using bio-inspired algorithms
Published 2025-02-01“…This study solves this problem using Bio-inspired algorithms to tune the controller gain. To determine the required PID controller gain parameters this paper utilizes a Simulink model of a quadcopter combined with the particle swarm optimization (PSO) algorithm and the cuckoo search algorithm (CSA) optimization respectively to minimize error in the attitude rate. …”
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1931
Advanced KNN-based cost-efficient algorithm for precision localization and energy optimization in dynamic underwater sensor networks
Published 2025-01-01“…Results demonstrate notable improvements in localization accuracy by optimizing the localization error rate from 4.59m to $$3.88 \times 10^{-8}$$ m, Reducing localization energy consumption rate 0.0045J in addition for the first time we have also computed the localization Time cost rate which is 0.06762s. we assumed that in real-time and in NS-3 simulations on the Aqua-sim model indicate communication speed at 1500m/s. …”
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1932
Parametric-modeling-based multi-objective thermoelastic optimization of rudder structures
Published 2025-01-01“…By leveraging commercial software and established optimization algorithms, this method can be adapted to other thermoelastic optimization challenges through refinements such as parametric modeling and multi-objective optimization functions. …”
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1933
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1934
Research on Stacking Distribution of Steel Plates Input Based on Improved Multi-objective Particle Swarm Optimization
Published 2025-07-01“…Finally, the stacking situations before and after optimization were compared. Compared to the traditional stacking method used before optimization, the optimized stacking distribution scheme improved by 19.35%, 4.97%, and 62.23% under the three objectives, respectively, indicating a more significant optimization effect.ConclusionsBased on the actual demand of enterprises for optimizing automatic steel plate warehouse loading decisions, the PCDMOPSO algorithm has demonstrated good performance in the simulation test of solving the stack allocation model. …”
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1935
A Genetic Algorithm Approach to Adaptive Learning: Enhancing Learner Satisfaction and Performance
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1936
A Study on the Design of a New Three-Dimensional Seismic Isolation Bearing Based on an Improved Genetic Algorithm for Bridge Engineering
Published 2024-10-01“…However, passive seismic isolation devices, due to their non-adjustable performance parameters, struggle to achieve effective seismic isolation across a wide frequency range of 0 Hz to 20 Hz in response to random and varying seismic loads. (2) Methods: The sensitivity of the design parameters of the seismic isolation bearing was analyzed using the optimization center gradient method, and an improved genetic algorithm was employed to quickly optimize and obtain the optimal design parameters. (3) Results: The effectiveness of the three-dimensional seismic isolation bearing was validated through experiments. (4) Conclusions: The multi-factor sensitivity analysis approach used in this study for designing novel isolation bearings is applicable not only to seismic design in bridges but also serves as a reference for parameter design in isolation bearings requiring medium to high precision in seismic performance.…”
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1937
Integrating evolutionary algorithms and enhanced-YOLOv8 + for comprehensive apple ripeness prediction
Published 2025-03-01“…For structured text data, support vector regression (SVR) models optimized using the Whale Optimization Algorithm (WOA), Grey Wolf Optimizer (GWO), and Sparrow Search Algorithm (SSA) were utilized to predict apple ripeness, with the WOA-optimized SVR demonstrating exceptional generalization capabilities. …”
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1938
Fog node intrusion detection and response based on SVMIF and INSGA-II algorithm
Published 2025-12-01“…Additionally, modified particle swarm optimization was employed to optimize the model's parameters. …”
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1939
Optimizing Human-Centric Warehouse Operations: A Digital Twin Approach Using Dynamic Algorithms and AI/ML
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1940
Path planning in radioactive environment of nuclear facilities based on modified A-star algorithm and search neighborhood optimization
Published 2025-10-01“…Compared with the Probabilistic Roadmap Method (PRM), PRM has the shortest computation time due to its random sampling characteristics, but the cumulative dose and path length are higher than the two A-star algorithms. For models of varying complexity, optimizing the number of search neighborhoods further enhances search efficiency without affecting path planning results. …”
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