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541
An Enhanced Genetic Algorithm for Optimized Educational Assessment Test Generation Through Population Variation
Published 2025-04-01“…The most important aspect of a genetic algorithm (GA) lies in the optimal solution found. …”
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542
Urban flood hazard assessment using FLA-optimized boost algorithms in Ankara, Türkiye
Published 2025-03-01“…By applying advanced boosting algorithms—specifically, XGBoost, GradientBoost, and CatBoost—along with hyperparameter optimization through the Fick’s law algorithm (FLA), this research introduces an innovative methodology aimed at improving the reliability and accuracy of flood hazard assessments in Ankara’s urban landscape. …”
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543
An Improved Large Neighborhood Search Algorithm for the Comprehensive Container Drayage Problem with Diverse Transport Requests
Published 2025-05-01“…Given the problem’s complexity, obtaining an exact solution for large instances is not feasible. Therefore, an improved large neighborhood search (LNS) algorithm is tailored by incorporating the “Sequential insertion” and the “Solution re-optimization” operations. …”
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544
A Fast Satellite Selection Algorithm Based on Hierarchical Clustering and Iterative Subset Optimization
Published 2025-02-01Get full text
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545
Flow direction algorithm for optimal coordination of directional overcurrent relays considering arc flash
Published 2025-03-01“…This paper presents a novel meta-heuristic optimization method called flow direction algorithm (FDA) to achieve optimal coordination of Directional Overcurrent Relays (DOCRs) while considering the impact of Arc Flash (AF). …”
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546
Bi-Level Game Strategy for Virtual Power Plants Based on an Improved Reinforcement Learning Algorithm
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547
Research on the optimization of optimal blasting parameters and fragmentation control based on coal seam geological conditions
Published 2025-04-01“…Abstract Open-pit coal mining often employs loosening blasting, with perforation blasting accounting for a significant portion of the coal seam mining costs. For coal of the same quality, the price of lump coal is much higher than that of crushed coal. …”
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548
Wideband distributed cooperative compressed spectrum sensing algorithm based on weighted consensus optimization
Published 2016-11-01“…Wideband distributed cooperative spectrum sensing based on compressed sensing can not only reduce high sampling rate,but also improve the spectrum sensing performance in low signal to noise ratio environment.In order to further enhance the spectrum sensing performance,a wideband distributed cooperative compressed spectrum sensing algorithm based on weighted consensus optimization was proposed.In this algorithm,the next iterative reconstruction weights were determined according to the current iterative reconstructed spectrum signal,which can encourage the sub-band occupied by primary user to generate signal value and decrease the likelihood of incorrect reconstruction.Simulation results show that the proposed algorithm can not only increases the spectral reconstruction accuracy,but also reduces time and communication costs of the sensing process,and improves the spectrum sensing performance.…”
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549
Wideband distributed cooperative compressed spectrum sensing algorithm based on weighted consensus optimization
Published 2016-11-01“…Wideband distributed cooperative spectrum sensing based on compressed sensing can not only reduce high sampling rate,but also improve the spectrum sensing performance in low signal to noise ratio environment.In order to further enhance the spectrum sensing performance,a wideband distributed cooperative compressed spectrum sensing algorithm based on weighted consensus optimization was proposed.In this algorithm,the next iterative reconstruction weights were determined according to the current iterative reconstructed spectrum signal,which can encourage the sub-band occupied by primary user to generate signal value and decrease the likelihood of incorrect reconstruction.Simulation results show that the proposed algorithm can not only increases the spectral reconstruction accuracy,but also reduces time and communication costs of the sensing process,and improves the spectrum sensing performance.…”
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550
Wind energy resource assessment based on joint wolf pack intelligent optimization algorithm.
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551
Load optimization of cogeneration units based on intuitive multi-objective fish swarm algorithm
Published 2025-06-01“…A cogeneration unit model incorporating operational characteristics and historical data demonstrates the method’s efficacy: multi-objective balance is maintained across iterations, achieving a 1.41% thermoelectric load increase and 1.54% optimal coal consumption reduction. The algorithm reduces heat/electricity losses and operational costs under diverse conditions while enhancing load utilization rates. …”
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552
Optimization of Combat Resource Allocation Based on Restricted Tournament Selection Social Genetic Algorithm
Published 2025-08-01“…In addition, we innovatively incorporate the concept of ‘group effect’ from sociology, adding a socialization operator to the algorithm to accelerate convergence and improve the quality of optimal solutions. …”
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553
A Lightweight Algorithm for Detection and Grading of Olive Ripeness Based on Improved YOLOv11n
Published 2025-04-01“…Olives are a crucial woody oil crop, the harvesting of which predominantly relies on manual labor, which is characterized by high costs, low efficiency, and challenges in ensuring optimal harvesting timing. …”
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554
Pricing principles in the field of ready–made meal delivery: analysis of influence factors
Published 2025-04-01“…The study describes the most popular pricing principles: cost–based, competitor–oriented, as well as dynamic algorithms taking into account seasonal demand. …”
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555
Image cluster algorithm of hybrid encoding method
Published 2017-02-01“…In the clustering analysis based on swarm intelligence optimization algorithm,the most of encoding method only used single form,and this method might be limit range of search space,the algorithm was easy to fall into local op-timum.In order to solve this problem,image clustering algorithm of hybrid encoding (HEICA) was proposed.Firstly,a hybrid encoding model based on image clustering was established,this method could expand the scope of the search space.Meanwhile,it was combined with two optimization algorithms which improved rain forest algorithm (IRFA) and quantum particle swarm optimization (QPSO),this method could improve the global search capability.In the simulation experiment,it was carried out to illustrate the performance of the proposed method based on four datasets.Compared with results form four measured cluster algorithm.The experimental results show that the algorithm has strong global search capability,high stability and clustering effect.…”
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556
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557
A quasi-opposition learning and chaos local search based on walrus optimization for global optimization problems
Published 2025-01-01“…The study aims to prevent premature convergence to local optima and enhance the diversity of the population by integrating the quasi-oppositional-based learning mechanism into the original Walrus Optimization (WO) algorithm, thereby improving the global search capability and expanding the search range. …”
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558
Dynamic Optimization of Xylitol Production Using Legendre-Based Control Parameterization
Published 2025-05-01“…This dimensionality reduction improves the robustness of the optimization by decreasing the likelihood of convergence to local optima while also reducing the computational cost and enhancing feasibility for implementation. …”
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559
Optimizing energy cost in the residential sector through home energy management systems in a smart grid environment
Published 2025-07-01“…The results show that GA achieved a 48% cost reduction compared to PSO, with significant peak load reduction and improved energy optimization when integrated with PV systems. …”
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560
Model Optimization for High-Yield Biocrude in Co-Hydrothermal Liquefaction of Municipal Sludge
Published 2025-04-01“…After training with the Levenberg-Marquardt algorithm, the model′s R2 significantly improved to 0.9989, demonstrating the superiority of neural networks in modeling nonlinear complex systems. …”
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