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Multi-objective data collecting strategies for wireless sensor network based on the time variable multi-salesman problem and genetic algorithm
Published 2017-03-01“…Comparing to the traditional data collecting method with data route,the technology of wireless mobile nodes has gradually became a new technique in the wireless sensor network.As the solution to the visiting order of the static nodes was an intrinsic NP-hard problem,a more general multi-objective data colleting strategies based on multi-mobile nodes was proposed.The proposed data collecting technique was abstracted as a model of time variable multiple traveling salesman problem.Belonging to a discrete optimal problem,the proposed model was solved by with a proposed hybrid genetic algorithm to determine the paths of the multi-mobile nodes.The convergence analysis of the proposed algorithm was given.With the experiment of open dataset,the proposed model based on the time variable multiple traveling salesman problem and the proposed hybrid genetic algorithm certify a certain improvement to the efficiency and real-time ability.…”
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2662
A Hybrid Deep Learning-ViT Model and A Meta-Heuristic Feature Selection Algorithm for Efficient Remote Sensing Image Classification
Published 2025-05-01“…In this study, we introduced XNANet, a self-attention-based CNN network for image classification. Bayesian optimization has been used to initialize the hyperparameters of the proposed model to improve training on the radiographic images. …”
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2664
Optimizing Berth Allocation for Maritime Autonomous Surface Ships (MASSs) in the Context of Mixed Operation Scenarios
Published 2025-02-01“…A large-scale simulation of the mixed-type berth allocation model is carried out using an improved simulated annealing algorithm. …”
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2665
Integration of multi agent reinforcement learning with golden jackal optimization for predicting average localization error in wireless sensor networks
Published 2025-07-01“…The GJO algorithm fine-tunes the hyperparameters of MARL to improve generalization across different WSN configurations. …”
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2667
Few-shot hotel industry site selection prediction method based on meta learning algorithms and transportation accessibility
Published 2025-05-01“…Abstract Exploring the rationality of hotel location selection is of significant importance for optimizing urban spatial structure and improving tourism service levels. …”
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2668
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2669
Designing an explainable bio-inspired model for suspended sediment load estimation: eXtreme Gradient Boosting coupled with Marine Predators Algorithm
Published 2024-12-01“…The superiority of the proposed model (XGB-MPA) compared to two other hybrid models, including XGB-PSO (Particle Swarm Optimization) and XGB-GWO (Grey Wolf Optimization) was also investigated. …”
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2670
UAV Path Planners in Complex Environments: A Multi-Dimensional Perturbation Based on Artificial Bee Colony
Published 2025-01-01“…In the onlooker bee phase, the curvature-guided elite neighbor search strategy is used to prioritizes high-curvature waypoints, enhancing optimization efficiency in complex terrain. Furthermore, path costs are independently modeled in the horizontal and vertical directions. …”
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2671
A Novel High-Precision Workpiece Self-Positioning Method for Improving the Convergence Ratio of Optical Components in Magnetorheological Finishing
Published 2025-06-01“…A composite data acquisition method using both a camera and probe is designed, and a stepwise global optimization model is constructed by integrating a synchronous iterative localization algorithm with the Non-dominated Sorting Genetic Algorithm II (NSGA-II). …”
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2672
Optimization of thermal conductivity in coir fibre-reinforced PVC composites using advanced computational techniques
Published 2025-05-01“…To address these challenges, the study uses Response Surface Methodology (RSM) and three nature-inspired optimization methods viz. Particle Swarm Optimization (PSO), Dragonfly Optimization (DFO) and Cuckoo Search Algorithm (CSA) to improve factors like fibre content, particle size and chemical treatment. …”
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2673
Influencing factors of cross screening rate and its intelligent prediction model
Published 2025-07-01“…Combined with particle swarm optimization (PSO), the hyper-parameter combination optimization of support vector machine, decision tree and random forest models is carried out to obtain the optimal parameter combination of the model and improve the prediction performance and generalization ability of the model. …”
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2674
Sparse support path generation for multi-axis curved layer fused filament fabrication
Published 2025-08-01“…Currently, most support generation algorithms are for the conventional 2.5D printing, which are not applicable to multi-axis printing. …”
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2675
SIDDA: SInkhorn Dynamic Domain Adaptation for image classification with equivariant neural networks
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On the machine learning algorithm combined evolutionary optimization to understand different tool designs’ wear mechanisms and other machinability metrics during dry turning of D2...
Published 2025-03-01“…In this study, three-step novel modelling approach for optimal prediction of dry turning parameters is proposed. …”
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Potential of random forest machine learning algorithm for geological mapping using PALSAR and Sentinel-2A remote sensing data: A case study of Tsagaan-uul area, southern Mongolia
Published 2025-12-01“…Geological mapping in remote and geologically complex regions can be substantially improved by integrating remote sensing data with machine learning algorithms. …”
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2679
Improving health-promoting workplaces through interdisciplinary approaches. The example of WISEWORK-C, a cluster of five work and health projects within Horizon-Europe
Published 2025-07-01“…These shifts are giving rise to new forms of work (eg, hybrid work, gig economy jobs) and reshaping management and work organization practices (eg, through algorithmic decision-making or digital monitoring of worker performance). …”
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Research on Performance Predictive Model and Parameter Optimization of Pneumatic Drum Seed Metering Device Based on Backpropagation Neural Network
Published 2025-03-01“…The MOPSO algorithm uses the BPNN predictive model as a fitness function to search for the optimal solution for three types of seeds, and the optimized results were verified through bench experiments. …”
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