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2501
Deploying UAV-based detection of bridge structural deterioration with pilgrimage walk optimization-lite for computer vision
Published 2024-12-01“…This system uses UAVs to capture high-resolution images, which are then processed by the You Only Look Once (YOLO) models for instance segmentation. The YOLOv7 model, fine-tuned with the Pilgrimage Walk Optimization (PWO)-Lite algorithm, achieved the highest accuracy, recording a 65.6 % mAP50 on the testing set. …”
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2502
New QSPR/QSAR Models for Organic and Inorganic Compounds: Similarity and Dissimilarity
Published 2025-07-01“…<b>Conclusions:</b> A comparison of different methods for the optimization of correlation weights using the Monte Carlo method showed that optimization can be improved using the coefficient of conformism of a correlative prediction (CCCP) or the index of the ideality of correlation (IIC). …”
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2503
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2504
Optimized CNN-LSTM with hybrid metaheuristic approaches for solar radiation forecasting
Published 2025-08-01“…To improve the accuracy of the model, hyperparameter optimization is applied to the CNN-LSTM model using three metaheuristic algorithms: Particle Swarm Optimization, Grey Wolf Optimization, and Starfish Optimization Algorithm. …”
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2505
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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2506
Evaluation and Optimization of Traditional Mountain Village Spatial Environment Performance Using Genetic and XGBoost Algorithms in the Early Design Stage—A Case Study in the Cold...
Published 2024-09-01“…It then employed the Wallacei_X plugin, which uses the NSGA-II algorithm for multi-objective genetic optimization (MOGO) to optimize five energy consumption and comfort objectives. …”
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2507
Application of a Hybrid Model Based on CEEMDAN and IMSA in Water Quality Prediction
Published 2025-06-01“…Next, Fuzzy Dispersion Entropy (FuzzDE) categorized the components into high-, medium-, and low-complexity subsequences. Then, an Improved Mantis Search Algorithm (IMSA) optimized three distinct models: Bidirectional Long Short-Term Memory (BiLSTM) for high-complexity components, Least Squares Support Vector Regression (LSSVR) for medium-complexity components, and Extreme Learning Machine (ELM) for low-complexity components. …”
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2508
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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2509
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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2510
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2511
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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2512
A Computational Intelligence Framework Integrating Data Augmentation and Meta-Heuristic Optimization Algorithms for Enhanced Hybrid Nanofluid Density Prediction Through Machine and...
Published 2025-01-01“…In particular, autoencoder-based augmentation combined with hyperparameter optimization consistently improved predictive accuracy across all models. …”
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2513
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2514
Predicting equilibrium scour depth around non-circular bridge piers with shallow foundations using hybrid explainable machine learning methods
Published 2024-12-01“…The findings indicate that BOA and STO effectively optimize ANN hyperparameters, resulting in improved prediction accuracy. …”
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2515
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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2516
Predicting COVID-19 severity in pediatric patients using machine learning: a comparative analysis of algorithms and ensemble methods
Published 2025-08-01“…Integrating these predictive models into clinical practice could support early identification of high-risk patients and optimize clinical decision-making.…”
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2517
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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2518
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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2519
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2520
Node optimization coverage method under link model in passive monitoring system of three-dimensional wireless sensor network
Published 2019-08-01“…In the process of optimal coverage, the traditional genetic algorithm and particle swarm optimization algorithm are introduced and improved. …”
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