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A Review of Stochastic Optimization Algorithms Applied in Food Engineering
Published 2024-01-01“…It was observed that evolutionary methods are the most applied in solving food engineering optimization problems where the genetic algorithm and differential evolution stand out. …”
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62
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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63
Study on optimization of Al6061 sphere surface roughness in diamond turning based on central composite design model and grey wolf optimizer algorithms
Published 2025-02-01“…This paper presents optimization results of the Al6061 surface roughness in turning ultra-precision based on the central composite design method (CCD) and the grey wolf optimization algorithm (GWO). …”
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64
Forecasting Influenza Trends Using Decomposition Technique and LightGBM Optimized by Grey Wolf Optimizer Algorithm
Published 2024-12-01“…Accurate influenza prediction is a critical issue in public health and serves as an essential tool for epidemiological studies. This paper seeks to improve the prediction accuracy of influenza-like illness (ILI) proportions by proposing a novel predictive model that integrates a data decomposition technique with the Grey Wolf Optimizer (GWO) algorithm, aiming to overcome the limitations of current prediction methods. …”
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65
Improved Virtual Potential Field Algorithm Based on Probability Model in Three-Dimensional Directional Sensor Networks
Published 2012-05-01“…The extensive simulations results demonstrate the effectiveness of our proposed 3D sensing model and IPA3D (improved virtual potential field based algorithm in three-dimensional directional sensor networks).…”
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66
A Model Predictive Control to Improve Grid Resilience
Published 2025-04-01“…The following article details a model predictive control (MPC) to improve grid resilience when faced with variable generation resources. …”
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67
Leveraging retinanet based object detection model for assisting visually impaired individuals with metaheuristic optimization algorithm
Published 2025-05-01“…This paper proposes a novel Object Detection Model for Visually Impaired Individuals with a Metaheuristic Optimization Algorithm (ODMVII-MOA) technique. …”
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First-principle modeling of parallel-flow regenerative kilns and their optimization with genetic algorithm and gradient-based method
Published 2024-12-01“…Finally, we use a genetic algorithm to optimize the feed mass flows such that the conversion and the fuel efficiency are improved in a Pareto-optimal manner. …”
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70
Development of Hybrid Optimization Model Using Grey-ANFIS-Jaya Algorithm for CNC Drilling of Aluminium Alloy
Published 2024-01-01“…Statistical error analysis is used to estimate the performance of the established optimization model. Based on the investigative outcomes, the best-suited process variable combinations will be used to provide improved and enhanced multiperformance characteristics.…”
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71
Developing a Machine Learning-Driven Model that Leverages Meta-Heuristic Algorithms to Forecast the Load-Bearing Capacity of Piles
Published 2023-12-01“…Findings show that the GPR-GJO model provides the most accurate Pu predictions, emphasizing its potential to optimize pile design, mitigate risks, and ensure long-term structural safety.…”
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72
TBESO-BP: an improved regression model for predicting subclinical mastitis
Published 2025-04-01“…The TBESO algorithm notably enhances the efficacy of the BP neural network in regression prediction, ensuring elevated computational efficiency and practicality post-improvement.…”
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YOLOGX: an improved forest fire detection algorithm based on YOLOv8
Published 2025-01-01“…Finally, the proposed Focal-SIoU loss function replaces the original loss function, effectively reducing directional errors by combining angle, distance, shape, and IoU losses, thus optimizing the model training process. YOLOGX was evaluated on the D-Fire dataset, achieving a mAP@0.5 of 80.92% and a detection speed of 115 FPS, surpassing most existing classical detection algorithms and specialized fire detection models. …”
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75
Employment of a Radial Basis Function Model for Predicting the Heating Load of Construction
Published 2025-04-01“…The innovative approaches presented in this research consist of integrating 2 advanced optimizers, namely an Improved Manta-Ray Foraging Optimizer (IMRFO) and a Population-based Vortex Search Algorithm (PVSA), with a Radial Basis Function (RBF). …”
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Multi-objective optimization of a novel control algorithm and scheduling procedure for optimal use of energy storage systems
Published 2025-04-01“…Peak shaving with energy storage systems (ESSs) is a promising approach to optimize energy use, reduce costs, and ensure a more reliable power grid.This paper aims to improve the performance of a novel control algorithm for efficient peak shaving by using sensitivity analysis and multi-objective optimization techniques. …”
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Optimized Negative Selection Algorithm for Image Classification in Multimodal Biometric System
Published 2023-04-01“…Hence, this work developed an Optimized Negative Selection Algorithm (ONSA) for image classification in biometric systems. …”
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78
Gradient-Enhanced Kriging-Based Parallel Efficient Global Optimization Algorithm and Its Application in Aerodynamic Shape Optimization
Published 2025-01-01“…To further enhance the optimization potential of the parallel EGO algorithm, an improved system that integrates the parallel EGO algorithm with gradient-enhanced kriging (GEK) is proposed. …”
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An Enhanced Local Optimization Algorithm for GNSS Shadow Matching in Mobile Phones
Published 2025-02-01“…In the context of mobile phones, the local optimal global navigation satellite systems (GNSS) shadow matching algorithm, which is based on the urban three-dimensional model, can effectively reduce the error of GNSS pseudo-range single-point positioning. …”
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