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1701
The Study of Roadside Visual Perception in Internet of Vehicles Based on Improved YOLOv5 and CombineSORT
Published 2025-01-01“…It indicates that most algorithms can achieve good detection results when the targets are sparse, and the lightweight models may have more advantages with considering the demand of computing resources. …”
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1702
Meta-transformer: leveraging metaheuristic algorithms for agricultural commodity price forecasting
Published 2025-05-01“…To address these challenges, this study proposes a novel framework that combines Transformer models with Metaheuristic Algorithms (MHAs), including the Grey Wolf Optimizer (GWO), Whale Optimization Algorithm (WOA), and Particle Swarm Optimization (PSO) to enhance agricultural price forecasting accuracy. …”
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1703
A Hybrid ARO Algorithm and Key Point Retention Strategy Trajectory Optimization for UAV Path Planning
Published 2024-11-01“…An effective path planning algorithm can greatly improve the operational efficiency of UAVs in complex environments like urban and mountainous areas, thus offering more extensive coverage for various tasks. …”
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1704
Particle Swarm Optimization Based Optimal Design of Six-Phase Induction Motor for Electric Propulsion of Submarines
Published 2022-04-01“…This research presented a comparison of optimal model design of a six phase squirrel cage induction motor (IM) for electric propulsion by using Genetic Algorithm (GA) and Particle Swarm Optimization (PSO). …”
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1705
Inverse methods and integral-differential model demonstration for optimal mechanical operation of power plants – numerical graphical optimization for second generation of tribology...
Published 2018-07-01“…Stepping forward from a previous conference contribution, the article focuses on extension of inverse problem algorithms to integral-differential modelling and formal/strict demonstration of graphical-optimization method. …”
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1706
An analytical optimal calibration framework of bonded particle model for rock strength envelop modelling
Published 2025-05-01“…Adaptive moment estimation (Adam) was chosen as the iterative optimization algorithm to avoid the vanishing gradient problem. …”
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1707
A multi-objective improved horse herd optimizer based on convex lens imaging for stochastic optimization of wind energy resources in distribution networks considering reliability a...
Published 2024-11-01“…Abstract In this study, stochastic multi-objective allocation of wind turbines (WTs) in radial distribution networks is performed using a new multi-objective improved horse herd optimizer (MOIHHO) and an unscented transformation (UT) method for modeling the uncertainties of WTs power and network load. …”
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1708
An unmanned intelligent inspection technology based on improved reinforcement learning algorithm for power large-area multi-scene inspection
Published 2025-07-01“…Consequently, this study investigates a multi scene unmanned intelligent patrol technology for power large area, based on an improved reinforcement learning algorithm. The unmanned intelligent patrol model is designed according to the patrol UAVs, wireless charging piles distributed in appropriate locations, and the targets to be patrolled (i.e., multiple scenes within a large power area). …”
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1709
A recommender algorithm based on SVD ++model under trust network
Published 2021-07-01“…Recommender algorithms are usually modeled based on user behavior data.However, the sparseness of explicit behavior data may cause the cold start problem of recommender algorithms.In order to solve the impact of data sparseness and cold-start problems on the effect of recommender algorithms, implicit trust relationship based on user similarity was introduced based on the existing revealed trust relationship, and a new recommender algorithm was designed through the SVD++ implicit semantic model.In order to improve the effect of the algorithm, the neighborhood model was integrated further, and the algorithm score prediction formula and loss function were derived.In the Epinions open source data set, RMSE and MAE were used as test indicators, and comparative experiments were conducted on the entire user set and the cold start user set.The experimental results show that the recommender algorithm can optimize the cold start problem of the original recommender algorithm to a certain extent, and achieve a better rating prediction accuracy.…”
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1710
Research on rock strength prediction model based on machine learning algorithm
Published 2024-12-01“…By selecting different features, the optimal feature combination for predicting rock compressive strength was obtained, and the optimal parameters for different models were obtained through the Sparrow Search Algorithm (SSA). …”
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1711
Study on the Switching Model Predictive Control Algorithm in Batch Polymerization Process
Published 2025-06-01“…Finally, a switching model predictive control algorithm that determines the optimal manipulated value based on the on-line updated step response model is constructed, and a cascade control system using this algorithm is introduced to the temperature control of batch polyvinyl chloride suspension polymerization process. …”
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1712
Applicability of Different Assimilation Algorithms in Crop Growth Model Simulation of Evapotranspiration
Published 2024-11-01Get full text
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1713
Sustainable supply chain: An optimization and resource efficiency in additive manufacturing for automotive spare part
Published 2025-06-01“…Leveraging genetic algorithm techniques for optimization and reinforced by rigorous numerical analysis, its efficacy and validity are robustly demonstrated.…”
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1714
Study on the anti-penetration randomness of metal protective structures based on optimized artificial neural network
Published 2025-05-01“…And by adopting the Back Propagation Neural Network optimized by Dynamic Lifecycle Genetic Algorithm (DLGABPNN) as the surrogate model of APRMPS, this paper presents the technical route of DLGABPNN-MCS, the Monte Carlo Simulation with DLGABPNN calculation as repeated sampling tests, to addressing APRMPS. …”
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1715
Ensemble Learning-Based Wine Quality Prediction Using Optimized Feature Selection and XGBoost
Published 2025-10-01Get full text
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1716
Predictive Ecological Cooperative Control of Electric Vehicles Platoon on Hilly Roads
Published 2025-03-01“…Unlike most existing literature that focuses on suboptimal coordination under predefined leading vehicle trajectories, this strategy employs an approach based on the combination of a long short-term memory network (LSTM) and genetic algorithm (GA) optimization (GA-LSTM) to predict the future speed of the leading vehicle. …”
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1717
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1718
Prediction of Interest Rate Using Artificial Neural Network and Novel Meta-Heuristic Algorithms
Published 2021-03-01“…The main goal of this article, as it is clear from the title, is the prediction of interest rate using ANN and improving the network using some novel heuristic algorithms such as Moth Flame Optimization algorithm (MFO), Chimp Optimization Algorithm (CHOA), Time-varying Correlation Particle Swarm Optimization algorithm (TVAC-PSO), etc. we used 17 variables such as oil price, gold coin price, house price, etc. as input variables. …”
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1719
Adaptive energy loss optimization in distributed networks using reinforcement learning-enhanced crow search algorithm
Published 2025-04-01“…Unlike traditional methods such as Genetic Algorithm (GA), Particle Swarm Optimization (PSO), and standard Crow Search Algorithm (CSA), which suffer from premature convergence and limited adaptability to real-time variations, Reinforcement Learning Enhanced Crow Search Algorithm (RL-CSA) which is proposed in this research work solves network reconfiguration optimization problem and minimize energy losses. …”
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1720
Data-Driven Battery Remaining Life Prediction Based on ResNet with GA Optimization
Published 2025-05-01“…To this end, this paper proposes a data-driven lithium-ion battery life prediction method based on residual network (ResNet) and genetic algorithm (GA) optimization, which is designed to screen the features of the lithium-ion battery training data in order to effectively reduce the redundant features and improve the prediction performance of the model. …”
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