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701
A Minimized Data Collection Optimization Method for Distribution Networks Considering Multiple-Time and Compressed Candidate Sets
Published 2023-12-01“…The minimized data collection technology for distribution networks can optimize the measurement configuration with the minimum economic cost, which plays an important role in improving the system observability. …”
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702
Identification of polynomial models of static load characteristics based on passive experiment results
Published 2024-04-01“…In the paper, the technique based on the initial identification of the linear model, defined by EM-algorithm, and continued by the Lagrange multiplier method optimization with iterations by the Newton method is suggested.Results and discussion. …”
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703
Modeling and Solving the Multi-Objective Vehicle Routing Problem with Soft and Fuzzy Time Windows
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704
Research on Fractional-Order Control of Anchor Drilling Machine Optimized by Intelligent Algorithms
Published 2025-05-01“…To achieve precise docking in unmanned conditions, we employed an inner-loop fractional-order proportional–integral–derivative (FOPID) controller optimized by an improved particle swarm optimization (ILPSO) algorithm. …”
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705
Improved Genetic Algorithm of Helical Gear Reducer and 3D Modeling
Published 2015-01-01“…Based on the penalty function method combined with the improved genetic algorithm,the multi-objective and multi-restriction reliability optimal design of the reducer with hardened tooth surface and modified helical cylinder gear is carried out.According to the properties of the constraint conditions,the different methods are used for effectively avoiding the local optimum problem.The accurate three-dimensional description of the involute gear is carried out by the establishment of the tooth profile curve coordinate equation of the involute gear.According to the interface technology of VB and SolidWorks,the three-dimensional parametric modeling of the involute gear is achieved based on the optimal design results.…”
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706
Charge and discharge scheduling method for large-scale electric vehicles in V2G mode via MLGCSO
Published 2025-05-01“…Compared with traditional methods, the diversity and convergence of particle swarm learning are enhanced, and the optimization performance is improved. Simulation results indicate that when compared with three state-of-the-art optimizers, the optimization accuracy of the proposed algorithm is increased by at least 34% and the total cost is reduced by 3.14% and 1.62% respectively, demonstrating that the MLGCSO exhibits high optimization performance and remarkable optimization effects.…”
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707
Construction and Application of Agricultural Talent Training Model Based on AHP-KNN Algorithm
Published 2023-01-01“…To solve this problem, an improved AHP-KNN algorithm is proposed by combining the analytic hierarchy process (AHP) and the optimized K-nearest neighbor algorithm, and an agricultural talent training model is proposed based on this algorithm. …”
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708
Encapsulation of anticancer drugs into carbon nanotubes: Heuristic algorithm approach and mathematical model.
Published 2025-01-01“…We derive analytical expression for the interaction energy between an atom and an infinite cylinder, and utilize the U-NSGA-III algorithm to optimize the system's energy by varying molecular positions and tube radius. …”
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709
A cloud-metaheuristic-based framework for stochastic optimization of a hybrid wind/hydrogen based-Fuel cell system in distribution network considering uncertainty
Published 2025-08-01“…An improved Fire Hawks Optimization (IFHO) algorithm is utilized in solving the optimization problem by determining the optimal installation locations and sizes of HRES components. …”
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710
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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711
Prediction of CO2 emission for the central European countries through five metaheuristic optimization techniques helping multilayer perceptron
Published 2024-12-01“…To develop a reliable predictive network considering the problem complexity, multilayer perceptron (MLP) is combined with several nature-inspired optimization algorithms, namely, black hole algorithm (BHA), future search algorithm (FSA), backtracking search algorithm (BSA), biogeography-based optimization (BBO), and shuffled complex evolution (SCE). …”
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712
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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713
Fault Diagnosis of Power Equipment Based on Improved SVM Algorithm
Published 2025-07-01“…Therefore, this study proposes an improved support vector machine model, combined with grey wolf optimization algorithm, aimed at improving the accuracy and efficiency of power equipment fault diagnosis. …”
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714
Improved Gradient-Based Optimizer for Modelling Thermal and Hydropower Plants
Published 2022-01-01“…In this research, a modified optimization algorithm called an improved gradient-based optimizer (IGBO) is deployed for the optimal extraction of TPP and HPP input-output parameters. …”
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715
Research on switch migration method based on minimum cost path
Published 2020-02-01“…In order to protect the controller,especially the controller in backbone network,from security threats and attacks,improve the security of the software-defined network (SDN) control plane,a switch migration algorithm based on minimum cost path was proposed.A load prediction module was added to the migration model,which executed a controller load prediction algorithm to obtain a load prediction matrix,and then a migration-target controller set was determined according to the load prediction matrix.The improved Dijkstra algorithm was used to determine the minimum cost path.According to the load state of the controller and the traffic priority of the switch to be migrated,the optimal migration switch set was determined.The problem of isolated nodes was solved that may occur during the migration process.The experimental results show that the migration timing of the algorithm is more reasonable,the selection of the migration controller and the target controller is more reasonable,the load balancing of the control plane is realized,the number of migrations and cost are reduced,and the performance of the controller is improved.…”
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716
Improved Directional Mutation Moth–Flame Optimization Algorithm via Gene Modification for Automatic Reverse Parking Trajectory Optimization
Published 2025-05-01“…To address this, we propose an improved directional mutation moth–flame optimization algorithm with gene modification (IDMMFO-GM). …”
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717
Hybrid extreme learning machine for real-time rate of penetration prediction
Published 2025-08-01“…Abstract This study presents a comparative analysis of hybrid Extreme Learning Machine (ELM) models optimized with metaheuristic algorithms Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Whale Optimization Algorithm (WOA), and Grey Wolf Optimizer (GWO) for real-time Rate of Penetration (ROP) prediction in drilling operations. …”
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718
Methods and Algorithms for Predictive Analytics of Time Series in Energy Consumption
Published 2024-03-01“…States must minimize carbon dioxide emissions and businesses must optimize their energy costs. In this regard, improving energy efficiency plays a key role in solving the climate crisis and reducing costs for businesses. …”
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719
Conflict-based strategy combined integrated optimal conflict avoidance algorithm
Published 2025-02-01“…Next, the low-level model of the traditional CBS algorithm is improved, transforming the path search process into two distinct algorithms with different focuses. …”
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720
Novel nonlinear wind power prediction based on improved iterative algorithm
Published 2025-12-01“…To effectively improve the accuracy of wind power prediction and reduce the load on the power grid, a new nonlinear wind power prediction model based on an improved iterative learning algorithm was investigated. …”
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