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3141
Novel Gaussian-Decrement-Based Particle Swarm Optimization with Time-Varying Parameters for Economic Dispatch in Renewable-Integrated Microgrids
Published 2025-07-01“…Findings: Field case studies demonstrate that, compared to other algorithms, the improved Particle Swarm Optimization algorithm effectively reduces the operational costs of microgrid systems while exhibiting accelerated convergence speed and enhanced robustness. …”
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3142
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3143
Design and Performance Optimization of a Radial Turbine Using Hydrogen Combustion Products
Published 2024-12-01“…This study aims to design a radial turbine using the differential evolution (DE) algorithm to improve its characteristics and optimize its aerodynamic performance through an orthogonal experiment and analysis of means (ANOM). …”
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3144
Double and integer multi-objective optimization of solar HDH desalination system with bubble column dehumidifier: An artificial neural network approach
Published 2025-09-01“…The gain output ratio (GOR) is selected to indicate the thermal performance, while the unit cost of water produced (UCWP) is chosen to reflect the economic performance. …”
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3145
Optimized Dimensioning and Economic Assessment of Decentralized Hybrid Small Wind and Photovoltaic Power Systems for Residential Buildings
Published 2025-04-01“…In contrast, electricity production from small wind turbines remains marginal (<0.01%). While currently only viable in high-wind locations, factors like rising electricity prices, cheaper battery storage, and increasing electrification could boost their future role. …”
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3146
Extended target tracking with mobility based on GPR-AUKF
Published 2024-12-01“…Specifically, the GPR-AUKF algorithm is built based on expectation maximization (EM) algorithm to track the target state and covariance, and which updates the measurement noise covariance in real-time. …”
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3147
Metaheuristic Prediction Models for Kerf Deviation in Nd-YAG Laser Cutting of AlZnMgCu1.5 Alloy
Published 2025-02-01“…A detailed investigation was conducted to examine the effects of various parameters on kerf deviation. The metaheuristic algorithms (i.e., Giant Trevally Optimizer—GTO; and Zebra Optimization Algorithm—ZOA) were implemented to determine the optimum process parameters for producing the best performance measures. …”
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3148
A novel two stage neighborhood search for flexible job shop scheduling problem considering reconfigurable machine tools
Published 2025-06-01“…Experimental results on extended benchmark instances demonstrate that the proposed IGA-TNS effectively addresses the FJSP-MR, outperforming other algorithms in solution quality and computational efficiency. …”
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3149
A Two-Stage Optimization Method for Multi-Runway Departure Sequencing Based on Continuous-Time Markov Chain
Published 2025-03-01“…Then, continuous-time Markov chains (CTMC) were employed to track aircraft state transitions in the taxiway queue, and a nested whale optimization algorithm was proposed to optimize both the pushback sequence and runway resource allocation. …”
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3150
Design optimization of multipoles radial magnetic bearings for large industrial rotors
Published 2025-07-01“…The design objective is to minimize the bearing volume while providing the required bearing capacity, taking into consideration the design constraints imposed. …”
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3151
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3152
Fusion of MHSA and Boruta for key feature selection in power system transient angle stability
Published 2025-01-01“…Subsequently, the Boruta algorithm is employed to determine the number of key features. …”
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3153
Milling Machine Fault Diagnosis Using Acoustic Emission and Hybrid Deep Learning with Feature Optimization
Published 2024-11-01“…The genetic algorithm (GA) is used to optimize feature selection and ensure the selection of the most relevant features to further improve the model’s performance. …”
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3154
Knowledge Graph-Enhanced Digital Twin Framework for Optimized Job Shop Scheduling in Smart Manufacturing
Published 2025-01-01“…The approach is grounded in a DT framework that leverages a knowledge graph to represent the assets of the manufacturing system. Two algorithms are designed to balance the time required to complete a list of jobs with the energy consumed by the machines in the factory, all while considering the delivery deadline of the final product. …”
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3155
A new type of sustainable operation method for urban rail transit: Joint optimization of train route planning and timetabling
Published 2025-12-01“…To solve large-scale problems, an improved adaptive large neighborhood search algorithm (ALNS) is designed accordingly. The proposed method's solution efficiency is compared with genetic algorithms (GA) and commercial solvers (CPLEX) through small case studies. …”
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3156
A metaheuristic-based approach for optimizing the allocation of emergency water reservoirs for fire following earthquake suppression
Published 2025-09-01“…Using a metaheuristic algorithm, the optimal allocation zones are identified based on the total distance from urban areas and the FFE risk factor. …”
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3157
Comprehensive quality assessment of 296 sweetpotato core germplasm in China: A quantitative and qualitative analysis
Published 2024-12-01“…Landraces had higher sugar content in roots, while wild relatives showed increased total flavonoid and phenol contents. …”
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3158
Salp Navigation and Competitive based Parrot Optimizer (SNCPO) for efficient extreme learning machine training and global numerical optimization
Published 2025-04-01“…The results demonstrate that SNCPO consistently outperforms existing state-of-the-art algorithms, achieving superior convergence speed, solution quality, and robustness while effectively avoiding local optima. …”
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3159
Energy-efficient artificial fish swarm-based clustering protocol for enhancing network lifetime in underwater wireless sensor networks
Published 2024-12-01“…It also reduces energy consumption by 25.6% and decreases packet loss by 50.5%, while achieving 20.4% higher throughput at the initial stage. …”
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3160
A composite photovoltaic power prediction optimization model based on nonlinear meteorological factors analysis and hybrid deep learning framework
Published 2025-08-01“…Firstly, to reduce the redundancy of the input for the prediction model and the computational time complexity, while enhancing the robustness and stability of the prediction model, nonlinear correlation search algorithm based on time window extending and time window shrinking strategies have been proposed. …”
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