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Modeling and Performance Evaluation of Hybrid Classical–Quantum Serverless Computing Platforms
Published 2025-01-01“…While quantum computing technologies are evolving toward achieving full maturity, hybrid algorithms, such as variational quantum computing, are already emerging as valid candidates to solve practical problems in fields, such as chemistry and operations research. …”
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903
Optimization of thermal conductivity in coir fibre-reinforced PVC composites using advanced computational techniques
Published 2025-05-01“…To address these challenges, the study uses Response Surface Methodology (RSM) and three nature-inspired optimization methods viz. Particle Swarm Optimization (PSO), Dragonfly Optimization (DFO) and Cuckoo Search Algorithm (CSA) to improve factors like fibre content, particle size and chemical treatment. …”
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904
Hierarchical Disturbance Propagation Mechanism and Improved Contract Net Protocol for Satellite TT&C Resource Dynamic Scheduling
Published 2024-06-01“…Dynamic disturbances are propagated layer by layer from the task layer to the central external collaboration layer in a bottom-up manner, using efficient heuristic strategies in the task layer and the resource layer, respectively. We use improved contract network algorithms in the center internal collaboration layer and the center external collaboration layer, the original scheduling plan is quickly adjusted to minimize the impact of disturbances while effectively completing dynamic task requirements. …”
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905
Multi-clause deduction algorithm based on dynamic combination optimization of strategies and its application(策略动态组合优化多元演绎算法及应用)
Published 2024-11-01“…In order to better guide the clause selection in multi-clause deduction, multi-clause deduction method based on dynamic combination optimization of strategies is proposed. This method dynamically combines and iteratively optimizes the number of words and function term depth of clause, fully exploring the existing multi-clause deduction heuristic strategies while improving the adaptability of different problems to strategies, achieving efficient clause selection of multi-clause deduction. …”
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906
Impact of agricultural industry transformation based on deep learning model evaluation and metaheuristic algorithms under dual carbon strategy
Published 2025-07-01“…To enhance model performance, the slime mould algorithm is employed for parameter optimization. Experimental results demonstrated that the hybrid model achieves excellent predictive accuracy, with crop yield prediction exceeding 99%. …”
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907
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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908
Machine-learning based optimizing the neutronic and thermal-hydraulic performance in a VVER-1000 mixed-core as well as fuel burnup assessment
Published 2025-06-01“…By integrating this neural network with a genetic algorithm, optimization was carried out to identify the optimal fuel placement and enrichment for loading the UTVS fuel assembly into the targeted reactor core. …”
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909
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A constructal theory framework for optimizing HRSG design: Enhancing thermal performance and cost-effectiveness
Published 2025-09-01“…Thermal efficiency improvements facilitate a 7.3-9.8% increase in steam production while maintaining optimal pinch point temperature differences of 10-12°C. …”
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911
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Tomato leaf disease detection method based on improved YOLOv8n
Published 2025-07-01“…To address this issue, this paper proposes an optimized YOLOv8n algorithm, incorporating a C2f-DynamicConv optimization module. …”
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913
Enhancing Smart Microgrid Resilience and Virtual Power Plant Profitability Through Hybrid IGWO-PSO Optimization With a Three-Phase Bidding Strategy
Published 2025-01-01“…A hybrid improved grey wolf optimization-particle swarm optimization (IGWO-PSO) algorithm is developed to solve this complex optimization problem. …”
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914
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New Design of Smooth PSO-IPF Navigator With Kinematic Constraints
Published 2024-01-01“…To address this, we propose Smoothed Partial Swarm Optimization with Improved Potential Field (SPSO-IPF), combining both approaches and it is capable of generating a smooth and safe path. …”
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916
Smart homes energy management: Optimal multi-objective appliance scheduling model considering electrical energy storage and renewable energy resources
Published 2025-02-01“…The maximum standard deviation of total objective function between all cases for IBBO, gray wolf optimizer (GWO), and whale optimization algorithm (WOA) are 6.55, 17.22, and 24.87, respectively, which show the robustness of IBBO in finding the best solution in comparisons of other algorithms. …”
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917
Double layered expansion planning for virtual power plants considering virtual energy storage systems
Published 2025-07-01“…To improve computational efficiency, a hybrid Grey Wolf Optimization algorithm is employed for model solution. …”
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918
ACO-NM hybrid optimization calculation method for transit time of oxygen activation logging in CO2 injection profile
Published 2025-08-01“…The least squares method exhibited errors of 9.59% (tubing) and 9.29% (annulus), while the ACO-NM hybrid optimization algorithm yielded relative errors of 1.87% and 3.31% in the tubing and annulus, respectively. …”
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919
Data-driven parameter optimization for bead geometry in wire arc additive manufacturing of 17-4 PH stainless steel
Published 2025-12-01“…Moreover, a genetic algorithm (GA) optimizes for bead uniformity and deposition efficiency. …”
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920
Energy management for microgrids integrating renewable sources and hybrid electric vehicles
Published 2025-05-01“…It also incorporates demand response mechanisms for greater resilience. The Kepler Optimization Algorithm (KOA), inspired by Kepler's laws of planetary motion, is employed to tackle the nonlinear optimization problem. …”
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