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GLOPS: A Hybrid Approach for Enhanced Scheduling in Cloud Computing Environments via Machine Learning-Based Process Prediction
Published 2025-01-01“…However, early predictions would seem futile without efficient scheduling, which is why the article further proposes Global and Local Optimized Preemptive Scheduling (GLOPS), an enhanced metaheuristic scheduling algorithm employing Particle Swarm Optimization and Simulated Annealing. …”
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A Key Management Method Based on Dynamic Clustering for Sensor Networks
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A Novel Network Optimization Scheme Based on Anti-Flocking and Improved Nash Equilibrium Algorithm
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Intra-Net Cognitive Radio Intelligent Utility Maximization using Adaptive PSO-Gradient Algorithm
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Research on over-the-horizon air combat guidance method based on dynamic RCS
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A multi-objective metaheuristic method for node placement in dynamic IoT environments
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Azimuth and Elevation Dynamic Tracking of UAVs via 3-Axial ULA and Particle Filtering
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Study on Multi-Objective Optimization of Construction of Yellow River Grand Bridge
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Research on Dynamic Dissolving Model and Experiment for Rock Salt under Different Flow Conditions
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Deep Reinforcement Learning-Based Adaptive Nulling in Phased Array Under Dynamic Environments
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