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A Novel Algorithm for Enhancing Terrain-Aided Navigation in Autonomous Underwater Vehicles
Published 2024-09-01Get full text
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545
AN APPLICATION OF FUZZY PARTICLE SWARM OPTIMIZATION FOR CUSTOMER ANALYSIS
Published 2017-06-01“…This article presents the application of the Fuzzy Particle Swarm Optimization algorithm for analyzing customer needs. …”
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546
SOLVING ENGINEERING OPTIMIZATION PROBLEMS WITH THE SWARM INTELLIGENCE METHODS
Published 2017-05-01Get full text
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547
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Scalable and cohesive swarm control based on reinforcement learning
Published 2024-01-01Get full text
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549
A novel particle swarm optimisation with mutation breeding
Published 2020-10-01Get full text
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550
An innovative maximum power point tracking for photovoltaic systems operating under partially shaded conditions using Grey Wolf Optimization algorithm
Published 2024-10-01“…Partial shading conditions (PSCs) may be unpredictable and difficult to forecast in large-scale solar photovoltaic (PV) systems. …”
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551
Generic, scalable and decentralized fault detection for robot swarms.
Published 2017-01-01Get full text
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5G Network Deployment Planning Using Metaheuristic Approaches
Published 2024-07-01Get full text
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556
Improving Frequency Control of Multi-Area Interconnected Hydro-Thermal Power System Using PSO Algorithm
Published 2025-03-01Get full text
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557
An efficient metaheuristic optimization algorithm for optimal power extraction from PV systems under various weather and load-changing conditions
Published 2025-09-01“…A comprehensive study compares the HHO technique with established methods such as perturb and observe (P&O), modified P&O (MP&O), incremental conductance (IC), Spline MPPT, particle swarm optimization (PSO), grasshopper optimization (GHO), and grey wolf optimization (GWO) across fast-changing irradiance, partial shading, complex partial shading, and load-changing conditions. …”
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558
Solving MRTA problem based on multi-strategy genetic algorithm
Published 2024-12-01“…This paper proposes a multi-strategy genetic algorithm (DIHA-GA) to address the issues of local optima and low efficiency in solving multi-robot task allocation (MRTA) using genetic algorithm (GA). …”
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