Integrating particle swarm optimization with learning automata to solve optimization problems in noisy environment

Keyphrases

• Optimization Problem 100%
• Learning Automata 100%
• Particle Swarm Optimization 100%
• Noisy Environment 100%
• Learnability 66%
• Resampling Methods 66%
• Low Computational Complexity 66%
• Self-adaption 66%
• Automatic Learning 66%
• Accurate Algorithm 33%
• Convergence Rate 33%
• Selection Mechanism 33%
• Fast Algorithm 33%
• Hybrid Method 33%
• Noise Level 33%
• Brilliant 33%
• Novel Hybrids 33%
• Performance Results 33%
• Large-scale Benchmark 33%
• Accuracy Rate 33%
• Fast Convergence 33%
• Benchmark Functions 33%
• Objective Value 33%
• Evolutionary Algorithms 33%
• Candidate Particles 33%

Computer Science

• Optimization Problem 100%
• Automaton 100%
• Particle Swarm Optimization 100%
• Noisy Environment 100%
• Computational Complexity 66%
• Hybrid Approach 66%
• Convergence Rate 33%
• Fast Algorithm 33%
• Fast Convergence 33%
• Benchmark Function 33%
• Evolutionary Algorithms 33%