A hybrid deep learning and metaheuristic optimization algorithm for accurate and scalable community detection in complex networks

Key Points

• Community detection accuracy significantly improved through a hybrid deep learning approach and metaheuristic optimization.
• The proposed algorithm achieved a notable enhancement with a 20% increase in detection precision compared to traditional methods.
• This analysis employs a hybrid algorithm combining deep learning techniques and optimization strategies to analyze complex networks.
• Implications highlight the potential for scalable community detection, although scalability in larger networks needs further evaluation.