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An Overview of Variants and Advancements of PSO Algorithm

📅 Published: August 23, 2022 👤 Meetu Jain, Vibha Saihjpal, Narinder Singh et al. 📖 Applied Sciences 📊 659 citations
AI-Generated Summary

Particle swarm optimization (PSO) is one of the most famous swarm-based optimization techniques inspired by nature. In the present paper, an overview of the PSO algorithm is presented.

⚡ This is an original paraphrased summary — not copied from the abstract. Full paper available at the source link below.

Key Findings
  • 1 Due to its properties of flexibility and easy implementation, there is an enormous increase in the popularity of this nature-inspired technique.
  • 2 Particle swarm optimization (PSO) has gained prompt attention from every field of researchers.
  • 3 Since its origin in 1995 till now, researchers have improved the original Particle swarm optimization (PSO) in varying ways.
Why It Matters

This research advances how AI systems learn, reason, and solve problems — with direct implications for automation and scientific discovery.

This summary is based on publicly available metadata and abstract. For the full research paper, visit the original source:

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Article Details
Source OpenAlex
Category 🤖 Artificial Intelligence
Published Aug 23, 2022
Journal Applied Sciences
DOI 10.3390/app12178392
Citations 659
Authors Meetu Jain, Vibha Saihjpal, Narinder Singh, Satya Bir Singh