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Markov Chain in Particle Swarm Optimization by ijsc is a document available to read on EtoBox.

What is Markov Chain in Particle Swarm Optimization about?

1. The document analyzes the Particle Swarm Optimizer algorithm using a theoretical Markov chain approach. It defines the state of the PSO process and proves it has a memory-less property. 2. By dividing the PSO process into countable stages, the document establishes that PSO forms a stationary Markov chain. 3. Based on properties of Markov chains, the document proposes an adaptive method for selecting PSO parameters.

Author

ijsc

Language

EN