European Journal of Computer Science and Information Technology (EJCSIT)

EA Journals

Application of Particle Swarm Optimization Technique for Predicting Fire Outbreak Caused By Electrical Fault

Abstract

This Research work introduces Particle swarm optimization technique for predicting fire outbreaks in industrial environment. The Particle swarm optimization (PSO) method is a swarm-based heuristic, which mimics the foraging behavior of bird flocks. Two Experiments were conducted, the first Experiment (Exp. 1) using 26 different test simulations was performed, using different fault resistance, a constant population size of 20 and max iteration of 5. It shows that when the fault resistance is between 0.3 ohm – 0.0 ohm, there will be likelihood of danger occurring among all faults at the same time, and none of the faults will be normal. While the second Experiment (Exp. 2) conducted, using 26 different test simulations was performed, using different fault resistance, a constant population size of 100 and max iteration of 50, it proves that when the fault resistance is between 0.35 ohm – 0.0-ohm fault resistance, there will be likelihood of danger occurring among all faults at the same time. Results prove that PSO can be used to predict fire outbreak caused by electrical faults.

Keywords: Particle swarm optimization, fault resistance, fire outbreaks, population size and max iteration., swarm-based heuristic

cc logo

This work by European American Journals is licensed under a Creative Commons Attribution-NonCommercial-NoDerivs 4.0 Unported License

 

Recent Publications

Email ID: editor.ejcsit@ea-journals.org
Impact Factor: 7.80
Print ISSN: 2054-0957
Online ISSN: 2054-0965
DOI: https://doi.org/10.37745/ejcsit.2013

Author Guidelines
Submit Papers
Review Status

 

Scroll to Top

Don't miss any Call For Paper update from EA Journals

Fill up the form below and get notified everytime we call for new submissions for our journals.