<i>Application of Electronic Nose System Modes Based on Genetic Algorithm and Particle Swarm Algorithm</i>

Nanjing Wu; Wenshen Jia; Jie Ma

doi:10.13031/aim.201700939

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Application of Electronic Nose System Modes Based on Genetic Algorithm and Particle Swarm Algorithm

Published by the American Society of Agricultural and Biological Engineers, St. Joseph, Michigan www.asabe.org

Citation:  2017 ASABE Annual International Meeting 1700939.(doi:10.13031/aim.201700939)
Authors:   Nanjing Wu, Wenshen Jia, Jie Ma
Keywords:   Electronic Nose , Pattern Recognition Algorithm, Genetic Algorithm ,Particle Swarm Algorithm, Sensor Array

Abstract. In this paper, composition and working mechanism of the electronic nose were introduced. Highlights in electronic nose research were figured out. Principles of genetic algorithm and particle swarm algorithm and their application in electronic nose mode identification were described in detail. Genetic algorithm (GA) is a kind of global optimum algorithm. It has many advantages such as randomness, scalability and compatibility with other algorithms. Particle swarm optimization (PSO) is also a kind of global optimum algorithm. It features fast convergence, “self-learning for progress” and “learning from others for progress”. No matter whether it is used separately or in the form of combination with others, it can reach a very high accuracy and occupy very few resources. Thus, it has a great research prospect.

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