Pigeon-inspired optimization approach to information granulation-based fuzzy RBF neural networks for image fusion

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Nowadays, bio-mimetic method comes more and more popular as being applied in various fields including image fusion. A number of population-based algorithms are proposed to solve this kind of problem for example the ant colony optimization and the artificial bee colony optimization. In this paper, an original approach with bionic solutions named Pigeon-Inspired Optimization (PIO) is proposed, which possesses high efficiency especially for discrete optimization problem. It is combined with the fuzzy radial basis function neural network to optimize the problem of image fusion. A population-based searching process is provided to the optimization model, which is inspired by the movements of pigeons that can accurately guide a group of pigeons to their final destination. A series of experiments are set up in this paper to verify the feasibility and effectiveness of the method.

Original languageEnglish
Title of host publicationCGNCC 2016 - 2016 IEEE Chinese Guidance, Navigation and Control Conference
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1928-1933
Number of pages6
ISBN (Electronic)9781467383189
DOIs
StatePublished - 20 Jan 2017
Event7th IEEE Chinese Guidance, Navigation and Control Conference, CGNCC 2016 - Nanjing, Jiangsu, China
Duration: 12 Aug 201614 Aug 2016

Publication series

NameCGNCC 2016 - 2016 IEEE Chinese Guidance, Navigation and Control Conference

Conference

Conference7th IEEE Chinese Guidance, Navigation and Control Conference, CGNCC 2016
Country/TerritoryChina
CityNanjing, Jiangsu
Period12/08/1614/08/16

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