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Memetic Computing
Erschienen in: Memetic Computing 1/2015

01.03.2015 | Regular Research Paper

A BBO based framework for natural terrain identification in remote sensing

verfasst von: Arpita Sharma, Samiksha Goel

Erschienen in: Memetic Computing | Ausgabe 1/2015

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Abstract

Nature inspired intelligence is increasingly being used to solve complex problems. Identifying different types of terrains present in the satellite imagery of a given region is one such problem in the field of remote sensing. Prospects of its numerous applications in real life have been a motivating factor for scientists to develop newer terrain analyzers to perform this task with more precision. This paper presents a two phase biogeography based optimization (BBO) based generic frame work for identifying natural terrain features in a given region. BBO is a population-based algorithm and is based on the theory of island biogeography that explains the geographical distribution of biological organisms. Validation is performed on two remote sensing datasets for Alwar and Delhi regions in India. Better performance of proposed analyzers has been observed as compared to state of the art techniques.
Vorheriger Artikel A computational ecosystem for optimization: review and perspectives for future research
Nächster Artikel A memetic algorithm with support vector machine for feature selection and classification

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Metadaten
Titel
A BBO based framework for natural terrain identification in remote sensing
verfasst von
Arpita Sharma
Samiksha Goel
Publikationsdatum
01.03.2015
Verlag
Springer Berlin Heidelberg
Erschienen in
Memetic Computing / Ausgabe 1/2015
Print ISSN: 1865-9284
Elektronische ISSN: 1865-9292
DOI
https://doi.org/10.1007/s12293-015-0154-1

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