Proceedings of the 2014 International Conference on Mechatronics, Control and Electronic Engineering

Self-adaptive Differential Evolution Extreme Learning Machine for the Classification of Hyperspectral Images

Authors
Junhua Ku, Zhihua Cai, Xiuying Yang
Corresponding Author
Junhua Ku
Available Online March 2014.
DOI
https://doi.org/10.2991/mce-14.2014.144How to use a DOI?
Keywords
Differential Evolution; Self-adaptive; Extreme Learning Machine; Hyperspectral Images;Machine Learning
Abstract
In this paper, we propose an efficient classification method for hyperspectral images based on the extreme learning machine (ELM) and self-adaptive differential evolution (jDE).The approach of ELM is characterized by a unified formulation for regression, binary, and multiclass classification problems, and the related solution is given in an analytical compact form. In order to address the selection issue that is associated with the ELM, we have developed an automatic method to solve the model selection issue that is associated with this classifier based on the jDE optimization. The self-adaptive control mechanism is used to change control parameters, i.e. select weighting factor F and crossover constant CR, during the run. This simple yet powerful evolutionary optimization algorithm uses cross-validation accuracy as a performance indicator for determining the optimal ELM parameters. Experimental results obtained from hyperspectral data set confirm the attractive properties of the proposed jDE-ELM method in terms of classification accuracy and computation time.
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Proceedings
2014 International Conference on Mechatronics, Control and Electronic Engineering (MCE-14)
Part of series
Advances in Intelligent Systems Research
Publication Date
March 2014
ISBN
978-94-62520-31-8
ISSN
1951-6851
DOI
https://doi.org/10.2991/mce-14.2014.144How to use a DOI?
Open Access
This is an open access article distributed under the CC BY-NC license.

Cite this article

TY  - CONF
AU  - Junhua Ku
AU  - Zhihua Cai
AU  - Xiuying Yang
PY  - 2014/03
DA  - 2014/03
TI  - Self-adaptive Differential Evolution Extreme Learning Machine for the Classification of Hyperspectral Images
BT  - 2014 International Conference on Mechatronics, Control and Electronic Engineering (MCE-14)
PB  - Atlantis Press
SP  - 645
EP  - 649
SN  - 1951-6851
UR  - https://doi.org/10.2991/mce-14.2014.144
DO  - https://doi.org/10.2991/mce-14.2014.144
ID  - Ku2014/03
ER  -