TITLE

Crop Classification by Forward Neural Network with Adaptive Chaotic Particle Swarm Optimization

AUTHOR(S)
Yudong Zhang; Lenan Wu
PUB. DATE
May 2011
SOURCE
Sensors (14248220);2011, Vol. 11 Issue 5, p4721
SOURCE TYPE
Academic Journal
DOC. TYPE
Article
ABSTRACT
This paper proposes a hybrid crop classifier for polarimetric synthetic aperture radar (SAR) images. The feature sets consisted of span image, the H/A/a decomposition, and the gray-level co-occurrence matrix (GLCM) based texture features. Then, the features were reduced by principle component analysis (PCA). Finally, a two-hidden-layer forward neural network (NN) was constructed and trained by adaptive chaotic particle swarm optimization (ACPSO). K-fold cross validation was employed to enhance generation. The experimental results on Flevoland sites demonstrate the superiority of ACPSO to back-propagation (BP), adaptive BP (ABP), momentum BP (MBP), Particle Swarm Optimization (PSO), and Resilient back-propagation (RPROP) methods. Moreover, the computation time for each pixel is only 1.08 × 10-7 s.
ACCESSION #
62035989

 

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