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Neural networks / Time series analysis / Singular value decomposition / Principal component analysis / Artificial neural network / Time series / Global climate model / Seasonality / Statistics / Computational neuroscience / Multivariate statistics


Nonlinear Principal Component Analysis of Climate Data by Sailes K. Sengupta and James S. Boyle Program for Climate Model Diagnosis and Intercomparison Lawrence Livermore National Laboratory Livermore, CA USA
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Document Date: 2004-11-11 17:46:48

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File Size: 1,78 MB

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City

Springfield / /

Company

Lawrence Livermore National Laboratory / /

Country

United States / /

Facility

Lawrence Livermore National Laboratory / Port Royal Rd. / University of California / /

IndustryTerm

observational network / nonlinear processing elements / neural network / auto-associative feed-forward neural networks / data reduction tool / cases such networks / Artificial neural network / auto-associative feed-forward neural network / auto-associative neural network / autoassociative neural networks / extraction algorithm / /

NaturalFeature

Gulf Coast / /

Organization

office of Scientific / University of California / U.S. Department of Commerce / US Federal Reserve / National Center for Atmospheric Research / Department of Energy Environmental Sciences Division / United St Government / United States Government / /

Person

Lawrence Livermore / /

/

Position

model the analysis / auto-associative feed-forward / General / /

ProvinceOrState

Tennessee / Virginia / Florida / Carolinas / California / Arkansas / Michigan / /

PublishedMedium

Atmospheric Research / /

Region

Eastern US / east coast / Gulf Coast / central US / /

Technology

neural network / PCA extraction algorithm / simulation / /

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