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Application of Bayesian Regularized BP Neural...
Journal article

Application of Bayesian Regularized BP Neural Network Model for Trend Analysis, Acidity and Chemical Composition of Precipitation in North Carolina

Abstract

Bayesian regularized back-propagation neural network (BRBPNN) was developed for trend analysis, acidity and chemical composition of precipitation in North Carolina using precipitation chemistry data in NADP. This study included two BRBPNN application problems: (i) the relationship between precipitation acidity (pH) and other ions (NH4+, NO3−, SO42−, Ca2+, Mg2+, K+, Cl− and Na+) was performed by BRBPNN and the achieved optimal network structure …

Authors

Xu M; Zeng G; Xu X; Huang G; Jiang R; Sun W

Journal

Water, Air, & Soil Pollution, Vol. 172, No. 1-4, pp. 167–184

Publisher

Springer Nature

Publication Date

5 2006

DOI

10.1007/s11270-005-9068-8

ISSN

0049-6979

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