A semi-evolutionary approach for modeling pedotransfer functions with small size of data using artificial neural networks

Authors:
T. M. Taheri;K. Mahdaviani;J. Mohammadi
Affiliations:
School of Mathematical Sciences, Isfahan University of Technology, Isfahan, Iran;Electrical and Computer Engineering Faculty, Isfahan University of Technology, and Isfahan Mathematics, Isfahan, Iran;Soil Science Department, College of Agriculture, Shahrekord University, Shahrekord, Iran
Venue:
ISTASC'06 Proceedings of the 6th WSEAS International Conference on Systems Theory & Scientific Computation
Year:
2006

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Abstract

Pedotransfer functions are predictive functions of certain soil properties based on their easily or cheaply measured features. An approach based on the artificial neural networks is taken to model such functions. Due to the small size of the relevant data set, a especial procedure is used to design the architecture of the suitable network to avoid the problem of overfitting.