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Volume 7   Issue 1   Year 2012
Neural Network Analysis of Interdependences of the Top-soil Parameters

Bartsev S.I., Pochekutov A.A., Priputina I.V.

Institute of biophysics, Siberian branch of Russian Academy of Sciences, Krasnoyarsk, Russian Federation
Institute of physicochemical and biological problems of soil science, Russian Academy of Sciences, Pushchino, Moscow Region, Russian Feder

Abstract. To test a possibility of reduction of soil parameters number used for description of total amount of soil organic matter, a neural network analysis of regional soil databases was carried out. It was shown, that two to three soil parameters are sufficient for the prediction of amount of soil organic matter. Herewith, to implement this prediction, a neural network can consist of less then four neurons. The obtained results indicate that it is possible to represent explicated dependencies in terms of relatively simple mathematical formulae. In turn, this gives promise to expect, if not a simplicity of a possible mathematical model of soil forming, a simple form of a dependence of steady states of the model on soil parameters considered in this work.

Key words: neural network analysis of soil parameters, soil organic carbon reserves.

Table of Contents Original Article
Math. Biol. Bioinf.
doi: 10.17537/2012.7.19
published in Russian

Abstract (rus.)
Abstract (eng.)
Full text (rus., pdf)


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