Research of methods and processing of databases on the biomass of Eurasian forests as neural networks. Part 1. System analysis of a database for transformation into neural networks of artificial intelligence

Abstract

The assessment of the carbon storage capacity of forests is now reaching the global level, and the assessment of greenhouse gas absorption at carbon landfills is relevant. The authors have developed and published three author's databases on the biological productivity of Eurasian forests. An algorithm for estimating the incoming part of the carbon cycle (NWP) of the forest cover of the Ural region has been developed, which forms the basis for generating a neural network from initial databases. The present work is devoted to the further development of models and algorithms for the use of these databases, transformed into neural networks to solve urgent global problems of our time related to climate change.