Magnetic Declination Statistics (Dusheti 1935-1989) and Deep Self-Learning Model

Abstract

Nowadays, there are many new instruments available for studying the parameters of the Earth’s magnetic field with higher precision and more discretization. Moreover, data processing techniques have been developing on strong mathematical basis. The paper presents a rather long-term (1935 - 1950, total 19332 records) data of Dusheti Observatory on the statistics of magnetic declination (1) and considers the possibilities of so called machine learning (ML), a widespread method nowadays. It gives hypotheses to prove certain hidden regularities and periodicity of some geomagnetic parameters and determines so called “storages” of high statistical reliability, which are the etalon samples we use to build attribution function by use of so called Adam Deep Learning network (2