Using ensemble systems to study natural processes

Abstract

Increasing accuracy of the data analysis of remote sensing of the Earth significantly affects the quality of decisions taken in the field of environmental management. The article describes the methodology for decoding multispectral space images based on the ensemble learning concept, which can effectively solve important problems of geosystems mapping, including diagnostics of the structure and condition of catchment basins, inventory of water bodies and assessment of their ecological state, study of channel processes; monitoring and forecasting of functioning, dynamics and development of geotechnical systems. The developed methodology is based on an algorithm for analyzing the structure of geosystems using ensemble systems based on a fundamentally new organization of the metaclassifier that allows for a weighted decision based on the efficiency matrix, which is characterized by an increase in accuracy of the decoding of space images and resistance to errors. The metaclassification training algorithm based on the method of weighted voting of monoclassifiers is proposed, in which the weights are calculated on the basis of error matrix metrics. The methodology was tested at the test site ‘Inerka’. The performed experiments confirmed that the use of ensemble systems increases the final accuracy, objectivity, and reliability of the analysis.

Artificial Intelligence Based Ensemble Modeling for Multi-Station Prediction of Precipitation

“…Li and Sankarasubramanian [29] presented a new dynamic approach for combining multiple hydrological models evaluating the performance during prediction and also a weighted averaging method to reduce the modeling uncertainty in monthly streamflow prediction. Yamashkin et al [30] confirmed that reliability, objectivity, and accuracy of the analysis are increased by the use of ensemble systems. Sharghi et al [31] indicated that performance of the seepage modeling can be enhanced by the ensemble method up to 20%.…”

Geodiagnostics of lithogydrogenic systems for forecasting exoggeodynamic processes

“…The ensemble-systems allow to achieve the solution of the task of parameterizing the classifier by sharing models of one class with different parameters. In the framework of the classification of the geophysical surface of the test polygon of "Inerka", the developed [1] ensemble system showed the best result in comparison with individual classificative models (8.02% more accurate than the result shown by the decision tree -the best model from monoclassifiers) and ensemble systems of another architecture by 3.13% more accurate than the result of the ensemble, working on the basis of a simple vote and showing the second result).…”

“…The regional geographic information system "Mordovia" was used as the main sources of information on the regularities in the development of EGP, including, in addition to electronic topographic maps of the space imagery, more than 150 thematic maps and databases [1]. To analyze the development of EGP, morphometric and morphological information was used on the manifestations of landslide, erosion, suffosion, karst processes.…”

Matters of Neural Network Repository Designing for Analyzing and Predicting of Spatial Processes

“…A significant role in solving the problem of strengthening the connectivity of territories of countries and regions is played by the introduction of effective digital infrastructures of spatial data (SDI), aimed at operational diagnostics of natural-socialproduction systems (NSPS) and high-precision forecasting of the development of natural processes and phenomena [1]. The core of systems of this class is represented by methods and algorithms for machine analysis of spatial data, which allow solving a whole range of applied problems -anomaly detection, data classification, data fusion.…”