Ranking spatially distributed systems for resource monitoring in the emergency situations

Oleksandr Zarytskyi

O. M. Beketov National University of Urban Economy in Kharkiv

https://orcid.org/0000-0003-0790-8399

Oleksandr Kostenko

O. M. Beketov National University of Urban Economy in Kharkiv

http://orcid.org/0000-0001-9744-4377

DOI: https://doi.org/10.5281/zenodo.4400179

Keywords: emergency situation, regional resources, spatially distributed systems, ranking, production model

Abstract

The problem of improving the quality of input data to support decision-making in humanitarian logistics in the article has been explored. The role of spatial-distributed systems for disaster relief tasks has been determined. The risks that exist in information interaction and influence the proper support for emergency decision-making has been analyzed. The deployment of a dynamic spatial distributed system to organize spatial distributed data in the region has been substantiated. The system of rating coeffi-cients, which saves information resources for the construction of logistics and rescue measures, has been presented. Information technology of unification with ranking for information interaction control of spa-tial distributed systems of the field of use and territories planning has been developed. The production mathematical model, on the basis of which the obtaining of high-quality and reliable input data for the needs of humanitarian logistics was ensured, has been developed. The role of ordered input data for dis-aster control optimization and accuracy improvement of further empirical results has been determined. It is shown that the developed information technology of unification with ranking increases the quality of filling input data for any models of formation of supporting information materials in the process of sup-porting decision-making in emergency situations. The analysis of the results suggests that the ordering and reliability of representation of regional resources will contribute to the accurate determination of the scale of damage to the territories as a result of fires and flooding, also to data recovery on the territory property structure, which was partially destroyed or damaged by natural disasters.

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