Lyashenko E. Models and methods of information support for decision-making on the prevention of forest fires

The object of research - decision-making process of prevention of forest fires. Subject of research - models and methods of decision support information to prevent forest fires. Methods of research - theoretical study based on the theory of artificial intelligence, theory of relational databases, predictive data analysis, visualization of spatial data, GIS techniques and technologies - systems. Scientific novelty of the results: first proposed and tested method of integrating neural networks and GIS technologies for the first time using GIS and neural network technology developed set of interrelated models for solving decision support to prevent forest fires has been further developed mathematical model for classification of forest fires based on the use of Kohonen maps, which allow for correlation between data points and not interaction points and centers of clusters, which might not exist at all, improved model of spatial data that combines heorelyatsiynyy, layer-and vector- topological approach, which allows you to submit information necessary for decision-making as a set of objects that have certain properties related to certain relationships and grouped into separate layers, developed and implemented software for the information decision support to prevent forest fires. Introduced in the Scientific Research Institute of Forestry and agroforestry them. GM Vysotsky, Steppe branch crown them. VM Vinogradov and forestry Kherson region.