Keywords: neural network, clustering, machine learning, adaptive resonance theory, fuzzy art network, gis system
STRUCTURIZATION OF ENVIRONMENTAL INFORMATION WITH APPLICATION OF GEOINFORMATION TECHNOLOGIES
UDC 004.9
DOI: 10.26102/2310-6018/2019.27.4.044
The article discusses the development of managerial decisions to improve the environment through the introduction of geographic information technologies, including methods for assessing and predicting the environmental situation based on monitoring approaches. The development of big data processing technologies has identified trends in the widespread implementation of real-time monitoring systems. In this regard, the task of monitoring natural objects is proposed to be solved as the task of determining and controlling the properties and states of a complex object in real time and actively interacting with the environment, as well as developing managerial decisions and recommendations. It is proposed to use the Fuzzy ART neural network as a mathematical apparatus for structuring environmental information, which has proven itself in real-time data processing. To visualize the received information and integrate the results of the network operation of the Fuzzy ART network into a geographic information system, it is proposed to use the Folium Python library, which is intended for graphical display of geographic data and contains all the necessary cartographic information. Using Folium, the results of the structuring of environmental data can be displayed directly on Google maps, which makes it possible to visually determine the boundaries of clusters and possible buffer zones when the map is scaled up.
Keywords: neural network, clustering, machine learning, adaptive resonance theory, fuzzy art network, gis system
For citation: Fedutinov K.A. STRUCTURIZATION OF ENVIRONMENTAL INFORMATION WITH APPLICATION OF GEOINFORMATION TECHNOLOGIES. Modeling, Optimization and Information Technology. 2019;7(4). URL: https://moit.vivt.ru/wp-content/uploads/2019/11/Fedutinov_4_19_1.pdf DOI: 10.26102/2310-6018/2019.27.4.044 (In Russ).
Published 31.12.2019