Neural Network Modeling and Assessment of the Territorial Situation

• Published in: IEEE NW Russia Young Researchers in Electrical and Electronic Engineering Conference pp. 514 - 517
• Main Authors: Zinchenko, Elena G., Bidenko, Sergey I., Khramov, Igor S., Minakov, Vladimir F., Dytlov, Sergey A., Ivanovskii, Aleksei N.
• Format: Conference Proceeding
• Language: English
• Published: IEEE 25.01.2022
• Subjects: Analytical models; artificial neural network; Artificial neural networks; Backpropagation algorithms; Economics; Learning systems; Multilayer perceptrons; neural network model; Recurrent neural networks; spatial analysis; territorial economic situation; topological image of the geo-image of the economic situation
• ISSN: 2376-6565
• DOI: 10.1109/ElConRus54750.2022.9755500

The technologies of using the apparatus of an artificial neural network in a new subject area - procedures for spatial assessment of the rapidly changing situation in the region are considered. The tasks of neural network modeling of a complex dynamic territorial structure - a regional situation are formulated. The technologies for the formalized representation of the territorial situation in the region for spatial analysis using the apparatus of artificial neural networks have been determined. The order of formation of parameters and the range of output estimates are established. As a basic structure of a neural network, a recurrent neural network with a multilayer perceptron architecture is proposed. A neural network learning mechanism is substantiated in the form of an error backpropagation algorithm, which is optimal for the classification problem using a recurrent neural network.