Development of a system for optimizing the planning of the deployment of logging sites using the example of the Republic of Karelia

Abstract

Development of a system for optimizing the planning of the deployment of logging sites using the example of the Republic of Karelia

Kuzmin R.S., Alekseev I.V., Tumanyan M.M., Kempi E.A., Semenov R.A., Leva D.S., Rego G.E.

Incoming article date: 25.02.2025

The paper is devoted to the application of a machine learning model with reinforcement for automating the planning of the deployment of logging sites in forestry. A method for optimizing the selection of cutting areas based on the algorithm of optimization of the Proximal Policy Optimization is proposed. An information system adapted for processing forest management data in a matrix form and working with geographic information systems has been developed. The experiments conducted demonstrate the ability to find rational options for the placement of cutting areas using the proposed method. The results obtained are promising for the use of intelligent systems in the forestry industry.

Keywords: reinforcement learning, deep learning, cutting areas location, forestry, artificial intelligence, planning optimization, clear-cutting