Development of repository of deep neural networks for the analysis of geospatial data

• Published in: IOP conference series. Materials Science and Engineering Vol. 1047; no. 1; pp. 12124 - 12128
• Main Authors: Yamashkina, E O, Kovalenko, S M, Platonova, O V
• Format: Journal Article
• Language: English
• Published: Bristol IOP Publishing 01.02.2021
• Subjects: Algorithms; Artificial neural networks; Learning theory; Machine learning; Neural networks; Repositories; Spatial data; Storage containers
• ISSN: 1757-8981; 1757-899X
• DOI: 10.1088/1757-899X/1047/1/012124

The article proposes a solution for organizing a storage of artificial neural networks in a digital spatial data infrastructure system. Based on the analysis of world experience, a register of key storage cases was created, which made it possible to create an effective solution for analyzing large arrays of spatial data. The structure of the neural network sets the format of the input data and the type of the output signal. It is shown that the use of neural networks for solving design problems requires dividing the storage of the ontological model into machine learning, data and task modules. The introduction of deep learning models into the repository will allow not only to form an ANN system capable of solving urgent problems in the field of analysis of different types of big data, but also to solve the problem of choosing an effective model by building a system of recommendations that optimize the choice of algorithms.