دورية أكاديمية

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

التفاصيل البيبلوغرافية
العنوان: Development of repository of deep neural networks for the analysis of geospatial data
المؤلفون: Yamashkina, E O, Kovalenko, S M, Platonova, O V
المصدر: IOP Conference Series: Materials Science and Engineering ; volume 1047, issue 1, page 012124 ; ISSN 1757-8981 1757-899X
بيانات النشر: IOP Publishing
سنة النشر: 2021
الوصف: 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.
نوع الوثيقة: article in journal/newspaper
اللغة: unknown
DOI: 10.1088/1757-899x/1047/1/012124
DOI: 10.1088/1757-899X/1047/1/012124
DOI: 10.1088/1757-899X/1047/1/012124/pdf
الإتاحة: https://doi.org/10.1088/1757-899x/1047/1/012124Test
حقوق: http://creativecommons.org/licenses/by/3.0Test/ ; https://iopscience.iop.org/info/page/text-and-data-miningTest
رقم الانضمام: edsbas.36700075
قاعدة البيانات: BASE