Intelligent automation system of the railway company's purchasing activity based on artificial neural networks : доклад, тезисы доклада

Gek D.K.; Kukartsev V.V.; Markevich I.V.; Shalaeva D. S.; Yadrov A. S.; Rogova D.V.

Дополнительные ссылки: eLibrary · Источник статьи

База данных: Каталог библиотеки СФУ

Библиографическое описание: Intelligent automation system of the railway company's purchasing activity based on artificial neural networks : доклад, тезисы доклада / D. K. Gek [et al.]. - [S. l. : s. n.], 2020. - Текст : непосредственный // IOP Conference Series: Materials Science and Engineering : The 2020 International Conference on Transport and Infrastructure of the Siberian Region (SibTrans 2020) / International Conference on Transport and Infrastructure of the Siberian Region (2020 ; 11.11 - 13.11 ; Irkutsk) : IOP Publishing Ltd, 2020. - 1151. - P. 012042-012042.

Аннотация: A person is responsible for quality control of the purchase forecast of commercial enterprises, which entails a number of certain consequences. In this regard, we decided to create an intelligent system that will determine the quality of the forecast. Such a system will be a human assistant in deciding on the quality of the forecast. The system will also be able, if necessary, to indicate the necessary adjustments for its forecasting method. As part of this work, a software product will be created that will determine the quality of the created trade procurement plan, and, if necessary, help the user adjust the forecasting method used by the outlet. The aim of the work is to create an intelligent procurement system that will generate its forecast using a neural network, and then determine the forecast error using XYZ analysis.

Год издания: 2020

Авторы: Gek D.K. , Kukartsev V.V. , Markevich I.V. , Shalaeva D. S. , Yadrov A. S. , Rogova D.V.

Издательство: IOP Publishing Ltd

Источник: IOP Conference Series: Materials Science and Engineering

Выпуск: 1151

Мероприятие: International Conference on Transport and Infrastructure of the Siberian Region (Irkutsk, 2020 ; 11.11 - 13.11)

Номера страниц: 012042-012042

Держатель оригинала документа: Reshetnev Siberian State University of Science and Technology, Siberian Federal University

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