60845

Автор(ы): 

Автор(ов): 

3

Параметры публикации

Тип публикации: 

Тезисы доклада

Название: 

Comparative analysis of recurrent neural networks for natural gas quality analysis

Электронная публикация: 

Да

Наименование конференции: 

  • 6th International Reliability and Safety Engineering Conference (Shiraz, Iran, 2021)

Наименование источника: 

  • Abstract book of 6th International Reliability and Safety Engineering Conference (Shiraz, Iran, 2021)

Город: 

  • Shiraz, Iran

Издательство: 

  • Shiraz University

Год издания: 

2021

Страницы: 

152-152
Аннотация
The correlation methods are developed for real time natural gas quality analysis. Various statistical models are often used in correlation methods due to the impossibility or high complexity of solving the problems with traditional methods. The choice of a model for the problem under discussion is mostly made by heuristic methods due to the lack of a general algorithm for choosing a model and a variety of both statistical models and architectures of specific models. This paper provides a comparative analysis of the main models that are used to solve the task of natural gas composition analysis. Based on this analysis, the conclusions are drawn about a specific model that is most appropriate to apply to existing data.

Библиографическая ссылка: 

Брокарев И.А., Фархадов М.П., Васьковский С.В. Comparative analysis of recurrent neural networks for natural gas quality analysis / Abstract book of 6th International Reliability and Safety Engineering Conference (Shiraz, Iran, 2021). Shiraz, Iran: Shiraz University, 2021. С. 152-152.