43011

Автор(ы): 

Автор(ов): 

3

Параметры публикации

Тип публикации: 

Доклад

Название: 

Inverse Sets in Big Data Processing

ISBN/ISSN: 

978-1-5386-0500-4

Наименование конференции: 

  • 11th IEEE International Conference on Application of Information and Communication Technologies (AICT2017, Moscow)

Наименование источника: 

  • Proceedings of the 11th IEEE International Conference on Application of Information and Communication Technologies (AICT2017, Moscow)

Обозначение и номер тома: 

Vol. 1

Город: 

  • Москва

Издательство: 

  • IEEE

Год издания: 

2017

Страницы: 

40-43
Аннотация
Inverse sets [1] defined in 2011 and, independently, in [2] (2012) provide a concise mathematical description of indexing methods that deal efficiently with vast amounts of data. On the other hand, traditional, non-indexing machine learning methods are far more computationally demanding. For instance, aircraft engine prediction maintenance needs analyzing statistical records of hundreds of operational cycles of thousands of engines - a processing, which takes Microsoft’s cloud technologies and unspecified machine learning time. However, it was found that inverse sets-based approaches require only a PC or a smartphone platform providing practically instantaneous learning and prediction time.

Библиографическая ссылка: 

Михайлов А.М., Каравай М.Ф., Фархадов М.П. Inverse Sets in Big Data Processing / Proceedings of the 11th IEEE International Conference on Application of Information and Communication Technologies (AICT2017, Moscow). М.: IEEE, 2017. Vol. 1. С. 40-43.