55698

Автор(ы): 

Автор(ов): 

3

Параметры публикации

Тип публикации: 

Статья в журнале/сборнике

Название: 

Hybrid Optimization Modeling Framework for Research Activities in Intelligent Data Processing

ISBN/ISSN: 

978-3-030-39176-8 / 978-3-030-39177-5 (eBook)

DOI: 

doi.org/10.1007/978-3-030-39177-5_11

Наименование источника: 

  • Intelligent Systems Reference Library

Обозначение и номер тома: 

Volume 182, Computer Vision in Control Systems—6: Advances in Practical Applications

Город: 

  • Cham, Switzerland

Издательство: 

  • Springer Nature Switzerland AG

Год издания: 

2020

Страницы: 

141-152
Аннотация
The chapter continues our investigation of the problem investigations of advanced technology precursors from the point of view of the formation of intelligent transportation systems. The problem statement corresponds to an initiative focused on a comprehensive discussion of geosocial networking formation issues and assessment of the quality of intelligent data processing based on conceptual models of integration advanced technology of computer vision and location-based social networks. In this regard, interdisciplinary research and development of modifiable vehicles include the need to solved particular tasks of the system integration, optimization modeling, and control. Based on investigation of geosocial networking using data envelopment analysis, our discussion is directly aimed at the implementation of effective commons-based peer production of the geosocial networking in the progressive movement of pervasive informatics. This provides by creating the original tools of data envelopment analysis for search, collection, storage, and processing of pertinent information resources in modern conditions of rapid development of artificial neural networks, cognitive and other intelligent data processing technologies, in particular together object-based image analysis. The chapter provides the opportunities of intelligent data processing in object-based image analysis for location-based social networks. Proposed hybrid optimization modeling framework and experimental studies scenarios are discussed.

Библиографическая ссылка: 

Рожнов А.В., Лычёв А.В., Лобанов И.А. Hybrid Optimization Modeling Framework for Research Activities in Intelligent Data Processing // Intelligent Systems Reference Library. 2020. Volume 182, Computer Vision in Control Systems—6: Advances in Practical Applications. С. 141-152.