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An Investigation of Research Activities in Intelligent Data Processing Using Data Envelopment Analysisстатья
Информация о цитировании статьи получена из
Scopus
Дата последнего поиска статьи во внешних источниках: 4 марта 2022 г.
- Авторы: Lychev Andrey V., Rozhnov Aleksei V., Lobanov Igor A.
- Сборник: Computer Vision in Control Systems—6
- Год издания: 2020
- Издательство: Springer International Publishing AG
- Местоположение издательства: Cham, Switzerland
- Первая страница: 127
- Последняя страница: 139
- DOI: 10.1007/978-3-030-39177-5_10
- Аннотация: The report implements a vision of intelligent data processing task and elaboration of the efficiency evaluation using data envelopment analysis in discussions on the problem investigations of advanced technology precursors. Data processing aspect of a collaboration of intellectual processes from the standpoint of pervasive informatics is presented. The target setting 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, and innovative potential of distributed computer vision and collaborative innovation network. The representations of hybrid optimization modeling and control of intelligent transport systems are of interest in the modern conditions of rapid development of artificial neural networks, cognitive and other intelligent data processing technologies. In this regard, interdisciplinary research is directly aimed at the implementation of effective commons-based peer production of the geosocial networking in the transition to digital, intelligent production technologies, new materials, by creating original tools of data envelopment analysis (free disposal hull) for search, collection, storage and processing of pertinent information resources, in particular together object-based image analysis. A convergence of professional, scientific and educational network communities and prerequisites for its implementation at research activities are discussed. Primarily, the short description of data envelopment analysis is presented and followed by the overview of integration components which use the distributed computer and telecommunication networks. Hereinafter, we investigate the opportunities of intelligent data processing in object-based image analysis for location-based social networks. Presented hybrid optimization modeling framework is used at experimental studies.
- Добавил в систему: Рожнов Алексей Владимирович