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Abstract <p>The results of the development and application of an information system for identifying and forecasting current and potential trend technologies in industry are presented. The system is based on early detection of technologies, including the analysis of big data from three key sources (scientific publications, patents, and reports from leading research centers). Trend extrapolation methods, time series analysis, and S-curve technology lifecycle modeling are used for forecasting.</p>

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Architectural Solutions and Design Models for a System of Intelligent Forecasting and Assessment of Promising Technologies in Industry

  • 期刊论文

  • 发表日期：

    2025年7月1日

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  • R. A. Nezhmetdinov,
  • I. A. Kovalev,
  • M. A. Charuiskaya,
  • A. S. Kryzhanovskaya

摘要

Abstract

The results of the development and application of an information system for identifying and forecasting current and potential trend technologies in industry are presented. The system is based on early detection of technologies, including the analysis of big data from three key sources (scientific publications, patents, and reports from leading research centers). Trend extrapolation methods, time series analysis, and S-curve technology lifecycle modeling are used for forecasting.