Autors: Cooklev, T., Poulkov, V. K., Bennett, D., Tonchev, K.
Title: Enabling RF data analytics services and applications via cloudification
Keywords: Radio frequency; Cloud computing; Metadata; Data analysis; Wireless communication; Computer architecture; Monitoring

Abstract: Data analytics is related to extracting information from observations, measurements, or experiments about a phenomenon or subject of interest for different purposes, such as interpretation of the data, decision making, diagnosis, and prediction [1]. A classification of the entire field of big data analytics is difficult to make and can be based on a variety of criteria. One classification related to the depth of the analysis is presented by Blackett [2], identifying three levels: descriptive, predictive, and prescriptive analytics. Descriptive analytics uses past data to analyze what has occurred, while predictive analytics focuses on forecasting future trends and determining probabilities of occurrence mainly through the application of different statistical techniques or data mining algorithms for pattern extraction. Prescriptive analytics facilitates decision making and optimization of complex systems.



    IEEE Aerospace and Electronic Systems Magazine, vol. 33, issue 5, pp. 44-55, 2018, United States, IEEE, DOI 10.1109/MAES.2018.170108

    Copyright IEEE

    Цитирания (Citation/s):
    1. Khan, Z., Lehtomaki, J., Ganewattha, C., Shahabuddin, S., "Histograms to quantify dataset shift for spectrum data analytics: A SoC based device perspective", 2nd 6G Wireless Summit 2020: Gain Edge for the 6G Era, 6G SUMMIT 2020, 2020, DOI: 10.1109/6GSUMMIT49458.2020.9083875. - 2020 - в издания, индексирани в Scopus или Web of Science

    Вид: статия в списание, публикация в издание с импакт фактор, публикация в реферирано издание, индексирана в Scopus и Web of Science