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Autor(en): 
  • Hao Jiang
  • Yuanyuan Zeng
  • Qimei Chen
  • Deshi Li
  • Mobile Data Mining and Applications 
     

    (Buch)
    Dieser Artikel gilt, aufgrund seiner Grösse, beim Versand als 3 Artikel!


    Übersicht

    Auf mobile öffnen
     
    Lieferstatus:   Auf Bestellung (Lieferzeit unbekannt)
    Veröffentlichung:  Mai 2019  
    Genre:  Naturwissensch., Medizin, Technik 
     
    B / Communications engineering / telecommunications / Communications Engineering, Networks / Complex systems / Data Mining / Data Mining and Knowledge Discovery / Data-driven Science, Modeling and Theory Building / Ecological science, the Biosphere / Econophysics / Electrical Engineering / engineering / Expert systems / knowledge-based systems / Mobile & handheld device programming / Apps programming / Mobile communication systems / Mobile Computing / Social research & statistics / Sociophysics / Urban & municipal planning / Urban geography / Urban Geography / Urbanism (inc. megacities, cities, towns) / Urban Geography and Urbanism / Wireless and Mobile Communication / Wireless communication systems
    ISBN:  9783030165024 
    EAN-Code: 
    9783030165024 
    Verlag:  Springer Nature EN 
    Einband:  Gebunden  
    Sprache:  English  
    Serie:  Information Fusion and Data Science  
    Dimensionen:  H 235 mm / B 155 mm / D 19 mm 
    Gewicht:  530 gr 
    Seiten:  227 
    Illustration:  X, 227 p. 96 illus., 77 illus. in color., schwarz-weiss Illustrationen, farbige Illustrationen 
    Bewertung: Titel bewerten / Meinung schreiben
    Inhalt:
    This book focuses on mobile data and its applications in the wireless networks of the future. Several topics form the basis of discussion, from a mobile data mining platform for collecting mobile data, to mobile data processing, and mobile feature discovery. Usage of mobile data mining is addressed in the context of three applications: wireless communication optimization, applications of mobile data mining on the cellular networks of the future, and how mobile data shapes future cities.

    In the discussion of wireless communication optimization, both licensed and unlicensed spectra are exploited. Advanced topics include mobile offloading, resource sharing, user association, network selection and network coexistence. Mathematical tools, such as traditional convexappl/non-convex, stochastic processing and game theory are used to find objective solutions. Discussion of the applications of mobile data mining to cellular networks of the future includes topics such as green communication networks, 5G networks, and studies of the problems of cell zooming, power control, sleep/wake, and energy saving. The discussion of mobile data mining in the context of smart cities of the future covers applications in urban planning and environmental monitoring: the technologies of deep learning, neural networks, complex networks, and network embedded data mining. Mobile Data Mining and Applications will be of interest to wireless operators, companies, governments as well as interested end users.

      



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