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Path loss prediction in urban environment using learning machines and dimensionality reduction techniques

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  • M. Piacentini
  • F. Rinaldi

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  • M. Piacentini & F. Rinaldi, 2011. "Path loss prediction in urban environment using learning machines and dimensionality reduction techniques," Computational Management Science, Springer, vol. 8(4), pages 371-385, November.
    • Handle: RePEc:spr:comgts:v:8:y:2011:i:4:p:371-385
    DOI: 10.1007/s10287-010-0121-8
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    References listed on IDEAS

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    1. Lembke B., 1918. "√ a. p," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 111(1), pages 709-712, February.
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    Cited by:

    1. Alberto Mozo & Bruno Ordozgoiti & Sandra Gómez-Canaval, 2018. "Forecasting short-term data center network traffic load with convolutional neural networks," PLOS ONE, Public Library of Science, vol. 13(2), pages 1-31, February.
    2. Okiemute Roberts Omasheye & Samuel Azi & Joseph Isabona & Agbotiname Lucky Imoize & Chun-Ta Li & Cheng-Chi Lee, 2022. "Joint Random Forest and Particle Swarm Optimization for Predictive Pathloss Modeling of Wireless Signals from Cellular Networks," Future Internet, MDPI, vol. 14(12), pages 1-26, December.

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