High speed maglev wireless transmission environment has obvious characteristic, high-speed maglev train fast moving makes the high-speed maglev wireless channel show reveal the characteristics of rapid change, high-speed maglev train large capacity public wireless communication system is complex, low noise high electric locomotive’s own environment makes the research of high-speed maglev wireless channel challenges, especially the tendency of the wireless channel is difficult to analyze Autoregressive Integrated Moving Average Model (ARIMA) is one of the time sequence analysis models commonly used in data mining. Its goal is to predict future unknown number values through known time series. This paper mainly analyzes the time domain data of high-speed maglev wireless channel measured on site based on ARIMA time sequence analysis model. The mean absolute error and root mean square error are 4.4227 and 5.6112 respectively.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Time-domain Data Analysis of Maglev System EMI Based on ARIMA Model


    Contributors:
    Wu, Donghua (author) / Zhang, Jinbao (author)


    Publication date :

    2021-12-10


    Size :

    433994 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English




    Maglev track and maglev system

    ZHOU FAZHU / YANG JIE / GONG HONGJUN et al. | European Patent Office | 2021

    Free access

    Suspension guide driving system, maglev train and maglev system

    CHEN YIN / DENG YUNCHUAN / WANG MINGFEI et al. | European Patent Office | 2021

    Free access

    Short-time traffic flow prediction with ARIMA-GARCH model

    Chenyi Chen, / Jianming Hu, / Qiang Meng, et al. | IEEE | 2011


    Superconductive Maglev system on the Yamanashi Maglev test line

    Tsuruga,H. / Central Japan Railway,JP | Automotive engineering | 1992