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.
Time-domain Data Analysis of Maglev System EMI Based on ARIMA Model
10.12.2021
433994 byte
Aufsatz (Konferenz)
Elektronische Ressource
Englisch
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