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Research on the Advanced Prediction Model of the Tunnel Geological Radar Based on Cluster Computing

Meng Wei*, Ningxin Zhang, Yuan Tong, Yu Song
Chengdu University of Technology, College of the Environment and Civil Engineering, Chengdu, Sichuan,610059
Mailing address: No. 1, East Third Road, Erxianqiao, Chenghua District, Chengdu city, Sichuan Province
* Corresponding Author: Meng Wei,

Intelligent Automation & Soft Computing 2020, 26(3), 597-607. https://doi.org/10.32604/iasc.2020.013938

Abstract

The traditional radar signal detection mode of the analog digital converter (ADC) has a low prediction efficiency. Therefore, the advanced prediction model of the tunnel geological radar based on the cluster computing was designed. The completeness factor of the detection radar signal was calculated by the computer cluster effect, and then the information extraction and information integration of the radar pulse for the radar detection signal was determined. Moreover, the multi-order nonlinear regression forecasting model restructured the received signal. Thus, the prediction of the radar detection signal was achieved. In order to ensure the effectiveness of the design, the simulation experiment was carried out. Experimental results show that the ahead prediction model of the geological radar is 25% higher than that of the traditional model, which proves the effectiveness of the designed prediction model.

Keywords

Advanced prediction; cluster computing; computer technology; continuous wave radar; tunnel engineering; geological survey; pulse radar.

Cite This Article

M. Wei, N. Zhang, Y. Tong and Y. Song, "Research on the advanced prediction model of the tunnel geological radar based on cluster computing," Intelligent Automation & Soft Computing, vol. 26, no.3, pp. 597–607, 2020.

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This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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