Traffic Prediction Method for GEO Satellites Combining ARIMA Model and Grey Model

doi:10.1007/s12204-019-2152-9

Journal of Shanghai Jiao Tong University (Science) ›› 2020, Vol. 25 ›› Issue (1): 65-69.doi: 10.1007/s12204-019-2152-9

Traffic Prediction Method for GEO Satellites Combining ARIMA Model and Grey Model

ZHOU Jian* (周剑), YANG Qidong (杨启东), ZHANG Xiaofei (张小飞), HAN Chong (韩崇), SUN Lijuan (孙力娟)

(College of Computer; Jiangsu High Technology Research Key Laboratory for Wireless Sensor Networks, Nanjing University of Posts and Telecommunications, Nanjing 210023, China)

出版日期:2020-01-15 发布日期:2020-01-12
通讯作者: ZHOU Jian (周剑) E-mail:zhoujian@njupt.edu.cn

Traffic Prediction Method for GEO Satellites Combining ARIMA Model and Grey Model

ZHOU Jian* (周剑), YANG Qidong (杨启东), ZHANG Xiaofei (张小飞), HAN Chong (韩崇), SUN Lijuan (孙力娟)

(College of Computer; Jiangsu High Technology Research Key Laboratory for Wireless Sensor Networks, Nanjing University of Posts and Telecommunications, Nanjing 210023, China)

Online:2020-01-15 Published:2020-01-12
Contact: ZHOU Jian (周剑) E-mail:zhoujian@njupt.edu.cn

摘要/Abstract

摘要： An accurate traffic prediction on various service is of great importance to the channel resource man- agement of geostationary earth orbit (GEO) satellites. Therefore, a traffic prediction method for GEO satellites combining autoregressive integrated moving average (ARIMA) model and grey model is proposed. First, the traffic prediction methods based on ARIMA model and grey model are introduced respectively. Second, a combined model is given, in which according to the results of the historical prediction of ARIMA model and grey model, those two models are combined with di?erent weights. Third, the combined model is applied to a multi-service access and the access probability of each kind of service is calculated based on the prediction results. Finally, the simulation experiments indicate that the combined model has better prediction stability and higher average prediction accuracy than either of the separated models. Moreover, the proposed access strategy based on the combined model performs better than other similar strategies.

关键词: traffic prediction, ARIMA model, grey model, access, GEO satellites

Abstract: An accurate traffic prediction on various service is of great importance to the channel resource man- agement of geostationary earth orbit (GEO) satellites. Therefore, a traffic prediction method for GEO satellites combining autoregressive integrated moving average (ARIMA) model and grey model is proposed. First, the traffic prediction methods based on ARIMA model and grey model are introduced respectively. Second, a combined model is given, in which according to the results of the historical prediction of ARIMA model and grey model, those two models are combined with di?erent weights. Third, the combined model is applied to a multi-service access and the access probability of each kind of service is calculated based on the prediction results. Finally, the simulation experiments indicate that the combined model has better prediction stability and higher average prediction accuracy than either of the separated models. Moreover, the proposed access strategy based on the combined model performs better than other similar strategies.

Key words: traffic prediction, ARIMA model, grey model, access, GEO satellites

中图分类号:

TP 393

ZHOU Jian (周剑), YANG Qidong (杨启东), ZHANG Xiaofei (张小飞), HAN Chong (韩崇), SUN Lij. Traffic Prediction Method for GEO Satellites Combining ARIMA Model and Grey Model[J]. Journal of Shanghai Jiao Tong University (Science), 2020, 25(1): 65-69.

ZHOU Jian (周剑), YANG Qidong (杨启东), ZHANG Xiaofei (张小飞), HAN Chong (韩崇), SUN Lijuan (孙力娟). Traffic Prediction Method for GEO Satellites Combining ARIMA Model and Grey Model[J]. Journal of Shanghai Jiao Tong University (Science), 2020, 25(1): 65-69.

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Traffic Prediction Method for GEO Satellites Combining ARIMA Model and Grey Model

Traffic Prediction Method for GEO Satellites Combining ARIMA Model and Grey Model

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