Short-term Cloud Coverage Prediction Using the ARIMA Time Series Model | |
Wang Y(王钰); Wang CH(王春恒); Shi CZ(史存召); Xiao BH(肖柏华) | |
刊名 | Remote Sensing Letters |
2018 | |
期号 | 3页码:275-284 |
关键词 | Cloud Coverage Arima Time Series Model |
英文摘要 | In view of the important role of cloud coverage on the solar (energy) irradiance, the total cloud coverage prediction based on ground-based cloud images is studied in this paper. In traditional prediction techniques, the correlation between cloud coverage over continue time is always neglected. Thus, an autoregressive integrated moving average (ARIMA) time series model is used to predict the short-term cloud coverage. Experimental results on a collected time series database of cloud coverage computed from ground-based cloud images show that the correlation information of time series is useful for cloud coverage prediction. Additionally, the ARIMA model gains a superior prediction performance for forecasts of one minute or longer 20 and 30 minutes. We are able to predict the cloud coverage with an approximate error of 5%, 7%, and 9% for 1, 5, and 20 and 30 minute forecasts, respectively. Furthermore, we found that there are different error rates of predictions for different cloud coverage intervals. High cloud coverage always suffers from a higher error rate. |
内容类型 | 期刊论文 |
源URL | [http://ir.ia.ac.cn/handle/173211/23637] |
专题 | 自动化研究所_复杂系统管理与控制国家重点实验室_影像分析与机器视觉团队 |
推荐引用方式 GB/T 7714 | Wang Y,Wang CH,Shi CZ,et al. Short-term Cloud Coverage Prediction Using the ARIMA Time Series Model[J]. Remote Sensing Letters,2018(3):275-284. |
APA | Wang Y,Wang CH,Shi CZ,&Xiao BH.(2018).Short-term Cloud Coverage Prediction Using the ARIMA Time Series Model.Remote Sensing Letters(3),275-284. |
MLA | Wang Y,et al."Short-term Cloud Coverage Prediction Using the ARIMA Time Series Model".Remote Sensing Letters .3(2018):275-284. |
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