Predicting multivariate time series in real time with confidence intervals: Applications to renewable energy

被引：0
|
作者：
Yoshito Hirata
Kazuyuki Aihara
Hideyuki Suzuki
机构：
[1] Institute of Industrial Science,Department of Mathematical Informatics
[2] The University of Tokyo,undefined
[3] Graduate School of Information Science and Technology,undefined
[4] The University of Tokyo,undefined
[5] CREST,undefined
[6] JST,undefined
来源：
The European Physical Journal Special Topics | 2014年 / 223卷
关键词：
Prediction Error; Wind Turbine; European Physical Journal Special Topic; Japan Meteorological Agency; Multivariate Time Series;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
We extend our earlier work on predicting a univariate time series in real time with confidence intervals (Hirata, et al., Renew. Energy 67, 35 (2014)) to a multivariate time series. We realize this extension by using the “p-norm” where p is smaller than 1. We compare the performance when p is 0.5 with that when p is 2 using solar irradiation data and wind data measured all over Japan.
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页码：2451 / 2460
页数：9
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