图 书 馆
基于回归自动机的短期时间序列预测Short-term Time Series Forecasting with Regression Automata |
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| 课程网址: | https://videolectures.net/videos/kdd2016_chenal_regression_automa... |
| 主讲教师: | Massimo Chenal |
| 开课单位: | KDD 2016研讨会 |
| 开课时间: | 2025-02-04 |
| 课程语种: | 英语 |
| 中文简介: |  |
| 课程简介: | We present regression automata (RA), which are novel type syntactic models for time series forecasting. Building on top of conventional state-merging algorithms for identifying automata, RA use numeric data in addition to symbolic values and make predictions based on this data in a regression fashion. We apply our model to the problem of hourly wind speed and wind power forecasting. Our results show that RA outperform other state-of-the-art approaches for predicting both wind speed and power generation. In both cases, short-term predictions are used for resource allocation and infrastructure load balancing. For those critical tasks, the ability to inspect and interpret the generative model RA provide is an additional benefit. |
| 关 键 词: | 回归自动机; 时间序列; 数值数据 |
| 课程来源: | 视频讲座网 |
| 数据采集: | 2025-04-06：liyq |
| 最后编审: | 2025-04-06：liyq |
| 阅读次数: | 7 |