C-Cast: A Real-Time Forecasting Model for a Controlled Sequence
C-Cast: A Real-Time Forecasting Model for a Controlled Sequence
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C-Cast：受控序列的实时预测模型
DOI：
10.1145/3511808.3557817
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发表时间：
2022
期刊：
影响因子：
--
通讯作者：
Yasushi Sakurai
中科院分区：
文献类型：
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作者：
Ren Fujiwara;Yasuko Matsubara;Tasuku Kimura;Yasushi Sakurai
预测控制是一种先进的控制方法，在工业控制中得到了成功的应用。预测控制最基本的需求之一是使用由多个属性（被操纵变量和操作信号）组成的外生序列准确预测“受控序列”。给定受控序列和外生序列，我们如何有效地预测受控序列的未来行为？本文提出了一种利用外生序列预测时间演化控制序列的有效方法——C-Cast。我们提出的方法具有以下特点：(a)自适应：它在一个时间演变的控制序列中捕捉重要的时间演变模式和操作变化；(b)有效：它执行准确的预测。(c)实用性：它使实时控制序列预测足够快，以满足预测控制所需的限制。在真实数据集上进行的大量实验表明，C-Cast在准确性方面始终优于现有最先进的方法，并且执行速度足够快。
Predictive control is an advanced control method that is used successfully in industrial control applications. One of the most fundamental demands for predictive control is the accurate forecasting of a ''controlled sequence" using exogenous sequences which consist of multiple attributes (manipulated variables and operation signals). Given a controlled sequence and exogenous sequences, how can we effectively forecast the future behavior of a controlled sequence? In this paper, we present C-Cast, an efficient and effective method for forecasting a time-evolving controlled sequence with exogenous sequences. Our proposed method has the following properties: (a) Adaptive: it captures important time-evolving patterns and operation shift in a time-evolving controlled sequence (b) Effective: it performs accurate forecasting. (c) Practical: it enables real-time controlled sequence forecasting fast enough to satisfy the limitation required for predictive control. Extensive experiments on a real dataset demonstrate that C-Cast consistently outperforms the best existing state-of-the-art methods as regards accuracy, and the execution speed is sufficiently fast.
影响因子：
2.5
作者：
Li, Lei;Prakash, B. Aditya;Faloutsos, Christos
通讯作者：
Faloutsos, Christos
可解释的多项式神经常微分方程。
DOI：
10.1063/5.0130803
发表时间：
2023
期刊：
Chaos (Woodbury, N.Y.)
影响因子：
--
作者：
Fronk,Colby;Petzold,Linda
通讯作者：
Petzold,Linda