| 期刊全稱 | AI Time Series Control System Modelling | | 影響因子2023 | Chuzo Ninagawa | | 視頻video | http://file.papertrans.cn/143/142794/142794.mp4 | | 發(fā)行地址 | Covers theoretical basics and practical examples of machine learning modelling.Explains how to build control models from time-series data using machine learning.Manipulates the system to achieve the d | | 圖書封面 |  | | 影響因子 | This book describes the practical application of artificial intelligence (AI) methods using time series data in system control. This book consistently discusses the application of machine learning to the analysis and modelling of time series data of physical quantities to be controlled in the field of system control..Since dynamic systems are not stable steady states but changing transient states, the changing transient states depend on the state history before the change. In other words, it is essential to predict the change from the present to the future based on the time history of each variable in the target system, and to manipulate the system to achieve the desired change.?.In short, time series is the key to the application of AI machine learning to system control. This is the philosophy of this book: "time series data" + "AI machine learning" = "new practical control methods"..This book can give my helps to undergradate or graduate students, institute researchers and senior engineers whose scientific background are engineering, mathematics, physics and other natural sciences.. . | | Pindex | Book 2023 |
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