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AI time series control system modelling

Ninagawa, Chuzo.

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AI time series control system modelling

Record Type:	Electronic resources : Monograph/item
Title/Author:	AI time series control system modelling/ by Chuzo Ninagawa.
Author:	Ninagawa, Chuzo.
Published:	Singapore :Springer Nature Singapore : : 2023.,
Description:	xi, 237 p. :ill. (some col.), digital ;24 cm.
[NT 15003449]:	Introduction -- Linear Time Series Modeling -- Deep Learning AI Modeling -- LSTM AI Modeling -- Optimal Control by Time-Series AI Model -- The Reality of Time Series Learning Data Collection -- Practical Work on Time Series AI Modeling.
Contained By:	Springer Nature eBook
Subject:	Intelligent control systems. -
Online resource:	https://doi.org/10.1007/978-981-19-4594-6
ISBN:	9789811945946

AI time series control system modelling
Ninagawa, Chuzo.

AI time series control system modelling[electronic resource] /by Chuzo Ninagawa. - Singapore :Springer Nature Singapore :2023. - xi, 237 p. :ill. (some col.), digital ;24 cm.

Introduction -- Linear Time Series Modeling -- Deep Learning AI Modeling -- LSTM AI Modeling -- Optimal Control by Time-Series AI Model -- The Reality of Time Series Learning Data Collection -- Practical Work on Time Series AI Modeling.

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.

ISBN: 9789811945946

Standard No.: 10.1007/978-981-19-4594-6doiSubjects--Topical Terms:

546464
Intelligent control systems.

LC Class. No.: TJ217.5

Dewey Class. No.: 629.89015118

AI time series control system modelling
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100 1 $a Ninagawa, Chuzo. $3 3589886
245 1 0 $a AI time series control system modelling $h [electronic resource] / $c by Chuzo Ninagawa.
260 $a Singapore : $b Springer Nature Singapore : $b Imprint: Springer, $c 2023.
300 $a xi, 237 p. : $b ill. (some col.), digital ; $c 24 cm.
505 0 $a Introduction -- Linear Time Series Modeling -- Deep Learning AI Modeling -- LSTM AI Modeling -- Optimal Control by Time-Series AI Model -- The Reality of Time Series Learning Data Collection -- Practical Work on Time Series AI Modeling.
520 $a 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.
650 0 $a Intelligent control systems. $3 546464
650 0 $a Time-series analysis. $3 532530
650 0 $a Artificial intelligence. $3 516317
650 0 $a Intelligent control systems $x Mathematical models. $3 2134993
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856 4 0 $u https://doi.org/10.1007/978-981-19-4594-6
950 $a Intelligent Technologies and Robotics (SpringerNature-42732)