Chuzo Ninagawa – författare

This book focuses on building air conditioning demand response and power storage batteries as the resources that make up the virtual power plant.

This book focuses on building air conditioning demand response and power storage batteries as the resources that make up the virtual power plant.

This book deals with analysis techniques for TCP, UDP, Web, and SOAP data transmission performance on the IoT cloud side, CSMA-type, and multi-hop data transmission performance on the IoT edge side, as well as gateway receives buffer and transmit packet assembly data transmission performance.As mathematical tools for the analysis of communication performance, universal analysis methods such as stochastic processes, queues, Markov processes, and communication traffic simulators are applied to actual examples, and their usage is described in detail. This book aims to provide lifelong skills for analyzing communication performance that will serve as the basis for the future evolution of the IoT.

This book deals with analysis techniques for TCP, UDP, Web, and SOAP data transmission performance on the IoT cloud side, CSMA-type, and multi-hop data transmission performance on the IoT edge side, as well as gateway receives buffer and transmit packet assembly data transmission performance.As mathematical tools for the analysis of communication performance, universal analysis methods such as stochastic processes, queues, Markov processes, and communication traffic simulators are applied to actual examples, and their usage is described in detail. This book aims to provide lifelong skills for analyzing communication performance that will serve as the basis for the future evolution of the IoT.

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.

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.

This book describes new energy service controls of VRF (Variable Refrigerant Flow) air-conditioners, i.e., distributed-type air-conditioners for commercial buildings in the near future, in the context of the energy savings for CO2 reduction and the reform of the electric power system.