Автор: Yuanzheng Li, Yong Zhao Название: Artificial Intelligence Enabled Computational Methods for Smart Grid Forecast and Dispatch ISBN: 9819907985 ISBN-13(EAN): 9789819907984 Издательство: Springer Рейтинг: Цена: 149060.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: With the increasing penetration of renewable energy and distributed energy resources, smart grid is facing great challenges, which could be divided into two categories. On the one hand, the endogenous uncertainties of renewable energy and electricity load lead to great difficulties in smart grid forecast. On the other hand, massive electric devices as well as their complex constraint relationships bring about significant difficulties in smart grid dispatch. Owe to the rapid development of artificial intelligence in recent years, several artificial intelligence enabled computational methods have been successfully applied in the smart grid and achieved good performances. Therefore, this book is concerned with the research on the key issues of artificial intelligence enabled computational methods for smart grid forecast and dispatch, which consist of three main parts. (1) Introduction for smart grid forecast and dispatch, in inclusion of reviewing previous contribution of various research methods as well as their drawbacks to analyze characteristics of smart grid forecast and dispatch. (2) Artificial intelligence enabled computational methods for smart grid forecast problems, which are devoted to present the recent approaches of deep learning and machine learning as well as their successful applications in smart grid forecast. (3) Artificial intelligence enabled computational methods for smart grid dispatch problems, consisting of edge-cutting intelligent decision-making approaches, which help determine the optimal solution of smart grid dispatch. The book is useful for university researchers, engineers, and graduate students in electrical engineering and computer science who wish to learn the core principles, methods, algorithms, and applications of artificial intelligence enabled computational methods.
Автор: Viola Название: Digital-Twin-Enabled Smart Control Engineering ISBN: 3031221397 ISBN-13(EAN): 9783031221392 Издательство: Springer Рейтинг: Цена: 46570.00 T Наличие на складе: Поставка под заказ. Описание: This book presents a novel design framework for the development of Digital Twin (DT) models for process- and motion-control applications. It is based on system-data acquisition using cutting-edge computing technologies, modelling of physical-system behavior through detailed simultaneous simulation of different aspects of the system, and optimal dynamic behavior-matching of the process. The design framework is enhanced with real-time data analytics to improve the performance of the DT’s behavior-matching with the real system or physical twin. The methods of creating a DT detailed in Digital-Twin-Enabled Smart Control Engineering make possible the study of a system for real-time controller tuning and fault detection. They also facilitate life-cycle analysis for multiple critical and dangerous conditions that cannot be explored in the corresponding real system or physical twin. The authors show how a DT can be exploited to enable self-optimizing capabilities in feedback control systems. The DT framework and the control-performance assessment, fault diagnosis and prognosis, remaining-useful-life analysis, and self-optimizing control abilities it allows are validated with both process- and motion-control systems and their DTs. Supporting MATLAB-based material for a case study and an expanded introduction to the basic elements of DTs can be accessed on an associated website. This book helps university researchers from many areas of engineering to develop new tools for control design and reliability and life-cycle assessment and helps practicing engineers working with robotic, manufacturing and processing, and mechatronic systems to maintain and develop the mechanical tools they use.
Автор: Anil Saroliya et al. Название: Internet of things and fog computing-enabled solutions for real-life challenges ISBN: 1032136316 ISBN-13(EAN): 9781032136318 Издательство: Taylor&Francis Рейтинг: Цена: 100030.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book comprehensively covers smart technologies and their applications that will help during emergency situations in a single volume. It is an ideal text for graduate students, and academic researchers working in diverse engineering fields of electrical, biomedical, electronics and communication, and computer.
Автор: Karimipour Hadis, Derakhshan Farnaz Название: Ai-Enabled Threat Detection and Security Analysis for Industrial Iot ISBN: 3030766128 ISBN-13(EAN): 9783030766122 Издательство: Springer Рейтинг: Цена: 149060.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Artificial Intelligence for Threat Detection and Analysis in Industrial IoT: Applications and Challenges.- Complementing IIoT Services through AI: Feasibility and Suitability.- Data Security and Privacy in Industrial IoT.- Blockchain Applications in the Industrial Internet of Things.- Application of Deep Learning on IoT-enabled Smart Grid Monitoring.- Cyber Security of Smart Manufacturing Execution Systems: A Bibliometric Analysis.- The Role of Machine Learning in IIoT Through FPGAs.- Deep Representation Learning for Cyber-Attack Detection in Industrial IoT.- Classification and Intelligent Mining of Anomalies in Industrial IoT.- A Snapshot Ensemble Deep Neural Network Model for Attack Detection in Industrial Internet of Things.- Privacy Preserving Federated Learning Solution for Security of Industrial Cyber Physical Systems.- A Multi-Stage Machine Learning Model for Security Analysis in Industrial Control System.- A Recurrent Attention Model for Cyber Attack Classification.
Powertrain electrification, fuel decarburization, and energy diversification are techniques that are spreading all over the world, leading to cleaner and more efficient vehicles.
Hybrid electric vehicles (HEVs) are considered a promising technology today to address growing air pollution and energy deprivation. To realize these gains and still maintain good performance, it is critical for HEVs to have sophisticated energy management systems. Supervised by such a system, HEVs could operate in different modes, such as full electric mode and power split mode. Hence, researching and constructing advanced energy management strategies (EMSs) is important for HEVs performance. There are a few books about rule- and optimization-based approaches for formulating energy management systems. Most of them concern traditional techniques and their efforts focus on searching for optimal control policies offline. There is still much room to introduce learning-enabled energy management systems founded in artificial intelligence and their real-time evaluation and application.
In this book, a series hybrid electric vehicle was considered as the powertrain model, to describe and analyze a reinforcement learning (RL)-enabled intelligent energy management system. The proposed system can not only integrate predictive road information but also achieve online learning and updating. Detailed powertrain modeling, predictive algorithms, and online updating technology are involved, and evaluation and verification of the presented energy management system is conducted and executed.
Powertrain electrification, fuel decarburization, and energy diversification are techniques that are spreading all over the world, leading to cleaner and more efficient vehicles.
Hybrid electric vehicles (HEVs) are considered a promising technology today to address growing air pollution and energy deprivation. To realize these gains and still maintain good performance, it is critical for HEVs to have sophisticated energy management systems. Supervised by such a system, HEVs could operate in different modes, such as full electric mode and power split mode. Hence, researching and constructing advanced energy management strategies (EMSs) is important for HEVs performance. There are a few books about rule- and optimization-based approaches for formulating energy management systems. Most of them concern traditional techniques and their efforts focus on searching for optimal control policies offline. There is still much room to introduce learning-enabled energy management systems founded in artificial intelligence and their real-time evaluation and application.
In this book, a series hybrid electric vehicle was considered as the powertrain model, to describe and analyze a reinforcement learning (RL)-enabled intelligent energy management system. The proposed system can not only integrate predictive road information but also achieve online learning and updating. Detailed powertrain modeling, predictive algorithms, and online updating technology are involved, and evaluation and verification of the presented energy management system is conducted and executed.
Автор: Al-Turjman, Fadi Название: Artificial Intelligence of Health-Enabled Spaces ISBN: 1032345802 ISBN-13(EAN): 9781032345802 Издательство: Taylor&Francis Рейтинг: Цена: 112290.00 T Наличие на складе: Есть у поставщика Поставка под заказ.
Автор: Al-Turjman, Fadi Название: Smart-Grid in IoT-enabled Spaces ISBN: 0367517884 ISBN-13(EAN): 9780367517885 Издательство: Taylor&Francis Рейтинг: Цена: 102080.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: In this book, we consider the most significant and emergent research topics in this domain, addressing major issues and challenges in IoT-based solutions proposed for the smart grid. The chapters provide insight on comprehensive topics in IoT-based smart grid, combining technical aspects with the most up to date theory.
Автор: Bhattacharyya Siddhartha, Dutta Paramartha, Datta Kakali Название: Intelligence Enabled Research: Dosier 2020 ISBN: 9811592896 ISBN-13(EAN): 9789811592898 Издательство: Springer Цена: 93160.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book gathers extended versions of papers presented at DoSIER 2020 (the Second Doctoral Symposium on Intelligence Enabled Research, held at Visva-Bharati University, Santiniketan, West Bengal, India, during 12-13 August 2020).
Автор: Gaurav Dhiman, Sandeep Kautish Название: AI-Enabled Multiple Criteria Decision-Making Approaches for Healthcare Management ISBN: 1668444054 ISBN-13(EAN): 9781668444054 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 280890.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: In practical health care cases, semi-structured and unstructured decision-making issues involve multiple criteria (or goals) that may conflict with each other. Thus, the use of MCDM is a promising source of practical solutions for such problems.
Автор: Bhattacharyya Siddhartha, Das Gautam, de Sourav Название: Intelligence Enabled Research: DoSIER 2021 ISBN: 981190488X ISBN-13(EAN): 9789811904882 Издательство: Springer Рейтинг: Цена: 149060.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book gathers extended versions of papers presented at DoSIER 2021 (the 2021 Third Doctoral Symposium on Intelligence Enabled Research, held at Cooch Behar Government Engineering College, West Bengal, India, during November 12–13, 2021). The papers address the rapidly expanding research area of computational intelligence, which, no longer limited to specific computational fields, has since made inroads in signal processing, smart manufacturing, predictive control, robot navigation, smart cities, and sensor design, to name but a few. Presenting chapters written by experts active in these areas, the book offers a valuable reference guide for researchers and industrial practitioners alike and inspires future studies.
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