Ramani Kannan

Ajay Rana

Sumit Badotra

Sarvesh Tanwar

Nidhi Sindhwani

Augmented and Virtual Reality are revolutionizing present and future technologies: these are the fastest growing and most fascinating areas of technologies at present. This book aims to provide insight into the theory and applications of Augmented and Virtual Reality to multiple technologies such as IoT (Internet of Things), ML (Machine Learning), AI (Artifi cial Intelligence), Healthcare and Education.

Handbook of Augmented and Virtual Reality

Dharavath Kishan

B Dastagiri Reddy

Prajof Prabhakaran

This text will help readers to gain knowledge about designing power electronic converters and their control for electric vehicles. It discusses the ways in which power from electric vehicle batteries is transferred to an electric motor, the technology used for charging electric vehicle batteries, and energy storage. The text covers case studies and real-life examples related to electric vehicles. The book • Discusses the latest advances and developments in the field of electric vehicles • Examines the challenges associated with the integration of renewable energy sources with electric vehicles • Highlights basic understanding of the charging infrastructure for electric vehicles • Covers concepts including the reliability of power converters in electric vehicles, and battery management systems. This book discusses the challenges, emerging technologies, and recent development of power electronics for electric vehicles. It will serve as an ideal reference text for graduate students and academic researchers in the fields of electrical engineering, electronics and communication engineering, environmental engineering, automotive engineering, and computer science.

Emerging Technologies and Developments

Power Electronics for Electric Vehicles and Energy Storage

Samsul Ariffin Abdul Karim

Shaharin Anwar Sulaiman

Nursyarizal Mohd Nor

This book presents recent science and engineering research in the field of conventional and renewable energy, energy efficiency and optimization, discussing problems such as availability, peak load and reliability of sustainable supply for power to consumers. Such research is imperative since efficient and environmentally friendly solutions are critical in modern electricity production and transmission.

Sustainable Electrical Power Resources through Energy Optimization and Future Engineering

Nordin Saad

This book is a collection of research work conducted by researchers at Centre for Smart Grid Energy Research (CSMER), Institute of Autonomous System, Universiti Teknologi PETRONAS (UTP), and Seismic Modelling and Inversion Group, King Abdullah University of Science and Technology (KAUST), Saudi Arabia. The book covers topics in the field of renewable energy where visualization, artificial neural network and deep learning techniques have been applied to optimize the performance of various applications in energy-related industries. These examples include a natural gas vehicle (NGV), a single axis and a fixed axis solar tracker, seismic inversion enhanced oil recovery, viability of a PV system and construction of a septic B-spline tensor product scheme. Readers will benefit from these examples, which describe the current trend of energy optimization techniques in renewable energy applications making it a good reference for the researchers and industrial practitioners working in the field of renewable energy and optimization techniques.

A New Perspective from Signal to Image Recognition

Advanced Methods for Processing and Visualizing the Renewable Energy

Vishal Jain

Sapna Juneja

Abhinav Juneja

Technology is moving at an exponential pace in this era of computational intelligence. Machine learning has emerged as one of the most promising tools used to challenge and think beyond current limitations. This handbook will provide readers with a leading edge to improving their products and processes through optimal and smarter machine learning techniques. This handbook focuses on new machine learning developments that can lead to newly developed applications. It uses a predictive and futuristic approach, which makes machine learning a promising tool for processes and sustainable solutions. It also promotes newer algorithms that are more efficient and reliable for new dimensions in discovering other applications, and then goes on to discuss the potential in making better use of machines in order to ensure optimal prediction, execution, and decision-making. Individuals looking for machine learning-based knowledge will find interest in this handbook. The readership ranges from undergraduate students of engineering and allied courses to researchers, professionals, and application designers.

Applications and Case Studies

Handbook of Machine Learning for Computational Optimization

Ramani Kannan

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