Over the past decade, Artificial Intelligence has proved invaluable in a range of industry verticals such as automotive and assembly, life sciences, retail, oil and gas, and travel. The leading sectors adopting AI rapidly are Financial Services, Automotive and Assembly, High Tech and Telecommunications. Travel has been slow in adoption, but the opportunity for generating incremental value by leveraging AI to augment traditional analytics driven solutions is extremely high.

Soft Computing in Green and Renewable Energy Systems provides a practical introduction to the application of soft computing techniques and hybrid intelligent systems for designing, modeling, characterizing, optimizing, forecasting, and performance prediction of green and renewable energy systems. Research is proceeding at jet speed on renewable energy (energy derived from natural resources such as sunlight, wind, tides, rain, geothermal heat, biomass, hydrogen, etc.) as policy makers, researchers, economists, and world agencies have joined forces in finding alternative sustainable energy solutions to current critical environmental, economic, and social issues. The innovative models, environmentally benign processes, data analytics, etc. employed in renewable energy systems are computationally-intensive, non-linear and complex as well as involve a high degree of uncertainty. Soft computing technologies, such as fuzzy sets and systems, neural science and systems, evolutionary algorithms and genetic programming, and machine learning, are ideal in handling the noise, imprecision, and uncertainty in the data, and yet achieve robust, low-cost solutions. As a result, intelligent and soft computing paradigms are finding increasing applications in the study of renewable energy systems. Researchers, practitioners, undergraduate and graduate students engaged in the study of renewable energy systems will find this book very useful.

Robust Nano-Computing focuses on various issues of robust nano-computing, defect-tolerance design for nano-technology at different design abstraction levels. It addresses both redundancy- and configuration-based methods as well as fault detecting techniques through the development of accurate computation models and tools. The contents present an insightful view of the ongoing researches on nano-electronic devices, circuits, architectures, and design methods, as well as provide promising directions for future research.

We describe in this book, new methods for intelligent manufacturing using soft computing techniques and fractal theory. Soft Computing (SC) consists of several computing paradigms, including fuzzy logic, neural networks, and genetic algorithms, which can be used to produce powerful hybrid intelligent systems. Fractal theory provides us with the mathematical tools to understand the geometrical complexity of natural objects and can be used for identification and modeling purposes.

Real-time computing plays a crucial role in our society since an increasing num­ ber of complex systems rely, in part or completely, on processor control. Ex­ amples of applications that require real-time computing include nuclear power plants, railway switching systems, automotive electronics, air traffic control, telecommunications, robotics, and military systems. In spite of this large application domain, most of the current real-time systems are still designed and implemented using low-level programming and empirical techniques, without the support of a scientific methodology. This approach results in a lack of reliability, which in critical applications may cause serious environmental damage or even loss of life. This book is a basic treatise on real-time computing, with particular emphasis on predictable scheduling algorithms. The main objectives of the book are to introduce the basic concepts of real-time computing, illustrate the most sig­ nificant results in the field, and provide the basic methodologies for designing predictable computing systems useful in supporting critical control applica­ tions. The book is written for instructional use and is organized to enable readers without a strong knowledge of the subject matter to quickly grasp the material. Technical concepts are clearly defined at the beginning of each chapter, and algorithm descriptions are reinforced through concrete examples, illustrations, and tables.

Learn how the disruptive AI chatbot is going to change school, work, and beyond

This book comprises the select proceedings of the International Conference in Power, Energy, Control, Signals and Systems (IPECS) 2022. The book focuses on intelligent solutions for smart grids and smart cities. The content of this book is designed to develop many innovative ideas for an energy-efficient and sustainable future. It focuses on recent technological advances and challenges in the field of grid integration of renewable energy resources, AI/ML in power and energy systems, security enhancement of power systems/electronics using advanced ML techniques for integration of renewable energies, electric vehicle-energy storage, and battery charging technologies, etc. The book also covers the latest advances especially in instrumentation and control in smart grid applications —Internet of Things and cyber-physical systems, power semiconductor device technology leading to improvements in power losses for power electronic systems, economic and sustainable design of smart cities-security and data privacy in smart cities, lighting, and illumination. This book proves to be a valuable resource for those in academia and industry.

This book comprises the select proceedings of the International Conference in Power, Energy, Control, Signals and Systems (IPECS) 2022. The book focuses on intelligent solutions for smart grids and smart cities. The content of this book is designed to develop many innovative ideas for an energy-efficient and sustainable future. It focuses on recent technological advances and challenges in the field of grid integration of renewable energy resources, AI/ML in power and energy systems, security enhancement of power systems/electronics using advanced ML techniques for integration of renewable energies, electric vehicle-energy storage, and battery charging technologies, etc.

This book presents advances on the state of the art in smart cities systems and applications based on the proof of concept and prototyping for smart cities in an interdisciplinary context of engineering and information sciences. Smart cities have emerged as highly complex technological endeavors that combine knowledge and technology from many disciplines ranging from information sciences to engineering. Due to their complex nature, the modeling, development, and prototyping of applications in smart cities present a myriad of challenges, including technical, economic, and social ones, across application subdomains such as smart transportation, social welfare, tourism, and smart industry. It becomes difficult or sometimes impossible to provide a solution for such potential research issues and challenges from a traditional disciplinary-approach only; to tackle such research issues and to make the paradigm of smart cities a reality, interdisciplinary approaches are deemed necessary. Readers, developers, practitioners, and policy-makers in the field find in the book insights, experiences, findings, and perspectives on smart cities applications with an emphasis on real-life prototyping, beyond the confines of laboratory experiments.

This book provides a comprehensive overview of the state of the art in research and applications of Foundation Models and is intended for readers familiar with basic Natural Language Processing (NLP) concepts.

This book focuses on both theory and applications of Artificial Intelligence and Machine Learning in the broad areas of communication and networking. This book focuses on the ongoing research work and future scope for various open research issues related to sustainable design, development, and analysis of smart communication, 5G and beyond, with the integration of Artificial intelligence and IoT. It addresses fundamental technology components for 5G and beyond, which include modern advancements in communication and networking in a real-world application. The book presents the convergence of Artificial Intelligence, Machine Learning, and IoT with 5G and beyond wireless networks to give some ice-breaking solutions in radio resource allocation, network management, and cybersecurity. This book will be a valuable resource for academicians, researchers, and professionals working in artificial intelligence/machine learning and its applications in communication and 5G.