Название: Artificial Intelligence and Machine Learning Applications for Sustainable Development
Автор: A.J. Singh, Nikita Gupta, Sanjay Kumar, Sumit Sharma, Subho Upadhyay, Sandeep Kumar
Издательство: CRC Press
Год: 2025
Страниц: 370
Язык: английский
Формат: pdf (true), epub
Размер: 16.8 MB

The book highlights how technologies including Artificial Intelligence and Machine Learning are transforming renewable energy technologies and enabling the development of new solutions. It further discusses how smart technologies are employed to optimize energy production and storage, enhance energy efficiency, and improve the overall sustainability of energy systems.

The fundamental goal of this book is to provide a comprehensive guide to help readers understand the technology under the complex field of sustainable development with their real-world challenges due to its growing significance and demand. These developments have opened up new research, innovation, and exploration avenues. In recent years, the fields of Artificial Intelligence (AI) and Machine Learning (ML) have surged to the forefront of innovation, presenting unparalleled opportunities to address the pressing challenges of sustainable development. This book, Artificial Intelligence and Machine Learning Applications for Sustainable Development, curated by experts in the field, offers a comprehensive exploration of how these technologies can be harnessed to catalyze positive change.

The journey begins with an insightful overview of the evolution of AI and ML, tracing their origins and highlighting the key milestones that have shaped their development. From theoretical foundations to practical applications, readers will gain a deep understanding of the underlying principles driving this transformative field. As we delve deeper, the book navigates through a series of chapters that delve into specific applications of AI and ML in the realm of sustainable development. From leveraging renewable energy sources to optimizing smart city infrastructures, each chapter offers practical insights and real-world case studies that illustrate the potential impact of these technologies on building a more sustainable future. One of the core themes explored throughout the book is the intersection of AI and ML with big data management, cloud computing, image processing, pattern recognition, and signal processing. These chapters shed light on how advanced data analytics techniques can be used to derive valuable insights and inform decision-making processes in various domains related to sustainable development. In addition to addressing technological advancements, this book also examines the broader strategies and frameworks for integrating AI and ML into sustainable development initiatives.

DL, a subset of ML, utilizes algorithms that gain knowledge from various hierarchical levels to represent complex data relationships. It is characterized by deep architecture where high-level features are built upon lower-level ones. Mainly based on unsupervised learning, DL integrates neural networks, graphical modelling, and optimization, enabling significant advancements in information processing. Its popularity stems from enhancing computer processing capabilities, accommodating large datasets, and driving recent breakthroughs in ML. DL, a subset of AI, utilizes computer optimization algorithms modelled after artificial neural networks (ANNs) to replicate human cognitive processes. ANNs consist of interconnected nodes or artificial neurons that imitate the arrangement of human neural networks. Through learning mechanisms, such as reinforcement, synapses in ANNs strengthen, enabling the development of problem-solving capabilities.

This book:

Discusses artificial intelligence-based techniques, namely, neural networks, fuzzy expert systems, optimization techniques, and operational research.
Showcases the importance of artificial intelligence and machine learning in the energy market, demand analysis, and forecasting of renewable energy applications.
Illustrates strategies for sustainable development using Artificial Intelligence and Machine Learning applications.
Presents applications of Artificial Intelligence in the domain of electronics transformation and development, smart cities, and renewable energy utilization.
Highlights the role of Artificial Intelligence in solving problems such as image and signal processing, smart weather monitoring, smart farming, and distributed energy sources.

It is primarily written for senior undergraduates, graduate students, and academic researchers in diverse fields, including electrical, electronics and communications, energy, and environmental engineering.






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