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Artificial Intelligence for Renewable Energy Systems
ARTIFICIAL INTELLIGENCE FOR RENEWABLE ENERGY SYSTEMS Renewable energy systems, including solar, wind, biodiesel, hybrid energy, and other relevant types, have numerous advantages compared to their conventional counterparts. This book presents the application of machine learning and deep learning techniques for renewable energy system modeling, forecasting, and optimization for efficient system design. Due to the importance of renewable energy in today’s world, this book was designed to enhance the reader’s knowledge based on current developments in the field. For instance, the extraction and selection of machine learning algorithms for renewable energy systems, forecasting of wind and so...
Generative AI and LLMs
Generative artificial intelligence (GAI) and large language models (LLM) are machine learning algorithms that operate in an unsupervised or semi-supervised manner. These algorithms leverage pre-existing content, such as text, photos, audio, video, and code, to generate novel content. The primary objective is to produce authentic and novel material. In addition, there exists an absence of constraints on the quantity of novel material that they are capable of generating. New material can be generated through the utilization of Application Programming Interfaces (APIs) or natural language interfaces, such as the ChatGPT developed by Open AI and Bard developed by Google. The field of generative ...
Quantum-Safe Cryptography Algorithms and Approaches
Quantum computers have demonstrated that they have the inherent potential to outperform classical computers in many areas. One of the major impacts is that the currently available cryptography algorithms are bound to no longer hold once quantum computers are able to compute at full speed. This book presents an overview of all the cross-disciplinary developments in cybersecurity that are being generated by the advancements in quantum computing.
Quantum Machine Learning
Quantum computing has shown a potential to tackle specific types of problems, especially those involving a daunting number of variables, at an exponentially faster rate compared to classical computers. This volume focuses on quantum variants of machine learning algorithms, such as quantum neural networks, quantum reinforcement learning, quantum principal component analysis, quantum support vectors, quantum Boltzmann machines, and many more.
Blockchain, Artificial Intelligence, and the Internet of Things
This book provides basic concepts and deep knowledge about various security mechanisms that can be implemented in IoT through Blockchain technology. This book aids readers in gaining insight and knowledge about providing security and solutions to different challenges in IoT using Blockchain technology. This book primarily focuses on challenges to addressing the integration of the IoT with Blockchain with respect to potential benefits for IoT. This book gives descriptive analysis of Blockchain integrated with IoT applications and platforms for the development of IoT solutions along with possible topologies to that integration. Several application examples are included in a variety of industries.
Information and Communication Technology for Competitive Strategies (ICTCS 2022)
This book contains best selected research papers presented at ICTCS 2022: Seventh International Conference on Information and Communication Technology for Competitive Strategies. The conference will be held in Chandigarh, India during 9 – 10 December 2022. The book covers state-of-the-art as well as emerging topics pertaining to ICT and effective strategies for its implementation for engineering and managerial applications. This book contains papers mainly focused on ICT for computation, algorithms and data analytics and IT security. The work is presented in two volumes.
Intelligent Technologies and Parkinson’s Disease: Prediction and Diagnosis
When it comes to Parkinson's disease, one of the most important issues revolves around early detection and accurate diagnosis. The intricacies of this neurodegenerative disorder often elude timely identification, leaving patients and healthcare providers grappling with its progressive symptoms. Ethical concerns surrounding the use of machine learning to aid in diagnosis further complicate this challenge. This issue is particularly significant for research scholars, PhD fellows, post-doc fellows, and medical and biomedical scholars seeking to unravel the mysteries of Parkinson's disease and develop more effective treatments. Intelligent Technologies and Parkinson’s Disease: Prediction and Diagnosis serves as a beacon of hope in the quest to revolutionize Parkinson's disease diagnosis and treatment. It unveils the remarkable potential of artificial intelligence (AI) and machine learning (ML) in remodeling the way we approach this debilitating condition. With a comprehensive exploration of AI's capacity to analyze speech patterns, brain imaging data, and gait patterns, this book offers a powerful solution to the challenges of early detection and accurate diagnosis.
Applications of Artificial Intelligence and Machine Learning
The book presents a collection of peer-reviewed articles from the International Conference on Advances and Applications of Artificial Intelligence and Machine Learning—ICAAAIML 2021. The book covers research in the areas of artificial intelligence, machine learning, and deep learning applications in health care, agriculture, business, and security. This book contains research papers from academicians, researchers as well as students. There are also papers on core concepts of computer networks, intelligent system design and deployment, real-time systems, wireless sensor networks, sensors and sensor nodes, software engineering, and image processing. This book is a valuable resource for students, academics, and practitioners in the industry working on AI applications.
