Books in Artificial intelligence general

11-20 of 102 results in All results

Uncertainty in Computational Intelligence-Based Decision Making

• 1st Edition
• September 16, 2024
• Ali Ahmadian + 3 more
• English
• Paperback 978-0-443-21475-2

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• eBook 978-0-443-21476-9

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Uncertainty in Computational Intelligence-Based Decision-Making focuses on techniques for reasoning and decision-making under uncertainty that are used to solve issues in artificial intelligence (AI). It covers a wide range of subjects, including knowledge acquisition and automated model construction, pattern recognition, machine learning, natural language processing, decision analysis, and decision support systems, among others.The first chapter of this book provides a thorough introduction to the topics of causation in Bayesian belief networks, applications of uncertainty, automated model construction and learning, graphic models for inference and decision making, and qualitative reasoning. The following chapters examine the fundamental models of computational techniques, computational modeling of biological and natural intelligent systems, including swarm intelligence, fuzzy systems, artificial neutral networks, artificial immune systems, and evolutionary computation. They also examine decision making and analysis, expert systems, and robotics in the context of artificial intelligence and computer science.

Artificial Intelligence of Things (AIoT)

• 1st Edition
• September 11, 2024
• Fadi Al-Turjman + 2 more
• English
• Paperback 978-0-443-26482-5

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• eBook 978-0-443-26483-2

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Artificial Intelligence of Things (AIoT): Current and Future Trends brings together researchers and developers from a wide range of domains to share ideas on how to implement technical advances, create application areas for intelligent systems, and how to develop new services and smart devices connected to the Internet. Section One covers AIoT in Everything, providing a wide range of applications for AIoT methods and technologies. Section Two gives readers comprehensive guidance on AIoT in Societal Research and Development, with practical case studies of how AIoT is impacting cultures around the world. Section Three covers the impact of AIoT in educational settings.The book also covers new capabilities such as pervasive sensing, multimedia sensing, machine learning, deep learning, and computing power. These new areas come with various requirements in terms of reliability, quality of service, and energy efficiency.

Speech Signal Processing Based on Deep Learning in Complex Acoustic Environments

• 1st Edition
• September 4, 2024
• Xiao-Lei Zhang
• English
• Paperback 978-0-443-24856-6

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• eBook 978-0-443-24857-3

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Speech Signal Processing Based on Deep Learning in Complex Acoustic Environments provides a detailed discussion of deep learning-based robust speech processing and its applications. The book begins by looking at the basics of deep learning and common deep network models, followed by front-end algorithms for deep learning-based speech denoising, speech detection, single-channel speech enhancement multi-channel speech enhancement, multi-speaker speech separation, and the applications of deep learning-based speech denoising in speaker verification and speech recognition.

Artificial Intelligence for a More Sustainable Oil and Gas Industry and the Energy Transition

• 1st Edition
• July 13, 2024
• Mohammadali Ahmadi
• English
• Paperback 978-0-443-24010-2

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• eBook 978-0-443-24011-9

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Artificial Intelligence for a More Sustainable Oil and Gas Industry and the Energy Transition: Case Studies and Code Examples presents a package for academic researchers and industries working on water resources and carbon capture and storage. This book contains fundamental knowledge on artificial intelligence related to oil and gas sustainability and the industry’s pivot to support the energy transition and provides practical applications through case studies and coding flowcharts, addressing gaps and questions raised by academic and industrial partners, including energy engineers, geologists, and environmental scientists. This timely publication provides fundamental and extensive information on advanced AI applications geared to support sustainability and the energy transition for the oil and gas industry.

Responsible Artificial Intelligence Re-engineering the Global Public Health Ecosystem

• 1st Edition
• June 7, 2024
• Dominique J Monlezun
• English
• Paperback 978-0-443-21597-1

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• eBook 978-0-443-21596-4

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Responsible Artificial Intelligence Re-engineering the Global Public Health Ecosystem: A Humanity Worth Saving is the first comprehensive book showing how trustworthy AI can revolutionize decolonized global public health. It explains how it works as an ecosystem and how it can be fixed to equitably empower us all to solve the defining crises of our era, from poverty to pandemics, climate to conflicts, debt to divisions. It is written from the first-hand perspective of the world’s first triple doctorate trained physician-data scientist and ethicist who has cared for more than 10,000 patients and authored 5 AI textbooks and more than 400 scientific and ethics papers. This essential resource integrates science, political economics, and ethics to unite our unique cultures, belief systems, institutions, and governments. In doing so, it is meant to give humanity a fighting chance against shared existential threats through cooperation and managed strategic competition for integral sustainable development.Taking seriously diverse voices, perspectives, and insights from the Global North and the Global South, this book uses concrete examples backed up by clear explanations to elucidate the current failures, emerging successes, and societal trends of global public health. It shows how a small number of powerful governments and corporations—amid digitalization, deglobalization, and demographic shifts—dominate global health, and how we can re-engineer a better future for it both societally and technologically. The book spans health breakthroughs in federated data architectures, machine learning, deep learning, swarm learning, quantum computing, blockchain, agile data governance and solidarity, value blocks (of democracies and autocracies), adaptive value supply chains, social networks, pandemics, health financing, universal health coverage, public–private partnerships, healthcare system design, precision agriculture, clean energy, human security, and multicultural global ethics. This book therefore is meant to provide a clear, coherent, and actionable guide equipping students, practitioners, researchers, policymakers, and leaders in digital technology, public health, healthcare, health policy, public policy, political economics, and ethics to generate the solutions that will define humanity’s next era—while recovering what that humanity means, and why it is worth saving.

Computational Intelligence Techniques for Sustainable Supply Chain Management

• 1st Edition
• May 23, 2024
• Sanjoy Kumar Paul + 1 more
• English
• Paperback 978-0-443-18464-2

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• eBook 978-0-443-18465-9

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Computational Intelligence Techniques for Sustainable Supply Chain Management presents state-of-the-art computational intelligence techniques and applications for supply chain sustainability issues and logistic problems, filling the gap between general textbooks on sustainable supply chain management and more specialized literature dealing with methods for computational intelligence techniques. This book focuses on addressing problems in advanced topics in the sustainable supply chain and will appeal to practitioners, managers, researchers, students, and professionals interested in sustainable logistics, procurement, manufacturing, inventory and production management, scheduling, transportation, and supply chain network design.

Cognitive Assistant Supported Human-Robot Collaboration

• 1st Edition
• May 13, 2024
• Cecilio Angulo + 2 more
• Fatos Xhafa
• English
• Paperback 978-0-443-22135-4

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• eBook 978-0-443-22136-1

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Cognitive Assistant Supported Human-Robot Collaboration covers the design and development of cognitive assistants in the smart factory era, its application domains, challenges, and current state-of-the-art in assistance systems with collaborative robotics and IoT technologies, standards, platforms, and solutions. This book also provides a sociotechnical view of collaborative work in human-robot teams, investigating specific methods and techniques to analyze assistance systems. This provides readers with a comprehensive overview of how cognitive assistants function and work in human-robot teams.

Metaheuristic Optimization Algorithms

• 1st Edition
• May 5, 2024
• Laith Abualigah
• English
• Paperback 978-0-443-13925-3

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• eBook 978-0-443-13926-0

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Metaheuristic Optimization Algorithms: Optimizers, Analysis, and Applications presents the most recent optimization algorithms and their applications across a wide range of scientific and engineering research fields. The book provides readers with a comprehensive overview of eighteen optimization algorithms to address this complex data, including Particle Swarm Optimization Algorithm, Arithmetic Optimization Algorithm, Whale Optimization Algorithm, and Marine Predators Algorithm, along with new and emerging methods such as Aquila Optimizer, Quantum Approximate Optimization Algorithm, Manta-Ray Foraging Optimization Algorithm, and Gradient Based Optimizer, among others. Each chapter includes an introduction to the modeling concepts used to create the algorithm that is followed by the mathematical and procedural structure of the algorithm, associated pseudocode, and real-world case studies.

Artificial Intelligence and Machine Learning for Women’s Health Issues

• 1st Edition
• April 26, 2024
• Meenu Gupta + 1 more
• English
• Paperback 978-0-443-21889-7

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• eBook 978-0-443-21890-3

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Artificial Intelligence and Machine Learning for Women’s Health Issues discusses the applications, challenges, and solutions that machine learning can bring to women’s health challenges. The book illustrates advanced, innovative techniques, frameworks, concepts, and methodologies of machine learning which enhance the future healthcare system. This book's primary focus is on women’s health issues and machine learning's role in providing solutions to these challenges, providing novel ideas for feasible implementation. It also provides an early-stage analysis for early diagnosis of women’s health issues.

Intelligent Evolutionary Optimization

• 1st Edition
• April 18, 2024
• Hua Xu + 1 more
• English
• Paperback 978-0-443-27400-8

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• eBook 978-0-443-27401-5

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Intelligent Evolutionary Optimization introduces biologically-inspired intelligent optimization algorithms to address complex optimization problems and provide practical solutions for tackling combinatorial optimization problems. The book explores efficient search and optimization methods in high-dimensional spaces, particularly for high-dimensional multi-objective optimization problems, offering practical guidance and effective solutions across various domains. Providing practical solutions, methods, and tools to tackle complex optimization problems and enhance modern optimization techniques, this book will be a valuable resource for professionals seeking to enhance their understanding and proficiency in intelligent evolutionary optimization.