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Wiley-VCH - Industrial Engineering
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Decision-Making Techniques and Methods for Sustainable Technological Innovation
This book is an essential guide for anyone looking to drive sustainable technological innovation, providing a comprehensive toolkit of decision-making methods and real-world applications to effectively manage technology in the era of Industry 5.0. Sustainable technological innovation is critical for building a more sustainable future. As the world faces increasing environmental challenges, there is a pressing need for new and innovative technologies that can reduce resource consumption, mitigate environmental impacts, and promote sustainable development. This book focuses on the vital role of decision-making processes in achieving sustainability through technological innovation in the context of Industry 5.0. By delving into various decision-making methods and approaches employed to facilitate sustainable technological innovation across essential industries such as manufacturing, agriculture, and energy, the book will present both theoretical and applied research on managing technology, including decision-making connected to Industry 4.0 and 5.0, artificial intelligence, and other revolutionary techniques. The book covers a wide range of topics, including multiple attribute decision theory, multiple objective decision-making, patent mining, big data analytics, and other decision-making methods and techniques, and features case studies and reviews that highlight real-world applications of sustainable technological innovation in different industries. The exploration of various decision-making methods and approaches for sustainable technological innovation makes this book an essential guide for those looking toward a sustainable Industry 5.0. Readers will find the book: * Emphasizes the role of decision-making processes in enabling sustainable technological innovation, providing a unique perspective on the subject; * Covers a wide range of topics related to decision-making for sustainable technological innovation, including decision theory, multiple attribute and objective decision-making, patent mining, big data analytics, and case studies; * Provides real-world examples and case studies that demonstrate the effectiveness of decision-making processes in promoting sustainable technological innovation across various industries; * Features the latest research and developments in the field, ensuring that readers are up-to-date on the most current thinking on decision-making for sustainable technological innovation. Audience Researchers, practitioners, and students in the fields of computer science, data science, engineering, and mathematics, specifically interested in decision analytics and machine learning algorithms. [288 Pages, Hardcover]
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Adaptive Artificial Intelligence
Master the next frontier of technology with this book, which provides an in-depth guide to adaptive artificial intelligence and its ability to create flexible, self-governed systems in dynamic industries. Adaptive artificial intelligence represents a significant advancement in the development of AI systems, particularly within various industries that require robust, flexible, and responsive technologies. Unlike traditional AI, which operates based on pre-defined models and static data, adaptive AI is designed to learn and evolve in real time, making it particularly valuable in dynamic and unpredictable environments. This capability is increasingly important in disciplines such as autonomous systems, healthcare, finance, and industrial automation, where the ability to adapt to new information and changing conditions is crucial. In industry development, adaptive AI drives innovation by enabling systems that can continuously improve their performance and decision-making processes without the need for constant human intervention. This leads to more efficient operations, reduced downtime, and enhanced outcomes across sectors. As industries increasingly rely on AI for critical functions, the adaptive capability of these systems becomes a cornerstone for achieving higher levels of automation, reliability, and intelligence in technological solutions. Readers will find the book: * Introduces the emerging concept of adaptive artificial intelligence; * Explores the many applications of adaptive artificial intelligence across various industries; * Provides comprehensive coverage of reinforcement learning for different domains. Audience Research scholars, IT professionals, engineering students, network administrators, artificial intelligence and deep learning experts, and government research agencies looking to innovate with the power of artificial intelligence. [480 Pages, Hardcover]
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Green Hydrogen
Discover the key to a sustainable future with Green Hydrogen, an essential guide for those invested in the innovative potential of green hydrogen production for decarbonization. One of the worldwide objectives for 2050 is to decarbonize the planet. According to the International Energy Agency's most recent projections, the world's energy demand will rise by 25% to 30% by 2040. In an economy that depends on coal and oil, this will increase CO2, exacerbating climate change. Decarbonizing the Earth envisions a different world in 2050--one that is more open, effective, and sustainable, powered by clean energy like green hydrogen. Generating an element like hydrogen is one of the keys to achieving this goal because, unlike coal and oil, green hydrogen is a pure energy source that emits water vapor and leaves no residue in the air. Industry and hydrogen have a long-standing, global partnership that will only grow stronger as the planet moves away from fossil fuels. Green Hydrogen discusses the challenges and opportunities of sustainable hydrogen production and its applications in different industries, including heat and power generation, industry feedstock, and goods and passenger transport. [576 Pages, Hardcover]
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Multi-physics Optimization
[288 Pages, Hardcover]
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Advances in Artificial Intelligence Applications in Industrial and Systems Engineering
Comprehensive guide offering actionable strategies for enhancing human-centered AI, efficiency and productivity in industrial and systems engineering through the power of AI. Advances in Artificial Intelligence Applications is the first book in the Advances in Industrial and Systems Engineering series, offering insights into AI techniques, challenges, and applications across various industrial and systems engineering (ISE) domains. Not only does the book chart current AI trends and tools for effective integration, but it also raises pivotal ethical concerns and explores the latest methodologies, tools, and real-world examples relevant to today's dynamic ISE landscape. Readers will gain a practical toolkit for effective integration and utilization of AI in system design and operation. The book also presents the current state of AI across big data analytics, machine learning, artificial intelligence tools, cloud-based AI applications, neural-based technologies, modeling and simulation in the metaverse, intelligent systems engineering, and more, and discusses future trends. With by renowned international contributors written for an international audience, Advances in Artificial Intelligence Applications includes information on: * Reinforcement learning, computer vision and perception, and safety considerations for autonomous systems (AS) * (NLP) topics including language understanding and generation, sentiment analysis and text classification, and machine translation * AI in healthcare, covering medical imaging and diagnostics, drug discovery and personalized medicine, and patient monitoring and predictive analysis * Cybersecurity, covering threat detection and intrusion prevention, fraud detection and risk management, and network security * Social good applications including poverty alleviation and education, environmental sustainability, and disaster response and humanitarian aid. Advances in Artificial Intelligence Applications is a timely, essential reference for engineering, computer science, and business professionals worldwide. [400 Pages, Hardcover]
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