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"This book covers the latest and cutting-edge application technology of Adaptive AI in various fields. It can provide relevant practitioners with ideas to solve problems and have a deeper understanding of Adaptive AI. At the same time, guide and help Adaptive AI and related industries to deepen their understanding of the industry and enhance their professional knowledge and skills"--
Book Synopsis Handbook of Research on Adaptive Artificial Intelligence by : Zhihan Lv
Download or read book Handbook of Research on Adaptive Artificial Intelligence written by Zhihan Lv and published by . This book was released on 2024 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: "This book covers the latest and cutting-edge application technology of Adaptive AI in various fields. It can provide relevant practitioners with ideas to solve problems and have a deeper understanding of Adaptive AI. At the same time, guide and help Adaptive AI and related industries to deepen their understanding of the industry and enhance their professional knowledge and skills"--
The rapid adoption of deep learning models has resulted in many business services becoming model services, yet most AI systems lack the necessary automation and industrialization capabilities. This leads to heavy reliance on manual operation and maintenance, which not only consumes power but also causes resource wastage and stability issues during system mutations. The inadequate self-adaptation of AI systems poses significant challenges in terms of cost-effectiveness and operational stability. Principles and Applications of Adaptive Artificial Intelligence , edited by Zhihan Lv of Uppsala University, Sweden, offers a comprehensive solution to the self-adaptation issues in AI systems. It explores the latest concepts, technologies, and applications of adaptive AI, equipping academic scholars and professionals with the necessary knowledge to overcome the challenges faced by traditional business logic transformed into model services. With its problem-solving approach, the handbook presents real-world cases, along with thorough analysis and relatable examples, making it an invaluable resource for practitioners seeking practical ideas and solutions in the field. Additionally, the book serves as a teaching material and reference guide for students and educators in AI-related disciplines, ensuring a deep understanding and exploration of the emerging discipline of Adaptive AI. By emphasizing self-adaptation, continuous model iteration, and dynamic learning based on real-time feedback, the book empowers readers to significantly enhance the cost-effectiveness and operational stability of AI systems. In a rapidly changing landscape, Principles and Applications of Adaptive Artificial Intelligence becomes the ultimate guide for researchers, professionals, and students, enabling them to unleash the full potential of Adaptive AI and revolutionize their research and applications.
Book Synopsis Principles and Applications of Adaptive Artificial Intelligence by : Zhihan Lv
Download or read book Principles and Applications of Adaptive Artificial Intelligence written by Zhihan Lv and published by . This book was released on 2024 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: The rapid adoption of deep learning models has resulted in many business services becoming model services, yet most AI systems lack the necessary automation and industrialization capabilities. This leads to heavy reliance on manual operation and maintenance, which not only consumes power but also causes resource wastage and stability issues during system mutations. The inadequate self-adaptation of AI systems poses significant challenges in terms of cost-effectiveness and operational stability. Principles and Applications of Adaptive Artificial Intelligence , edited by Zhihan Lv of Uppsala University, Sweden, offers a comprehensive solution to the self-adaptation issues in AI systems. It explores the latest concepts, technologies, and applications of adaptive AI, equipping academic scholars and professionals with the necessary knowledge to overcome the challenges faced by traditional business logic transformed into model services. With its problem-solving approach, the handbook presents real-world cases, along with thorough analysis and relatable examples, making it an invaluable resource for practitioners seeking practical ideas and solutions in the field. Additionally, the book serves as a teaching material and reference guide for students and educators in AI-related disciplines, ensuring a deep understanding and exploration of the emerging discipline of Adaptive AI. By emphasizing self-adaptation, continuous model iteration, and dynamic learning based on real-time feedback, the book empowers readers to significantly enhance the cost-effectiveness and operational stability of AI systems. In a rapidly changing landscape, Principles and Applications of Adaptive Artificial Intelligence becomes the ultimate guide for researchers, professionals, and students, enabling them to unleash the full potential of Adaptive AI and revolutionize their research and applications.
The rapid adoption of deep learning models has resulted in many business services becoming model services, yet most AI systems lack the necessary automation and industrialization capabilities. This leads to heavy reliance on manual operation and maintenance, which not only consumes power but also causes resource wastage and stability issues during system mutations. The inadequate self-adaptation of AI systems poses significant challenges in terms of cost-effectiveness and operational stability. Principles and Applications of Adaptive Artificial Intelligence, edited by Zhihan Lv from Uppsala University, Sweden, offers a comprehensive solution to the self-adaptation problem in AI systems. It explores the latest concepts, technologies, and applications of Adaptive AI, equipping academic scholars and professionals with the necessary knowledge to overcome the challenges faced by traditional business logic transformed into model services. With its problem-solving approach, real-world case studies, and thorough analysis, the Handbook provides practitioners with practical ideas and solutions, while also serving as a valuable teaching material and reference guide for students and educators in AI-related disciplines. By emphasizing self-adaptation, continuous model iteration, and dynamic learning based on real-time feedback, the book empowers readers to significantly enhance the cost-effectiveness and operational stability of AI systems, making it an indispensable resource for researchers, professionals, and students seeking to revolutionize their research and applications in the field of Adaptive AI.
Book Synopsis Principles and Applications of Adaptive Artificial Intelligence by : Lv, Zhihan
Download or read book Principles and Applications of Adaptive Artificial Intelligence written by Lv, Zhihan and published by IGI Global. This book was released on 2024-01-24 with total page 332 pages. Available in PDF, EPUB and Kindle. Book excerpt: The rapid adoption of deep learning models has resulted in many business services becoming model services, yet most AI systems lack the necessary automation and industrialization capabilities. This leads to heavy reliance on manual operation and maintenance, which not only consumes power but also causes resource wastage and stability issues during system mutations. The inadequate self-adaptation of AI systems poses significant challenges in terms of cost-effectiveness and operational stability. Principles and Applications of Adaptive Artificial Intelligence, edited by Zhihan Lv from Uppsala University, Sweden, offers a comprehensive solution to the self-adaptation problem in AI systems. It explores the latest concepts, technologies, and applications of Adaptive AI, equipping academic scholars and professionals with the necessary knowledge to overcome the challenges faced by traditional business logic transformed into model services. With its problem-solving approach, real-world case studies, and thorough analysis, the Handbook provides practitioners with practical ideas and solutions, while also serving as a valuable teaching material and reference guide for students and educators in AI-related disciplines. By emphasizing self-adaptation, continuous model iteration, and dynamic learning based on real-time feedback, the book empowers readers to significantly enhance the cost-effectiveness and operational stability of AI systems, making it an indispensable resource for researchers, professionals, and students seeking to revolutionize their research and applications in the field of Adaptive AI.
These original contributions provide a unique opportunity for researchers and computing professionals, engineers, and managers to explore both the principles underlying basic AI research and their application in practice. The first part of the book describes work in five areas of AI research that is currently at the stage where it can be implemented in practical programs. These areas include blackboard architectures and systems, learning algorithms and strategies, neural networks, adaptive learning using pattern recognition, and signal processing. The second part describes six systems, designed for a wide variety of applications, that are now either in operation or at an advanced stage of development; intelligent techniques for spectral estimation, expert systems applied to antenatal assessment of fetal well-being, AI in the processing of underwater acoustic data, automatic speech recognition using neural networks, fault diagnosis of microwave digital radio, and waveguide filter alignment using adaptive learning techniques. A. R. Mirzai is a Research Fellow in the Department of Electrical Engineering at the University of Edinburgh. Artificial Intelligence: Concepts and Applications is included in the Artificial Intelligence series, edited by Michael Brady, Daniel Bobrow, and Randall Davis.
Book Synopsis Artificial Intelligence by : A. R. Mirzai
Download or read book Artificial Intelligence written by A. R. Mirzai and published by Chapman & Hall. This book was released on 1990 with total page 336 pages. Available in PDF, EPUB and Kindle. Book excerpt: These original contributions provide a unique opportunity for researchers and computing professionals, engineers, and managers to explore both the principles underlying basic AI research and their application in practice. The first part of the book describes work in five areas of AI research that is currently at the stage where it can be implemented in practical programs. These areas include blackboard architectures and systems, learning algorithms and strategies, neural networks, adaptive learning using pattern recognition, and signal processing. The second part describes six systems, designed for a wide variety of applications, that are now either in operation or at an advanced stage of development; intelligent techniques for spectral estimation, expert systems applied to antenatal assessment of fetal well-being, AI in the processing of underwater acoustic data, automatic speech recognition using neural networks, fault diagnosis of microwave digital radio, and waveguide filter alignment using adaptive learning techniques. A. R. Mirzai is a Research Fellow in the Department of Electrical Engineering at the University of Edinburgh. Artificial Intelligence: Concepts and Applications is included in the Artificial Intelligence series, edited by Michael Brady, Daniel Bobrow, and Randall Davis.
Book Synopsis Artificial Intelligence by : Masoud Yazdani
Download or read book Artificial Intelligence written by Masoud Yazdani and published by Chapman & Hall. This book was released on 1986 with total page 380 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Genetic algorithms are playing an increasingly important role in studies of complex adaptive systems, ranging from adaptive agents in economic theory to the use of machine learning techniques in the design of complex devices such as aircraft turbines and integrated circuits.
Book Synopsis Adaptation in Natural and Artificial Systems by : John H. Holland
Download or read book Adaptation in Natural and Artificial Systems written by John H. Holland and published by Bradford Book. This book was released on 1992-01-01 with total page 211 pages. Available in PDF, EPUB and Kindle. Book excerpt: Genetic algorithms are playing an increasingly important role in studies of complex adaptive systems, ranging from adaptive agents in economic theory to the use of machine learning techniques in the design of complex devices such as aircraft turbines and integrated circuits.
This book will advance the understanding and application of self-adaptive intelligent systems; therefore it will potentially benefit the long-term goal of replicating certain levels of brain-like intelligence in complex and networked engineering systems. It will provide new approaches for adaptive systems within uncertain environments. This will provide an opportunity to evaluate the strengths and weaknesses of the current state-of-the-art of knowledge, give rise to new research directions, and educate future professionals in this domain. Self-adaptive intelligent systems have wide applications from military security systems to civilian daily life. In this book, different application problems, including pattern recognition, classification, image recovery, and sequence learning, will be presented to show the capability of the proposed systems in learning, memory, and prediction. Therefore, this book will also provide potential new solutions to many real-world applications.
Book Synopsis Self-Adaptive Systems for Machine Intelligence by : Haibo He
Download or read book Self-Adaptive Systems for Machine Intelligence written by Haibo He and published by John Wiley & Sons. This book was released on 2011-09-15 with total page 189 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book will advance the understanding and application of self-adaptive intelligent systems; therefore it will potentially benefit the long-term goal of replicating certain levels of brain-like intelligence in complex and networked engineering systems. It will provide new approaches for adaptive systems within uncertain environments. This will provide an opportunity to evaluate the strengths and weaknesses of the current state-of-the-art of knowledge, give rise to new research directions, and educate future professionals in this domain. Self-adaptive intelligent systems have wide applications from military security systems to civilian daily life. In this book, different application problems, including pattern recognition, classification, image recovery, and sequence learning, will be presented to show the capability of the proposed systems in learning, memory, and prediction. Therefore, this book will also provide potential new solutions to many real-world applications.
The relentless growth of cyber threats poses an escalating challenge to our global community. The current landscape of cyber threats demands a proactive approach to cybersecurity, as the consequences of lapses in digital defense reverberate across industries and societies. From data breaches to sophisticated malware attacks, the vulnerabilities in our interconnected systems are glaring. As we stand at the precipice of a digital revolution, the need for a comprehensive understanding of cybersecurity risks and effective countermeasures has never been more pressing. Risk Assessment and Countermeasures for Cybersecurity is a book that clarifies many of these challenges in the realm of cybersecurity. It systematically navigates the web of security challenges, addressing issues that range from cybersecurity risk assessment to the deployment of the latest security countermeasures. As it confronts the threats lurking in the digital shadows, this book stands as a catalyst for change, encouraging academic scholars, researchers, and cybersecurity professionals to collectively fortify the foundations of our digital world.
Book Synopsis Risk Assessment and Countermeasures for Cybersecurity by : Almaiah, Mohammed Amin
Download or read book Risk Assessment and Countermeasures for Cybersecurity written by Almaiah, Mohammed Amin and published by IGI Global. This book was released on 2024-05-01 with total page 304 pages. Available in PDF, EPUB and Kindle. Book excerpt: The relentless growth of cyber threats poses an escalating challenge to our global community. The current landscape of cyber threats demands a proactive approach to cybersecurity, as the consequences of lapses in digital defense reverberate across industries and societies. From data breaches to sophisticated malware attacks, the vulnerabilities in our interconnected systems are glaring. As we stand at the precipice of a digital revolution, the need for a comprehensive understanding of cybersecurity risks and effective countermeasures has never been more pressing. Risk Assessment and Countermeasures for Cybersecurity is a book that clarifies many of these challenges in the realm of cybersecurity. It systematically navigates the web of security challenges, addressing issues that range from cybersecurity risk assessment to the deployment of the latest security countermeasures. As it confronts the threats lurking in the digital shadows, this book stands as a catalyst for change, encouraging academic scholars, researchers, and cybersecurity professionals to collectively fortify the foundations of our digital world.
The applications of rapidly advancing intelligent systems are so varied that many are still yet to be discovered. There is often a disconnect between experts in computer science, artificial intelligence, machine learning, robotics, and other specialties, which inhibits the potential for the expansion of this technology and its many benefits. A resource that encourages interdisciplinary collaboration is needed to bridge the gap between these respected leaders of their own fields. Deep Learning, Reinforcement Learning, and the Rise of Intelligent Systems represents an exploration of the forefront of artificial intelligence, navigating the complexities of this field and its many applications. This guide expertly navigates through the intricate domains of deep learning and reinforcement learning, offering an in-depth journey through foundational principles, advanced methodologies, and cutting-edge algorithms shaping the trajectory of intelligent systems. The book covers an introduction to artificial intelligence and its subfields, foundational aspects of deep learning, a demystification of the architecture of neural networks, the mechanics of backpropagation, and the intricacies of critical elements such as activation and loss functions. The book serves as a valuable educational resource for professionals. Its structured approach makes it an ideal reference for students, researchers, and industry professionals.
Book Synopsis Deep Learning, Reinforcement Learning, and the Rise of Intelligent Systems by : Uddin, M. Irfan
Download or read book Deep Learning, Reinforcement Learning, and the Rise of Intelligent Systems written by Uddin, M. Irfan and published by IGI Global. This book was released on 2024-02-26 with total page 307 pages. Available in PDF, EPUB and Kindle. Book excerpt: The applications of rapidly advancing intelligent systems are so varied that many are still yet to be discovered. There is often a disconnect between experts in computer science, artificial intelligence, machine learning, robotics, and other specialties, which inhibits the potential for the expansion of this technology and its many benefits. A resource that encourages interdisciplinary collaboration is needed to bridge the gap between these respected leaders of their own fields. Deep Learning, Reinforcement Learning, and the Rise of Intelligent Systems represents an exploration of the forefront of artificial intelligence, navigating the complexities of this field and its many applications. This guide expertly navigates through the intricate domains of deep learning and reinforcement learning, offering an in-depth journey through foundational principles, advanced methodologies, and cutting-edge algorithms shaping the trajectory of intelligent systems. The book covers an introduction to artificial intelligence and its subfields, foundational aspects of deep learning, a demystification of the architecture of neural networks, the mechanics of backpropagation, and the intricacies of critical elements such as activation and loss functions. The book serves as a valuable educational resource for professionals. Its structured approach makes it an ideal reference for students, researchers, and industry professionals.
In our increasingly interconnected world, low-resource languages face the threat of oblivion. These linguistic gems, often spoken by marginalized communities, are at risk of fading away due to limited data and resources. The neglect of these languages not only erodes cultural diversity but also hinders effective communication, education, and social inclusion. Academics, practitioners, and policymakers grapple with the urgent need for a comprehensive solution to preserve and empower these vulnerable languages. Empowering Low-Resource Languages With NLP Solutions is a pioneering book that stands as the definitive answer to the pressing problem at hand. It tackles head-on the challenges that low-resource languages face in the realm of Natural Language Processing (NLP). Through real-world case studies, expert insights, and a comprehensive array of topics, this book equips its readersacademics, researchers, practitioners, and policymakerswith the tools, strategies, and ethical considerations needed to address the crisis facing low-resource languages.
Book Synopsis Empowering Low-Resource Languages With NLP Solutions by : Pakray, Partha
Download or read book Empowering Low-Resource Languages With NLP Solutions written by Pakray, Partha and published by IGI Global. This book was released on 2024-02-27 with total page 328 pages. Available in PDF, EPUB and Kindle. Book excerpt: In our increasingly interconnected world, low-resource languages face the threat of oblivion. These linguistic gems, often spoken by marginalized communities, are at risk of fading away due to limited data and resources. The neglect of these languages not only erodes cultural diversity but also hinders effective communication, education, and social inclusion. Academics, practitioners, and policymakers grapple with the urgent need for a comprehensive solution to preserve and empower these vulnerable languages. Empowering Low-Resource Languages With NLP Solutions is a pioneering book that stands as the definitive answer to the pressing problem at hand. It tackles head-on the challenges that low-resource languages face in the realm of Natural Language Processing (NLP). Through real-world case studies, expert insights, and a comprehensive array of topics, this book equips its readersacademics, researchers, practitioners, and policymakerswith the tools, strategies, and ethical considerations needed to address the crisis facing low-resource languages.
