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System Analysis and Artificial Intelligence

System Analysis and Artificial Intelligence PDF Author: Michael Zgurovsky
Publisher: Springer Nature
ISBN: 3031374509
Category : Technology & Engineering
Languages : en
Pages : 468

Book Description
This book contains the latest scientific work of Ukrainian scientists and their colleagues from other countries of the world in three interrelated areas: systems analysis, artificial intelligence and data mining. The included articles present the theoretical foundations and practical applications of the latest tools and methods of artificial intelligence, scenario planning, decision making and computational intelligence for important areas of human activity. The tools and methods presented in the book are continuously evolving and finding new applications across various fields, contributing to advancements and efficiencies in different industries: healthcare, finance, retail and E-commerce, manufacturing and industrial automation, transportation and logistics advancements and cybersecurity. The results of the book are useful to teachers, scientists, graduate students of universities and managers of large companies specializing in strategic planning, engineering design of complex systems, decision-making, optimization of operations and other related fields of knowledge and practice.

System Analysis and Artificial Intelligence

System Analysis and Artificial Intelligence PDF Author: Michael Zgurovsky
Publisher: Springer Nature
ISBN: 3031374509
Category : Technology & Engineering
Languages : en
Pages : 468

Book Description
This book contains the latest scientific work of Ukrainian scientists and their colleagues from other countries of the world in three interrelated areas: systems analysis, artificial intelligence and data mining. The included articles present the theoretical foundations and practical applications of the latest tools and methods of artificial intelligence, scenario planning, decision making and computational intelligence for important areas of human activity. The tools and methods presented in the book are continuously evolving and finding new applications across various fields, contributing to advancements and efficiencies in different industries: healthcare, finance, retail and E-commerce, manufacturing and industrial automation, transportation and logistics advancements and cybersecurity. The results of the book are useful to teachers, scientists, graduate students of universities and managers of large companies specializing in strategic planning, engineering design of complex systems, decision-making, optimization of operations and other related fields of knowledge and practice.

Artificial Intelligence for Sustainable Development: Theory, Practice and Future Applications

Artificial Intelligence for Sustainable Development: Theory, Practice and Future Applications PDF Author: Aboul Ella Hassanien
Publisher: Springer Nature
ISBN: 3030519201
Category : Technology & Engineering
Languages : en
Pages : 310

Book Description
This book highlights the latest advances in the field of artificial intelligence and related technologies, with a special focus on sustainable development and environmentally friendly artificial intelligence applications. Discussing theory, applications and research, it covers all aspects of artificial intelligence in the context of sustainable development.

Artificial Intelligence Techniques in Power Systems

Artificial Intelligence Techniques in Power Systems PDF Author: Kevin Warwick
Publisher: IET
ISBN: 9780852968970
Category : Computers
Languages : en
Pages : 324

Book Description
The intention of this book is to give an introduction to, and an overview of, the field of artificial intelligence techniques in power systems, with a look at various application studies.

Adaptation in Natural and Artificial Systems

Adaptation in Natural and Artificial Systems PDF Author: John H. Holland
Publisher: MIT Press
ISBN: 9780262581110
Category : Psychology
Languages : en
Pages : 236

Book Description
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. Adaptation in Natural and Artificial Systems is the book that initiated this field of study, presenting the theoretical foundations and exploring applications. In its most familiar form, adaptation is a biological process, whereby organisms evolve by rearranging genetic material to survive in environments confronting them. In this now classic work, Holland presents a mathematical model that allows for the nonlinearity of such complex interactions. He demonstrates the model's universality by applying it to economics, physiological psychology, game theory, and artificial intelligence and then outlines the way in which this approach modifies the traditional views of mathematical genetics. Initially applying his concepts to simply defined artificial systems with limited numbers of parameters, Holland goes on to explore their use in the study of a wide range of complex, naturally occuring processes, concentrating on systems having multiple factors that interact in nonlinear ways. Along the way he accounts for major effects of coadaptation and coevolution: the emergence of building blocks, or schemata, that are recombined and passed on to succeeding generations to provide, innovations and improvements.

Computer Aided Verification

Computer Aided Verification PDF Author: Isil Dillig
Publisher: Springer
ISBN: 3030255409
Category : Computers
Languages : en
Pages : 680

Book Description
This open access two-volume set LNCS 11561 and 11562 constitutes the refereed proceedings of the 31st International Conference on Computer Aided Verification, CAV 2019, held in New York City, USA, in July 2019. The 52 full papers presented together with 13 tool papers and 2 case studies, were carefully reviewed and selected from 258 submissions. The papers were organized in the following topical sections: Part I: automata and timed systems; security and hyperproperties; synthesis; model checking; cyber-physical systems and machine learning; probabilistic systems, runtime techniques; dynamical, hybrid, and reactive systems; Part II: logics, decision procedures; and solvers; numerical programs; verification; distributed systems and networks; verification and invariants; and concurrency.

The Myth of Artificial Intelligence

The Myth of Artificial Intelligence PDF Author: Erik J. Larson
Publisher: Harvard University Press
ISBN: 0674983513
Category : Computers
Languages : en
Pages : 321

Book Description
“Artificial intelligence has always inspired outlandish visions—that AI is going to destroy us, save us, or at the very least radically transform us. Erik Larson exposes the vast gap between the actual science underlying AI and the dramatic claims being made for it. This is a timely, important, and even essential book.” —John Horgan, author of The End of Science Many futurists insist that AI will soon achieve human levels of intelligence. From there, it will quickly eclipse the most gifted human mind. The Myth of Artificial Intelligence argues that such claims are just that: myths. We are not on the path to developing truly intelligent machines. We don’t even know where that path might be. Erik Larson charts a journey through the landscape of AI, from Alan Turing’s early work to today’s dominant models of machine learning. Since the beginning, AI researchers and enthusiasts have equated the reasoning approaches of AI with those of human intelligence. But this is a profound mistake. Even cutting-edge AI looks nothing like human intelligence. Modern AI is based on inductive reasoning: computers make statistical correlations to determine which answer is likely to be right, allowing software to, say, detect a particular face in an image. But human reasoning is entirely different. Humans do not correlate data sets; we make conjectures sensitive to context—the best guess, given our observations and what we already know about the world. We haven’t a clue how to program this kind of reasoning, known as abduction. Yet it is the heart of common sense. Larson argues that all this AI hype is bad science and bad for science. A culture of invention thrives on exploring unknowns, not overselling existing methods. Inductive AI will continue to improve at narrow tasks, but if we are to make real progress, we must abandon futuristic talk and learn to better appreciate the only true intelligence we know—our own.

Trends in Artificial Intelligence Theory and Applications. Artificial Intelligence Practices

Trends in Artificial Intelligence Theory and Applications. Artificial Intelligence Practices PDF Author: Hamido Fujita
Publisher: Springer Nature
ISBN: 3030557898
Category : Computers
Languages : en
Pages : 931

Book Description
This book constitutes the thoroughly refereed proceedings of the 33rd International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2020, held in Kitakyushu, Japan, in September 2020. The 62 full papers and 17 short papers presented were carefully reviewed and selected from 119 submissions. The IEA/AIE 2020 conference will continue the tradition of emphasizing on applications of applied intelligent systems to solve real-life problems in all areas. These areas include are language processing; robotics and drones; knowledge based systems; innovative applications of intelligent systems; industrial applications; networking applications; social network analysis; financial applications and blockchain; medical and health-related applications; anomaly detection and automated diagnosis; decision-support and agent-based systems; multimedia applications; machine learning; data management and data clustering; pattern mining; system control, classification, and fault diagnosis.

Artificial Intelligence in Healthcare

Artificial Intelligence in Healthcare PDF Author: Adam Bohr
Publisher: Academic Press
ISBN: 0128184396
Category : Computers
Languages : en
Pages : 385

Book Description
Artificial Intelligence (AI) in Healthcare is more than a comprehensive introduction to artificial intelligence as a tool in the generation and analysis of healthcare data. The book is split into two sections where the first section describes the current healthcare challenges and the rise of AI in this arena. The ten following chapters are written by specialists in each area, covering the whole healthcare ecosystem. First, the AI applications in drug design and drug development are presented followed by its applications in the field of cancer diagnostics, treatment and medical imaging. Subsequently, the application of AI in medical devices and surgery are covered as well as remote patient monitoring. Finally, the book dives into the topics of security, privacy, information sharing, health insurances and legal aspects of AI in healthcare. - Highlights different data techniques in healthcare data analysis, including machine learning and data mining - Illustrates different applications and challenges across the design, implementation and management of intelligent systems and healthcare data networks - Includes applications and case studies across all areas of AI in healthcare data

Systems Engineering and Artificial Intelligence

Systems Engineering and Artificial Intelligence PDF Author: William F. Lawless
Publisher: Springer Nature
ISBN: 3030772837
Category : Computers
Languages : en
Pages : 566

Book Description
This book provides a broad overview of the benefits from a Systems Engineering design philosophy in architecting complex systems composed of artificial intelligence (AI), machine learning (ML) and humans situated in chaotic environments. The major topics include emergence, verification and validation of systems using AI/ML and human systems integration to develop robust and effective human-machine teams—where the machines may have varying degrees of autonomy due to the sophistication of their embedded AI/ML. The chapters not only describe what has been learned, but also raise questions that must be answered to further advance the general Science of Autonomy. The science of how humans and machines operate as a team requires insights from, among others, disciplines such as the social sciences, national and international jurisprudence, ethics and policy, and sociology and psychology. The social sciences inform how context is constructed, how trust is affected when humans and machines depend upon each other and how human-machine teams need a shared language of explanation. National and international jurisprudence determine legal responsibilities of non-trivial human-machine failures, ethical standards shape global policy, and sociology provides a basis for understanding team norms across cultures. Insights from psychology may help us to understand the negative impact on humans if AI/ML based machines begin to outperform their human teammates and consequently diminish their value or importance. This book invites professionals and the curious alike to witness a new frontier open as the Science of Autonomy emerges.

Artificial Intelligence Systems Based on Hybrid Neural Networks

Artificial Intelligence Systems Based on Hybrid Neural Networks PDF Author: Michael Zgurovsky
Publisher: Springer Nature
ISBN: 303048453X
Category : Technology & Engineering
Languages : en
Pages : 527

Book Description
This book is intended for specialists as well as students and graduate students in the field of artificial intelligence, robotics and information technology. It is will also appeal to a wide range of readers interested in expanding the functionality of artificial intelligence systems. One of the pressing problems of modern artificial intelligence systems is the development of integrated hybrid systems based on deep learning. Unfortunately, there is currently no universal methodology for developing topologies of hybrid neural networks (HNN) using deep learning. The development of such systems calls for the expansion of the use of neural networks (NS) for solving recognition, classification and optimization problems. As such, it is necessary to create a unified methodology for constructing HNN with a selection of models of artificial neurons that make up HNN, gradually increasing the complexity of their structure using hybrid learning algorithms.