Artificial Intelligence Theory, Models, and Applications
Artificial Intelligence Theory, Models, and Applications

Author: P Kaliraj

Publisher: CRC Press

Published: 2021-10-21

Total Pages: 507

ISBN-13: 1000460606

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This book examines the fundamentals and technologies of Artificial Intelligence (AI) and describes their tools, challenges, and issues. It also explains relevant theory as well as industrial applications in various domains, such as healthcare, economics, education, product development, agriculture, human resource management, environmental management, and marketing. The book is a boon to students, software developers, teachers, members of boards of studies, and researchers who need a reference resource on artificial intelligence and its applications and is primarily intended for use in courses offered by higher education institutions that strive to equip their graduates with Industry 4.0 skills. FEATURES: Gender disparity in the enterprises involved in the development of AI-based software development as well as solutions to eradicate such gender bias in the AI world A general framework for AI in environmental management, smart farming, e-waste management, and smart energy optimization The potential and application of AI in medical imaging as well as the challenges of AI in precision medicine AI’s role in the diagnosis of various diseases, such as cancer and diabetes The role of machine learning models in product development and statistically monitoring product quality Machine learning to make robust and effective economic policy decisions Machine learning and data mining approaches to provide better video indexing mechanisms resulting in better searchable results ABOUT THE EDITORS: Prof. Dr. P. Kaliraj is Vice Chancellor at Bharathiar University, Coimbatore, India. Prof. Dr. T. Devi is Professor and Head of the Department of Computer Applications, Bharathiar University, Coimbatore, India.

Decision Theory Models for Applications in Artificial Intelligence: Concepts and Solutions
Decision Theory Models for Applications in Artificial Intelligence: Concepts and Solutions

Author: Sucar, L. Enrique

Publisher: IGI Global

Published: 2011-10-31

Total Pages: 444

ISBN-13: 160960167X

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One of the goals of artificial intelligence (AI) is creating autonomous agents that must make decisions based on uncertain and incomplete information. The goal is to design rational agents that must take the best action given the information available and their goals. Decision Theory Models for Applications in Artificial Intelligence: Concepts and Solutions provides an introduction to different types of decision theory techniques, including MDPs, POMDPs, Influence Diagrams, and Reinforcement Learning, and illustrates their application in artificial intelligence. This book provides insights into the advantages and challenges of using decision theory models for developing intelligent systems.

Applications of Artificial Intelligence in Process Systems Engineering
Applications of Artificial Intelligence in Process Systems Engineering

Author: Jingzheng Ren

Publisher: Elsevier

Published: 2021-06-05

Total Pages: 542

ISBN-13: 012821743X

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Applications of Artificial Intelligence in Process Systems Engineering offers a broad perspective on the issues related to artificial intelligence technologies and their applications in chemical and process engineering. The book comprehensively introduces the methodology and applications of AI technologies in process systems engineering, making it an indispensable reference for researchers and students. As chemical processes and systems are usually non-linear and complex, thus making it challenging to apply AI methods and technologies, this book is an ideal resource on emerging areas such as cloud computing, big data, the industrial Internet of Things and deep learning. With process systems engineering's potential to become one of the driving forces for the development of AI technologies, this book covers all the right bases. - Explains the concept of machine learning, deep learning and state-of-the-art intelligent algorithms - Discusses AI-based applications in process modeling and simulation, process integration and optimization, process control, and fault detection and diagnosis - Gives direction to future development trends of AI technologies in chemical and process engineering

Artificial Intelligence: Theories, Models and Applications
Artificial Intelligence: Theories, Models and Applications

Author:

Publisher:

Published: 2008

Total Pages: 0

ISBN-13: 9788354087885

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This book constitutes the refereed proceedings of the 5th Hellenic Conference on Artificial Intelligence, SETN 2008, held at Syros, Greece in October 2008. The 27 revised full papers together with 17 revised short papers were carefully reviewed and selected from 76 submissions. The papers address any area of artificial intelligence; particular fields of interest include: Adaptive Systems, AI and Creativity, AI rchitectures, Artificial Life, Autonomous Systems, Data Mining and Knowledge Discovery, Hybrid Intelligent Systems & Methods, Intelligent Agents, Multi-agent Systems, Intelligent Distributed Systems, Intelligent Information Retrieval, Intelligent/Natural Interactivity, Intelligent Virtual Environments, Knowledge Representation and Reasoning, Logic Programming, Knowledge-Based Systems, Machine Learning, Neural Nets, Genetic Algorithms, Natural Language Processing, Planning and Scheduling, Problem Solving, Constraint Satisfaction, Robotics, Machine Vision, Machine Sensing.

Artificial Intelligence: Models, Algorithms and Applications
Artificial Intelligence: Models, Algorithms and Applications

Author: Terje Solsvik Kristensen

Publisher: Bentham Science Publishers

Published: 2021-05-31

Total Pages: 176

ISBN-13: 1681088274

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Artificial Intelligence: Models, Algorithms and Applications presents focused information about applications of artificial intelligence (AI) in different areas to solve complex problems. The book presents 8 chapters that demonstrate AI based systems for vessel tracking, mental health assessment, radiology, instrumentation, business intelligence, education and criminology. The book concludes with a chapter on mathematical models of neural networks. The book serves as an introductory book about AI applications at undergraduate and graduate levels and as a reference for industry professionals working with AI based systems.

Artificial Intelligence: Theories, Models and Applications
Artificial Intelligence: Theories, Models and Applications

Author: Ilias Maglogiannis

Publisher: Springer

Published: 2012-05-26

Total Pages: 399

ISBN-13: 3642304486

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This book constitutes the proceedings of the 7th Hellenic Conference on Artificial Intelligence, SETN 2012, held in Lamia, Greece, in May 2012. The 47 contributions included in this volume were carefully reviewed and selected from 81 submissions. They deal with emergent topics of artificial intelligence and come from the SETN main conference as well as from the following special sessions on advancing translational biological research through the incorporation of artificial intelligence methodologies; artificial intelligence in bioinformatics; intelligent annotation of digital content; intelligent, affective, and natural interfaces; and unified multimedia knowledge representation and processing.

Artificial Intelligence: Theories, Models and Applications
Artificial Intelligence: Theories, Models and Applications

Author: John Darzentas

Publisher: Springer

Published: 2008-09-22

Total Pages: 457

ISBN-13: 3540878815

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Artificial intelligence (AI) is a dynamic field that is constantly expanding into new application areas, discovering new research challenges and facilitating the devel- ment of innovative products. Today’s information overload and rapid technological advancement raise needs for effective management of the complexity and heteroge- ity of knowledge, for intelligent and adaptable man–machine interfaces and for pr- ucts and applications that can learn and take decisions by themselves. Although the mystery of human-level intelligence has just started to be uncovered in various int- disciplinary fields, AI is inspired by the respective scientific areas to explore certain theories and models that will provide the methods and techniques to design and - velop human-centered applications that address the above-mentioned needs. This volume contains papers selected for presentation at the 5th Hellenic Conference on Artificial Intelligence (SETN 2008), the official meeting of the Hellenic Society for Artificial Intelligence (EETN). Previous conferences were held at the University of Piraeus (1996), at the Aristotle University of Thessaloniki (2002), at the University of the Aegean (2004) and at the Institute of Computer Science at FORTH (Foundation for Research and Technology - Hellas) and the University of Crete (2006).

Interpretable Machine Learning
Interpretable Machine Learning

Author: Christoph Molnar

Publisher: Lulu.com

Published: 2020

Total Pages: 320

ISBN-13: 0244768528

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This book is about making machine learning models and their decisions interpretable. After exploring the concepts of interpretability, you will learn about simple, interpretable models such as decision trees, decision rules and linear regression. Later chapters focus on general model-agnostic methods for interpreting black box models like feature importance and accumulated local effects and explaining individual predictions with Shapley values and LIME. All interpretation methods are explained in depth and discussed critically. How do they work under the hood? What are their strengths and weaknesses? How can their outputs be interpreted? This book will enable you to select and correctly apply the interpretation method that is most suitable for your machine learning project.

Advances in Artificial Intelligence: Theories, Models, and Applications
Advances in Artificial Intelligence: Theories, Models, and Applications

Author: Stasinos Konstantopoulos

Publisher: Springer Science & Business Media

Published: 2010-04-23

Total Pages: 433

ISBN-13: 3642128416

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This volume constitutes the refereed proceedings of the 6th Hellenic Conference on Artificial Intelligence, SETN 2010, held in Athens, Greece, in May 2010. The 28 revised full papers and 22 revised short papers presented were carefully reviewed and selected from 83 submissions. The topics include but are not restricted to adaptive systems; AI and creativity; AI architectures; artificial life; autonomous systems; data mining and knowledge discovery; hybrid intelligent systems & methods; intelligent agents, multi-agent systems; intelligent distributed systems; intelligent information retrieval; intelligent/natural interactivity, intelligent virtual environments; knowledge representation and reasoning, logic programming; knowledge-based systems; machine learning, neural nets, genetic algorithms; natural language processing; planning and scheduling; problem solving, constraint satisfaction; robotics, machine vision, machine sensing.

Application of Artificial Intelligence to Assessment
Application of Artificial Intelligence to Assessment

Author: Hong Jiao

Publisher: IAP

Published: 2020-03-01

Total Pages: 218

ISBN-13: 1641139536

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The general theme of this book is to present the applications of artificial intelligence (AI) in test development. In particular, this book includes research and successful examples of using AI technology in automated item generation, automated test assembly, automated scoring, and computerized adaptive testing. By utilizing artificial intelligence, the efficiency of item development, test form construction, test delivery, and scoring could be dramatically increased. Chapters on automated item generation offer different perspectives related to generating a large number of items with controlled psychometric properties including the latest development of using machine learning methods. Automated scoring is illustrated for different types of assessments such as speaking and writing from both methodological aspects and practical considerations. Further, automated test assembly is elaborated for the conventional linear tests from both classical test theory and item response theory perspectives. Item pool design and assembly for the linear-on-the-fly tests elaborates more complications in practice when test security is a big concern. Finally, several chapters focus on computerized adaptive testing (CAT) at either item or module levels. CAT is further illustrated as an effective approach to increasing test-takers’ engagement in testing. In summary, the book includes both theoretical, methodological, and applied research and practices that serve as the foundation for future development. These chapters provide illustrations of efforts to automate the process of test development. While some of these automation processes have become common practices such as automated test assembly, automated scoring, and computerized adaptive testing, some others such as automated item generation calls for more research and exploration. When new AI methods are emerging and evolving, it is expected that researchers can expand and improve the methods for automating different steps in test development to enhance the automation features and practitioners can adopt quality automation procedures to improve assessment practices.