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Books in Artificial intelligence expert systems and knowledge based systems

11-20 of 149 results in All results

Artificial Intelligence and Industry 4.0

  • 1st Edition
  • August 14, 2022
  • Aboul Ella Hassanien + 2 more
  • English
  • Paperback
    9 7 8 - 0 - 3 2 3 - 8 8 4 6 8 - 6
  • eBook
    9 7 8 - 0 - 3 2 3 - 9 0 6 3 9 - 5
Artificial Intelligence and Industry 4.0 explores recent advancements in blockchain technology and artificial intelligence (AI) as well as their crucial impacts on realizing Industry 4.0 goals. The book explores AI applications in industry including Internet of Things (IoT) and Industrial Internet of Things (IIoT) technology. Chapters explore how AI (machine learning, smart cities, healthcare, Society 5.0, etc.) have numerous potential applications in the Industry 4.0 era. This book is a useful resource for researchers and graduate students in computer science researching and developing AI and the IIoT.

Data Mining

  • 4th Edition
  • July 2, 2022
  • Jiawei Han + 2 more
  • English
  • Paperback
    9 7 8 - 0 - 1 2 - 8 1 1 7 6 0 - 6
  • eBook
    9 7 8 - 0 - 1 2 - 8 1 1 7 6 1 - 3
Data Mining: Concepts and Techniques, Fourth Edition introduces concepts, principles, and methods for mining patterns, knowledge, and models from various kinds of data for diverse applications. Specifically, it delves into the processes for uncovering patterns and knowledge from massive collections of data, known as knowledge discovery from data, or KDD. It focuses on the feasibility, usefulness, effectiveness, and scalability of data mining techniques for large data sets. After an introduction to the concept of data mining, the authors explain the methods for preprocessing, characterizing, and warehousing data. They then partition the data mining methods into several major tasks, introducing concepts and methods for mining frequent patterns, associations, and correlations for large data sets; data classificcation and model construction; cluster analysis; and outlier detection. Concepts and methods for deep learning are systematically introduced as one chapter. Finally, the book covers the trends, applications, and research frontiers in data mining.

Blockchain Technology for Emerging Applications

  • 1st Edition
  • May 21, 2022
  • SK Hafizul Islam + 3 more
  • English
  • Paperback
    9 7 8 - 0 - 3 2 3 - 9 0 1 9 3 - 2
  • eBook
    9 7 8 - 0 - 3 2 3 - 9 0 1 9 4 - 9
Blockchain Technology for Emerging Applications: A Comprehensive Approach explores recent theories and applications of the execution of blockchain technology. Chapters look at a wide range of application areas, including healthcare, digital physical frameworks, web of-things, smart transportation frameworks, interruption identification frameworks, ballot-casting, architecture, smart urban communities, and digital rights administration. The book addresses the engineering, plan objectives, difficulties, constraints, and potential answers for blockchain-based frameworks. It also looks at blockchain-based design perspectives of these intelligent architectures for evaluating and interpreting real-world trends. Chapters expand on different models which have shown considerable success in dealing with an extensive range of applications, including their ability to extract complex hidden features and learn efficient representation in unsupervised environments for blockchain security pattern analysis.

Recent Trends in Computational Intelligence Enabled Research

  • 1st Edition
  • July 31, 2021
  • Siddhartha Bhattacharyya + 4 more
  • English
  • Paperback
    9 7 8 - 0 - 1 2 - 8 2 2 8 4 4 - 9
  • eBook
    9 7 8 - 0 - 3 2 3 - 8 5 1 7 9 - 4
The field of computational intelligence has grown tremendously over that past five years, thanks to evolving soft computing and artificial intelligent methodologies, tools and techniques for envisaging the essence of intelligence embedded in real life observations. Consequently, scientists have been able to explain and understand real life processes and practices which previously often remain unexplored by virtue of their underlying imprecision, uncertainties and redundancies, and the unavailability of appropriate methods for describing the incompleteness and vagueness of information represented. With the advent of the field of computational intelligence, researchers are now able to explore and unearth the intelligence, otherwise insurmountable, embedded in the systems under consideration. Computational Intelligence is now not limited to only specific computational fields, it has made inroads in signal processing, smart manufacturing, predictive control, robot navigation, smart cities, and sensor design to name a few.   Recent Trends in Computational Intelligence Enabled Research: Theoretical Foundations and Applications explores the use of this computational paradigm across a wide range of applied domains which handle meaningful information. Chapters investigate a broad spectrum of the applications of computational intelligence across different platforms and disciplines, expanding our knowledge base of various research initiatives in this direction. This volume aims to bring together researchers, engineers, developers and practitioners from academia and industry working in all major areas and interdisciplinary areas of computational intelligence, communication systems, computer networks, and soft computing. 

Machine Learning, Big Data, and IoT for Medical Informatics

  • 1st Edition
  • June 13, 2021
  • Pardeep Kumar + 3 more
  • English
  • Paperback
    9 7 8 - 0 - 1 2 - 8 2 1 7 7 7 - 1
  • eBook
    9 7 8 - 0 - 1 2 - 8 2 1 7 8 1 - 8
Machine Learning, Big Data, and IoT for Medical Informatics focuses on the latest techniques adopted in the field of medical informatics. In medical informatics, machine learning, big data, and IOT-based techniques play a significant role in disease diagnosis and its prediction. In the medical field, the structure of data is equally important for accurate predictive analytics due to heterogeneity of data such as ECG data, X-ray data, and image data. Thus, this book focuses on the usability of machine learning, big data, and IOT-based techniques in handling structured and unstructured data. It also emphasizes on the privacy preservation techniques of medical data. This volume can be used as a reference book for scientists, researchers, practitioners, and academicians working in the field of intelligent medical informatics. In addition, it can also be used as a reference book for both undergraduate and graduate courses such as medical informatics, machine learning, big data, and IoT.  

The Era of Artificial Intelligence, Machine Learning, and Data Science in the Pharmaceutical Industry

  • 1st Edition
  • April 23, 2021
  • Stephanie K. Ashenden
  • English
  • Paperback
    9 7 8 - 0 - 1 2 - 8 2 0 0 4 5 - 2
  • eBook
    9 7 8 - 0 - 1 2 - 8 2 0 4 4 9 - 8
The Era of Artificial Intelligence, Machine Learning and Data Science in the Pharmaceutical Industry examines the drug discovery process, assessing how new technologies have improved effectiveness. Artificial intelligence and machine learning are considered the future for a wide range of disciplines and industries, including the pharmaceutical industry. In an environment where producing a single approved drug costs millions and takes many years of rigorous testing prior to its approval, reducing costs and time is of high interest. This book follows the journey that a drug company takes when producing a therapeutic, from the very beginning to ultimately benefitting a patient’s life. This comprehensive resource will be useful to those working in the pharmaceutical industry, but will also be of interest to anyone doing research in chemical biology, computational chemistry, medicinal chemistry and bioinformatics.

Artificial Intelligence for the Internet of Everything

  • 1st Edition
  • February 21, 2019
  • William Lawless + 4 more
  • English
  • Paperback
    9 7 8 - 0 - 1 2 - 8 1 7 6 3 6 - 8
  • eBook
    9 7 8 - 0 - 1 2 - 8 1 7 6 3 7 - 5
Artificial Intelligence for the Internet of Everything considers the foundations, metrics and applications of IoE systems. It covers whether devices and IoE systems should speak only to each other, to humans or to both. Further, the book explores how IoE systems affect targeted audiences (researchers, machines, robots, users) and society, as well as future ecosystems. It examines the meaning, value and effect that IoT has had and may have on ordinary life, in business, on the battlefield, and with the rise of intelligent and autonomous systems. Based on an artificial intelligence (AI) perspective, this book addresses how IoE affects sensing, perception, cognition and behavior. Each chapter addresses practical, measurement, theoretical and research questions about how these “things” may affect individuals, teams, society or each other. Of particular focus is what may happen when these “things” begin to reason, communicate and act autonomously on their own, whether independently or interdependently with other “things”.

Geographical and Fingerprinting Data for Positioning and Navigation Systems

  • 1st Edition
  • September 14, 2018
  • Jordi Conesa + 3 more
  • English
  • Paperback
    9 7 8 - 0 - 1 2 - 8 1 3 1 8 9 - 3
  • eBook
    9 7 8 - 0 - 1 2 - 8 1 3 1 9 0 - 9
Geographical and Fingerprinting Data for Positioning and Navigation Systems: Challenges, Experiences and Technology Roadmap explores the state-of-the -art software tools and innovative strategies to provide better understanding of positioning and navigation in indoor environments using fingerprinting techniques. The book provides the different problems and challenges of indoor positioning and navigation services and shows how fingerprinting can be used to address such necessities. This advanced publication provides the useful references educational institutions, industry, academic researchers, professionals, developers and practitioners need to apply, evaluate and reproduce this book’s contributions. The readers will learn how to apply the necessary infrastructure to provide fingerprinting services and scalable environments to deal with fingerprint data.

Computational Intelligence for Multimedia Big Data on the Cloud with Engineering Applications

  • 1st Edition
  • August 21, 2018
  • Arun Kumar Sangaiah + 2 more
  • English
  • Paperback
    9 7 8 - 0 - 1 2 - 8 1 3 3 1 4 - 9
  • eBook
    9 7 8 - 0 - 1 2 - 8 1 3 3 2 7 - 9
Computational Intelligence for Multimedia Big Data on the Cloud with Engineering Applications covers timely topics, including the neural network (NN), particle swarm optimization (PSO), evolutionary algorithm (GA), fuzzy sets (FS) and rough sets (RS), etc. Furthermore, the book highlights recent research on representative techniques to elaborate how a data-centric system formed a powerful platform for the processing of cloud hosted multimedia big data and how it could be analyzed, processed and characterized by CI. The book also provides a view on how techniques in CI can offer solutions in modeling, relationship pattern recognition, clustering and other problems in bioengineering. It is written for domain experts and developers who want to understand and explore the application of computational intelligence aspects (opportunities and challenges) for design and development of a data-centric system in the context of multimedia cloud, big data era and its related applications, such as smarter healthcare, homeland security, traffic control trading analysis and telecom, etc. Researchers and PhD students exploring the significance of data centric systems in the next paradigm of computing will find this book extremely useful.

Big Data Analytics for Sensor-Network Collected Intelligence

  • 1st Edition
  • February 2, 2017
  • Hui-Huang Hsu + 2 more
  • English
  • Paperback
    9 7 8 - 0 - 1 2 - 8 0 9 3 9 3 - 1
  • eBook
    9 7 8 - 0 - 1 2 - 8 0 9 6 2 5 - 3
Big Data Analytics for Sensor-Network Collected Intelligence explores state-of-the-art methods for using advanced ICT technologies to perform intelligent analysis on sensor collected data. The book shows how to develop systems that automatically detect natural and human-made events, how to examine people’s behaviors, and how to unobtrusively provide better services. It begins by exploring big data architecture and platforms, covering the cloud computing infrastructure and how data is stored and visualized. The book then explores how big data is processed and managed, the key security and privacy issues involved, and the approaches used to ensure data quality. In addition, readers will find a thorough examination of big data analytics, analyzing statistical methods for data analytics and data mining, along with a detailed look at big data intelligence, ubiquitous and mobile computing, and designing intelligence system based on context and situation. Indexing: The books of this series are submitted to EI-Compendex and SCOPUS