Intelligent Systems Theory Research And Innovation In Applications
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Intelligent Systems: Theory, Research and Innovation in Applications
Author: Ricardo Jardim-Goncalves
language: en
Publisher: Springer Nature
Release Date: 2020-03-03
From artificial neural net / game theory / semantic applications, to modeling tools, smart manufacturing systems, and data science research – this book offers a broad overview of modern intelligent methods and applications of machine learning, evolutionary computation, Industry 4.0 technologies, and autonomous agents leading to the Internet of Things and potentially a new technological revolution. Though chiefly intended for IT professionals, it will also help a broad range of users of future emerging technologies adapt to the new smart / intelligent wave. In separate chapters, the book highlights fourteen successful examples of recent advances in the rapidly evolving area of intelligent systems. Covering major European projects paving the way to a serious smart / intelligent collaboration, the chapters explore e.g. cyber-security issues, 3D digitization, aerial robots, and SMEs that have introduced cyber-physical production systems. Taken together, they offer unique insights into contemporary artificial intelligence and its potential for innovation.
Applications and Innovations in Intelligent Systems XIV
Author: Richard Ellis
language: en
Publisher: Springer Science & Business Media
Release Date: 2010-04-05
The papers in this volume are the refereed application papers presented at AI-2006, the Twenty-sixth SGAI International Conference on Innovative Techniques and Applications of Artificial Intelligence, held in Cambridge in December 2006. The papers present new and innovative developments in the field. The series serves as a key reference as to how AI technology has enabled organisations to solve complex problems and gain significant business benefit.
Handbook of Research on AI and ML for Intelligent Machines and Systems
The Handbook of Research on AI and ML for Intelligent Machines and Systems offers a comprehensive exploration of the pivotal role played by artificial intelligence (AI) and machine learning (ML) technologies in the development of intelligent machines. As the demand for intelligent machines continues to rise across various sectors, understanding the integration of these advanced technologies becomes paramount. While AI and ML have individually showcased their capabilities in developing robust intelligent machine systems and services, their fusion holds the key to propelling intelligent machines to a new realm of transformation. By compiling recent advancements in intelligent machines that rely on machine learning and deep learning technologies, this book serves as a vital resource for researchers, graduate students, PhD scholars, faculty members, scientists, and software developers. It offers valuable insights into the key concepts of AI and ML, covering essential security aspects, current trends, and often overlooked perspectives that are crucial for achieving comprehensive understanding. It not only explores the theoretical foundations of AI and ML but also provides guidance on applying these techniques to solve real-world problems. Unlike traditional texts, it offers flexibility through its distinctive module-based structure, allowing readers to follow their own learning paths.