Intelligent Computational Systems presents current and future developments in intelligent computational systems in a multi-disciplinary context. Readers will learn about the pervasive and ubiquitous roles of artificial intelligence (AI) and gain a perspective about the need for intelligent systems to behave rationally when interacting with humans in complex and realistic domains. This reference covers widespread applications of AI discussed in 11 chapters which cover topics such as AI and behavioral simulations, AI schools, automated negotiation, language analysis and learning, financial prediction, sensor management, Multi-agent systems, and much more. This reference work is will assist researchers, advanced-level students and practitioners in information technology and computer science fields interested in the broad applications of AI.
Applications of Computational Intelligence in Multi-Disciplinary Research provides the readers with a comprehensive handbook for applying the powerful principles, concepts, and algorithms of computational intelligence to a wide spectrum of research cases. The book covers the main approaches used in computational intelligence, including fuzzy logic, neural networks, evolutionary computation, learning theory, and probabilistic methods, all of which can be collectively viewed as soft computing. Other key approaches included are swarm intelligence and artificial immune systems. These approaches provide researchers with powerful tools for analysis and problem-solving when data is incomplete and when the problem under consideration is too complex for standard mathematics and the crisp logic approach of Boolean computing. - Provides an overview of the key methods of computational intelligence, including fuzzy logic, neural networks, evolutionary computation, learning theory, and probabilistic methods - Includes case studies and real-world examples of computational intelligence applied in a variety of research topics, including bioinformatics, biomedical engineering, big data analytics, information security, signal processing, machine learning, nanotechnology, and optimization techniques - Presents a thorough technical explanation on how computational intelligence is applied that is suitable for a wide range of multidisciplinary and interdisciplinary research
"This book explores the complex world of computational intelligence, which utilizes computational methodologies such as fuzzy logic systems, neural networks, and evolutionary computation for the purpose of managing and using data effectively to address complicated real-world problems"--
This book constitutes the refereed conference proceedings of the 11th International Conference on Multi-disciplinary Trends in Artificial Intelligence, MIWAI 2017, held in Gadong, Brunei, in November 2017. The 40 revised full papers presented were carefully reviewed and selected from 82 submissions. They are organized in the following topical sections: knowledge representation and reasoning; data mining and machine learning; deep learning and its applications; document analysis; intelligent information systems; swarm intelligence.
The development of new information and communication technologies has a considerable impact on the way humans interact with each other and their environment. The proper use of these technologies is an important consideration in the success of modern human endeavors. Multidisciplinary Perspectives on Telecommunications, Wireless Systems, and Mobile Computing explores some of the latest advances in wireless communication technologies, making use of empirical research and analytical case studies to evaluate best practices in the discipline. This book will provide insight into the next generation of information and communication technologies for developers, engineers, students, researchers, and managers in the telecommunications field.
The need for intelligent machines in areas such as medical diagnostics, biometric security systems, and image processing motivates researchers to develop and explore new techniques, algorithms, and applications in this evolving field.Cross-Disciplinary Applications of Artificial Intelligence and Pattern Recognition: Advancing Technologies provides a common platform for researchers to present theoretical and applied research findings for enhancing and developing intelligent systems. Through its discussions of advances in and applications of pattern recognition technologies and artificial intelligence, this reference highlights core concepts in biometric imagery, feature recognition, and other related fields, along with their applicability.
This is the first book to conceptualise and develop a roadmap for the adoption of cyber-physical systems (CPS) for facilities management (FM) in developing countries. It is argued that effective use of CPS can help to significantly improve issues such as extended processing time, poor data acquisition, ineffective coverage of facility maintenance history, and poor-quality control within the facilities management sector. Through a theoretical review of relevant technology adoption models and frameworks, A Roadmap for the Uptake of Cyber-Physical Systems for Facilities Management provides a clear insight into the required parameters for integrating CPS into facilities management. The book will be beneficial to relevant stakeholders who face the responsibility of facilities and construction management as it contributes to the growing demand for the adoption of digital technologies in the delivery and management of built infrastructure. Furthermore, it serves as a solid theoretical base for researchers and academics in the quest to expand the existing borderline on construction digitalisation, especially in the post-occupancy stage.
With the prevalence of digital information, IT professionals have encountered new challenges regarding data security. In an effort to address these challenges and offer solutions for securing digital information, new research on cryptology methods is essential. Multidisciplinary Perspectives in Cryptology and Information Security considers an array of multidisciplinary applications and research developments in the field of cryptology and communication security. This publication offers a comprehensive, in-depth analysis of encryption solutions and will be of particular interest to IT professionals, cryptologists, and researchers in the field.
This book addresses the challenging topic of modeling adaptive networks, which often manifest inherently complex behavior. Networks by themselves can usually be modeled using a neat, declarative, and conceptually transparent Network-Oriented Modeling approach. In contrast, adaptive networks are networks that change their structure; for example, connections in Mental Networks usually change due to learning, while connections in Social Networks change due to various social dynamics. For adaptive networks, separate procedural specifications are often added for the adaptation process. Accordingly, modelers have to deal with a less transparent, hybrid specification, part of which is often more at a programming level than at a modeling level. This book presents an overall Network-Oriented Modeling approach that makes designing adaptive network models much easier, because the adaptation process, too, is modeled in a neat, declarative, and conceptually transparent Network-Oriented Modeling manner, like the network itself. Thanks to this approach, no procedural, algorithmic, or programming skills are needed to design complex adaptive network models. A dedicated software environment is available to run these adaptive network models from their high-level specifications. Moreover, because adaptive networks are described in a network format as well, the approach can simply be applied iteratively, so that higher-order adaptive networks in which network adaptation itself is adaptive (second-order adaptation), too can be modeled just as easily. For example, this can be applied to model metaplasticity in cognitive neuroscience, or second-order adaptation in biological and social contexts. The book illustrates the usefulness of this approach via numerous examples of complex (higher-order) adaptive network models for a wide variety of biological, mental, and social processes. The book is suitable for multidisciplinary Master’s and Ph.D. students without assuming much prior knowledge, although also some elementary mathematical analysis is involved. Given the detailed information provided, it can be used as an introduction to Network-Oriented Modeling for adaptive networks. The material is ideally suited for teaching undergraduate and graduate students with multidisciplinary backgrounds or interests. Lecturers will find additional material such as slides, assignments, and software.
This book constitutes revised selected papers from the refereed proceedings of the First Human Centered Computing Conference, HCC 2014, that consolidated and further develops the successful ICPCA/SWS conferences on Pervasive Computing and the Networked World. The 54 full papers and 30 short papers presented in this volume were carefully reviewed and selected from 152 submissions. These proceedings present research papers investigating into a variety of aspects towards human centric intelligent societies. They cover the categories: infrastructure and devices; service and solution; data and knowledge; and community.
