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Witold Pedrycz - One of the best experts on this subject based on the ideXlab platform.

  • Computational Intelligence: Retrospection and Future
    Journal of Advanced Computational Intelligence and Intelligent Informatics, 2017
    Co-Authors: Witold Pedrycz
    Abstract:

    This study is aimed at a brief, carefully focused retrospective view at the Computational Intelligence – a paradigm supporting the analysis and synthesis of intelligent systems. We stress the reason behind the emergence of this discipline and identify its main features. We highlight the synergistic aspects of Computational Intelligence arising from an interaction and collaboration of fuzzy sets, neural networks, and evolutionary optimization. Some promising directions of future fundamental and applied research are also identified.

  • Computational Intelligence and Quantitative Software Engineering - Computational Intelligence: An Introduction
    Computational Intelligence and Quantitative Software Engineering, 2016
    Co-Authors: Witold Pedrycz
    Abstract:

    From the Publisher: Computational Intelligence: An Introduction consists of a highly readable and systematic exposure of the fundamentals of Computational Intelligence, along with the coherent presentation of sound and comprehensive analysis and design practices. Provides a balanced introduction to Computational Intelligence, emphasizing equally the important analysis and design aspects of the emerging technology; text is organized in a way that allows for the easy use of the book as a basic course material; presents a design-oriented approach toward the use of Computational Intelligence; organizes exercises and problems of different levels of difficulty following each chapter; and complete algorithms are presented in a structured fashion, easing understanding and implementation.

  • Computational Intelligence: An introduction
    Studies in Computational Intelligence, 2016
    Co-Authors: Witold Pedrycz, Alberto Sillitti, Giancarlo Succi
    Abstract:

    Computational Intelligence: An Introduction, Second Edition offers an in-depth exploration into the adaptive mechanisms that enable intelligent behaviour in complex and changing environments. The main focus of this text is centred on the Computational modelling of biological and natural intelligent systems, encompassing swarm Intelligence, fuzzy systems, artificial neutral networks, artificial immune systems and evolutionary computation. Engelbrecht provides readers with a wide knowledge of Computational Intelligence (CI) paradigms and algorithms; inviting readers to implement and problem solve real-world, complex problems within the CI development framework. This implementation framework will enable readers to tackle new problems without any difficulty through a single Java class as part of the CI library. Key features of this second edition include: A tutorial, hands-on based presentation of the material. State-of-the-art coverage of the most recent developments in Computational Intelligence with more elaborate discussions on Intelligence and artificial Intelligence (AI). New discussion of Darwinian evolution versus Lamarckian evolution, also including swarm robotics, hybrid systems and artificial immune systems. A section on how to perform empirical studies; topics including statistical analysis of stochastic algorithms, and an open source library of CI algorithms. Tables, illustrations, graphs, examples, assignments, Java code implementing the algorithms, and a complete CI implementation and experimental framework. Computational Intelligence: An Introduction, Second Edition is essential reading for third and fourth year undergraduate and postgraduate students studying CI. The first edition has been prescribed by a number of overseas universities and is thus a valuable teaching tool. In addition, it will also be a useful resource for researchers in Computational Intelligence and Artificial Intelligence, as well as engineers, statisticians, operational researchers, and bioinformaticians with an interest in applying AI or CI to solve problems in their domains. Check out http://www.ci.cs.up.ac.za for examples, assignments and Java code implementing the algorithms.

  • Computational Intelligence and Quantitative Software Engineering - Computational Intelligence and Quantitative Software Engineering
    Studies in Computational Intelligence, 2016
    Co-Authors: Witold Pedrycz, Giancarlo Succi, Alberto Sillitti
    Abstract:

    In a down-to-the earth manner, the volume lucidly presents how the fundamental concepts, methodology, and algorithms of Computational Intelligence are efficiently exploited in Software Engineering and opens up a novel and promising avenue of a comprehensive analysis and advanced design of software artifacts. It shows how the paradigm and the best practices of Computational Intelligence can be creatively explored to carry out comprehensive software requirement analysis, support design, testing, and maintenance. Software Engineering is an intensive knowledge-based endeavor of inherent human-centric nature, which profoundly relies on acquiring semiformal knowledge and then processing it to produce a running system. The knowledge spans a wide variety of artifacts, from requirements, captured in the interaction with customers, to design practices, testing, and code management strategies, which rely on the knowledge of the running system. This volume consists of contributions written by widely acknowledged experts in the field who reveal how the Software Engineering benefits from the key foundations and synergistically existing technologies of Computational Intelligence being focused on knowledge representation, learning mechanisms, and population-based global optimization strategies. This book can serve as a highly useful reference material for researchers, software engineers and graduate students and senior undergraduate students in Software Engineering and its sub-disciplines, Internet engineering, Computational Intelligence, management, operations research, and knowledge-based systems.

  • Springer Handbook of Computational Intelligence - Springer Handbook of Computational Intelligence
    2015
    Co-Authors: Janusz Kacprzyk, Witold Pedrycz
    Abstract:

    The Springer Handbook for Computational Intelligence is the first book covering the basics, the state-of-the-art and important applications of the dynamic and rapidly expanding discipline of Computational Intelligence. This comprehensive handbook makes readers familiar with a broad spectrum of approaches to solve various problems in science and technology. Possible approaches include, for example, those being inspired by biology, living organisms and animate systems. Content is organized in seven parts: foundations; fuzzy logic; rough sets; evolutionary computation; neural networks; swarm Intelligence and hybrid Computational Intelligence systems. Each Part is supervised by its own Part Editor(s) so that high-quality content as well as completeness are assured.

Ruili Wang - One of the best experts on this subject based on the ideXlab platform.

  • Computational Intelligence for Information Security: A Survey
    IEEE Transactions on Emerging Topics in Computational Intelligence, 2020
    Co-Authors: Ruili Wang
    Abstract:

    Information security is the set of processes that protect information away from unauthorized access, disclosure, replication, modification, or destruction. Recently, more and more real-world systems such as smart cities, wireless sensor networks, biometric systems, and surveillance, require the assurances of information security. Thus, many different techniques based on Computational Intelligence have been developed for information security in the past decades. However, there are no comprehensive surveys that summarize these techniques. Thus, this paper reviewed Computational Intelligence approaches published in journals and conferences for information security in the last decade. This paper is a brief, but a comprehensive survey to review numerous Computational Intelligence approaches and applications for information security. A discussion of the existing challenges of Computational Intelligence approaches and techniques for information security is also presented.

Antoni Martínez-ballesté - One of the best experts on this subject based on the ideXlab platform.

  • Computational Intelligence for Privacy and Security - Computational Intelligence for privacy and security: Introduction
    Computational Intelligence for Privacy and Security, 2012
    Co-Authors: David Elizondo, Agusti Solanas, Antoni Martínez-ballesté
    Abstract:

    The field of Computational Intelligence relates to the development of biologically inspired Computational algorithms. The field includes three main areas: neural networks, genetic algorithms and fuzzy systems. This book presents recent research on the application of Computational Intelligence models, algorithms and technologies to the areas of Privacy and Security. These areas are of vital importance to the safety, prosperity and future development of the world’s economy, underpin trust in all areas of commerce, defence, security and good governance, and are central to the daily lives of many people.

  • Computational Intelligence for Privacy and Security - Computational Intelligence for Privacy and Security
    Studies in Computational Intelligence, 2012
    Co-Authors: David Elizondo, Agusti Solanas, Antoni Martínez-ballesté
    Abstract:

    The book is a collection of invited papers on Computational Intelligence for Privacy and Security. The majority of the chapters are extended versions of works presented at the special session on Computational Intelligence for Privacy and Security of the International Joint Conference on Neural Networks (IJCNN-2010) held July 2010 in Barcelona, Spain. The book is devoted to Computational Intelligence for Privacy and Security. It provides an overview of the most recent advances on the Computational Intelligence techniques being developed for Privacy and Security. The book will be of interest to researchers in industry and academics and to post-graduate students interested in the latest advances and developments in the field of Computational Intelligence for Privacy and Security.

Manuel Graña - One of the best experts on this subject based on the ideXlab platform.

  • Computational Intelligence in Remote Sensing: An Editorial
    Sensors (Basel Switzerland), 2020
    Co-Authors: Manuel Graña, Michal Wozniak, Sebastián A. Ríos, Javier De Lope
    Abstract:

    Computational Intelligence is a very active and fruitful research of artificial Intelligence with a broad spectrum of applications. Remote sensing data has been a salient field of application of Computational Intelligence algorithms, both for the exploitation of the data and for the research/development of new data analysis tools. In this editorial paper we provide the setting of the special issue "Computational Intelligence in Remote Sensing" and an overview of the published papers. The 11 accepted and published papers cover a wide spectrum of applications and Computational tools that we try to summarize and put in perspective in this editorial paper.

  • Computational Intelligence for Remote Sensing - Computational Intelligence for Remote Sensing
    Studies in Computational Intelligence, 2008
    Co-Authors: Manuel Graña, Richard J. Duro
    Abstract:

    This book is a composition of different points of view regarding the application of Computational Intelligence techniques and methods to Remote Sensing data and applications. It is the general consensus that classification, its related data processing, and global optimization methods are core topics of Computational Intelligence. Much of the content of the book is devoted to image segmentation and recognition, using diverse tools from different areas of the Computational Intelligence field, ranging from Artificial Neural Networks to Markov Random Field modeling. The book covers a broad range of topics, starting from the hardware design of hyperspectral sensors, and data handling problems, namely data compression and watermarking issues, as well as autonomous web services. The main contents of the book are devoted to image analysis and efficient (parallel) implementations of these analysis techniques. The classes of images dealt with throughout the book are mostly multispectral-hyperspectral images, though there are some instances of processing Synthetic Aperture Radar images.

Athanasios V. Vasilakos - One of the best experts on this subject based on the ideXlab platform.

  • SAC - Application of Computational Intelligence techniques in active networks
    Proceedings of the 2001 ACM symposium on Applied computing - SAC '01, 2001
    Co-Authors: Athanasios V. Vasilakos, Kostas G. Anagnostakis, Witold Pedrycz
    Abstract:

    Computational Intelligence techniques have been successfully used for solving control problems in packet-switching network architectures. The introduction of active networking adds a high degree of flexibility in customizing the network infrastructure and introducing new functionality. Therefore, there is a clear need for investigating both the applicability of Computational Intelligence techniques in this new networking environment, as well as the provisions of active networking technology that Computational Intelligence techniques can exploit for improved operation. We report on the characteristics of these technologies, their synergy and on outline recent efforts in the design of a Computational Intelligence toolkit and its application to routing on a novel active networking environment.

  • Application of Computational Intelligence techniques in active networks
    Soft Computing, 2001
    Co-Authors: Athanasios V. Vasilakos, Kostas G. Anagnostakis, Witold Pedrycz
    Abstract:

    Computational Intelligence techniques have been successfully used for solving control problems in packet-switching network architectures. The introduction of active networking adds a high degree of flexibility in customizing the network infrastructure and introducing new functionality. Therefore, there is a clear need for investigating both the applicability of Computational Intelligence techniques in this new networking environment, as well as the provisions of active networking technology that Computational Intelligence techniques can exploit for improved operation. We report on the characteristics of these technologies, their synergy and on outline recent efforts in the design of a Computational Intelligence toolkit and its application to routing on a novel active networking environment.

  • Application of Computational Intelligence techniques in active networks
    Applications and Science of Neural Networks Fuzzy Systems and Evolutionary Computation III, 2000
    Co-Authors: Athanasios V. Vasilakos, Kostas G. Anagnostakis, Witold Pedrycz
    Abstract:

    Computational Intelligence techniques have been successfully applied for solving control problems in modern networking architectures such as ATM and the Internet. The introduction of active networks offers a high level of flexibility in customizing the network infrastructure and introducing new functionality. There is a clear need for revisiting both the applicability of Computational Intelligence techniques in this new networking environment, as well as the provisions of active networking technology that Computational Intelligence techniques can exploit for improved operation. We elaborate on the characteristics of these technologies, their synergy and report on our study with applying Computational Intelligence techniques for improved routing on a novel active network resource management architecture.

  • Computational Intelligence in Telecommunications Networks - Computational Intelligence in Telecommunications Networks
    2000
    Co-Authors: Witold Pedrycz, Athanasios V. Vasilakos
    Abstract:

    From the Publisher: Telecommunications has evolved and grown at an explosive rate inrecent years and will undoubtedly continue to do so. As its functions, applications, and technology grow, it becomes increasingly complex and difficult, if not impossible, to meet the demands of a global network using conventional computing technologies. Computational Intelligence (CI) is the technology of the future-and the future is now. Computational Intelligence in Telecommunications Networks offers the first in-depth look at the rapid progress of CI technology and shows its importance in solving the crucial problems of future telecommunications networks. It covers a broad range of topics, from Call Admission Control, congestion control, and QoS-routing for ATM networks, to network design and management, optical, mobile, and active networks, and Intelligent Mobile Agents. Today's telecommunications professionals need a working knowledge of CI to exploit its potential to overcome emerging challenges. The CI community must become acquainted with those challenges to take advantage of the enormous opportunities the telecommunications field offers. This text meets both those needs, clearly, concisely, and with a depth certain to inspire further theoretical and practical advances.