Next Generation Data Technologies For Collective Computational Intelligence
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Next Generation Data Technologies For Collective Computational Intelligence
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Author : Nik Bessis
language : en
Publisher: Springer
Release Date : 2011-06-29
Next Generation Data Technologies For Collective Computational Intelligence written by Nik Bessis and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-06-29 with Technology & Engineering categories.
This book focuses on next generation data technologies in support of collective and computational intelligence. The book brings various next generation data technologies together to capture, integrate, analyze, mine, annotate and visualize distributed data – made available from various community users – in a meaningful and collaborative for the organization manner. A unique perspective on collective computational intelligence is offered by embracing both theory and strategies fundamentals such as data clustering, graph partitioning, collaborative decision making, self-adaptive ant colony, swarm and evolutionary agents. It also covers emerging and next generation technologies in support of collective computational intelligence such as Web 2.0 social networks, semantic web for data annotation, knowledge representation and inference, data privacy and security, and enabling distributed and collaborative paradigms such as P2P, Grid and Cloud Computing due to the geographically dispersed and distributed nature of the data. The book aims to cover in a comprehensive manner the combinatorial effort of utilizing and integrating various next generations collaborative and distributed data technologies for computational intelligence in various scenarios. The book also distinguishes itself by assessing whether utilization and integration of next generation data technologies can assist in the identification of new opportunities, which may also be strategically fit for purpose.
Multimodal Analytics For Next Generation Big Data Technologies And Applications
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Author : Kah Phooi Seng
language : en
Publisher: Springer
Release Date : 2019-07-18
Multimodal Analytics For Next Generation Big Data Technologies And Applications written by Kah Phooi Seng and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-07-18 with Computers categories.
This edited book will serve as a source of reference for technologies and applications for multimodality data analytics in big data environments. After an introduction, the editors organize the book into four main parts on sentiment, affect and emotion analytics for big multimodal data; unsupervised learning strategies for big multimodal data; supervised learning strategies for big multimodal data; and multimodal big data processing and applications. The book will be of value to researchers, professionals and students in engineering and computer science, particularly those engaged with image and speech processing, multimodal information processing, data science, and artificial intelligence.
New Challenges In Computational Collective Intelligence
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Author : Radoslaw Katarzyniak
language : en
Publisher: Springer Science & Business Media
Release Date : 2009-08-27
New Challenges In Computational Collective Intelligence written by Radoslaw Katarzyniak and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009-08-27 with Computers categories.
Collective intelligence has become one of major research issues studied by today’s and future computer science. Computational collective intelligence is understood as this form of group intellectual activity that emerges from collaboration and compe- tion of many artificial individuals. Robotics, artificial intelligence, artificial cognition and group working try to create efficient models for collective intelligence in which it emerges from sets of actions carried out by more or less intelligent individuals. The major methodological, theoretical and practical aspects underlying computational collective intelligence are group decision making, collective action coordination, collective competition and knowledge description, transfer and integration. Obviously, the application of multiple computational technologies such as fuzzy systems, evo- tionary computation, neural systems, consensus theory, knowledge representation etc. is necessary to create new forms of computational collective intelligence and support existing ones. Three subfields of application of computational technologies to support forms of collective intelligence are of special attention to us. The first one is semantic web treated as an advanced tool that increases the collective intelligence in networking environments. The second one covers social networks modeling and analysis, where social networks are this area of in which various forms of computational collective intelligence emerges in a natural way. The third subfield relates us to agent and mul- agent systems understood as this computational and modeling paradigm which is especially tailored to capture the nature of computational collective intelligence in populations of autonomous individuals.
Implementing Computational Intelligence Techniques For Security Systems Design
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Author : Albastaki, Yousif Abdullatif
language : en
Publisher: IGI Global
Release Date : 2020-02-14
Implementing Computational Intelligence Techniques For Security Systems Design written by Albastaki, Yousif Abdullatif and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-02-14 with Computers categories.
Recently, cryptology problems, such as designing good cryptographic systems and analyzing them, have been challenging researchers. Many algorithms that take advantage of approaches based on computational intelligence techniques, such as genetic algorithms, genetic programming, and so on, have been proposed to solve these issues. Implementing Computational Intelligence Techniques for Security Systems Design is an essential research book that explores the application of computational intelligence and other advanced techniques in information security, which will contribute to a better understanding of the factors that influence successful security systems design. Featuring a range of topics such as encryption, self-healing systems, and cyber fraud, this book is ideal for security analysts, IT specialists, computer engineers, software developers, technologists, academicians, researchers, practitioners, and students.
Applied Computational Intelligence And Soft Computing In Engineering
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Author : Khalid, Saifullah
language : en
Publisher: IGI Global
Release Date : 2017-09-13
Applied Computational Intelligence And Soft Computing In Engineering written by Khalid, Saifullah and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-09-13 with Computers categories.
Although computational intelligence and soft computing are both well-known fields, using computational intelligence and soft computing in conjunction is an emerging concept. This combination can effectively be used in practical areas of various fields of research. Applied Computational Intelligence and Soft Computing in Engineering is an essential reference work featuring the latest scholarly research on the concepts, paradigms, and algorithms of computational intelligence and its constituent methodologies such as evolutionary computation, neural networks, and fuzzy logic. Including coverage on a broad range of topics and perspectives such as cloud computing, sampling in optimization, and swarm intelligence, this publication is ideally designed for engineers, academicians, technology developers, researchers, and students seeking current research on the benefits of applying computation intelligence techniques to engineering and technology.
Modern Big Data Architectures
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Author : Dominik Ryzko
language : en
Publisher: John Wiley & Sons
Release Date : 2020-03-31
Modern Big Data Architectures written by Dominik Ryzko and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-03-31 with Computers categories.
Provides an up-to-date analysis of big data and multi-agent systems The term Big Data refers to the cases, where data sets are too large or too complex for traditional data-processing software. With the spread of new concepts such as Edge Computing or the Internet of Things, production, processing and consumption of this data becomes more and more distributed. As a result, applications increasingly require multiple agents that can work together. A multi-agent system (MAS) is a self-organized computer system that comprises multiple intelligent agents interacting to solve problems that are beyond the capacities of individual agents. Modern Big Data Architectures examines modern concepts and architecture for Big Data processing and analytics. This unique, up-to-date volume provides joint analysis of big data and multi-agent systems, with emphasis on distributed, intelligent processing of very large data sets. Each chapter contains practical examples and detailed solutions suitable for a wide variety of applications. The author, an internationally-recognized expert in Big Data and distributed Artificial Intelligence, demonstrates how base concepts such as agent, actor, and micro-service have reached a point of convergence—enabling next generation systems to be built by incorporating the best aspects of the field. This book: Illustrates how data sets are produced and how they can be utilized in various areas of industry and science Explains how to apply common computational models and state-of-the-art architectures to process Big Data tasks Discusses current and emerging Big Data applications of Artificial Intelligence Modern Big Data Architectures: A Multi-Agent Systems Perspective is a timely and important resource for data science professionals and students involved in Big Data analytics, and machine and artificial learning.
Meta Learning In Computational Intelligence
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Author : Norbert Jankowski
language : en
Publisher: Springer Science & Business Media
Release Date : 2011-06-10
Meta Learning In Computational Intelligence written by Norbert Jankowski and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-06-10 with Computers categories.
Computational Intelligence (CI) community has developed hundreds of algorithms for intelligent data analysis, but still many hard problems in computer vision, signal processing or text and multimedia understanding, problems that require deep learning techniques, are open. Modern data mining packages contain numerous modules for data acquisition, pre-processing, feature selection and construction, instance selection, classification, association and approximation methods, optimization techniques, pattern discovery, clusterization, visualization and post-processing. A large data mining package allows for billions of ways in which these modules can be combined. No human expert can claim to explore and understand all possibilities in the knowledge discovery process. This is where algorithms that learn how to learnl come to rescue. Operating in the space of all available data transformations and optimization techniques these algorithms use meta-knowledge about learning processes automatically extracted from experience of solving diverse problems. Inferences about transformations useful in different contexts help to construct learning algorithms that can uncover various aspects of knowledge hidden in the data. Meta-learning shifts the focus of the whole CI field from individual learning algorithms to the higher level of learning how to learn. This book defines and reveals new theoretical and practical trends in meta-learning, inspiring the readers to further research in this exciting field.
Women In Computational Intelligence
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Author : Alice E Smith
language : en
Publisher: Springer Nature
Release Date : 2022-04-13
Women In Computational Intelligence written by Alice E Smith and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-04-13 with Technology & Engineering categories.
This book provides a breadth of innovative and impactful research in the field computational intelligence led by women investigators. Topics include intelligent data analytics, optimization of complex systems, approximation of human reasoning, robotic path planning, and intelligent control systems. These topics touch on many of the technological challenges facing the world today and these solutions by women researcher teams are valuable for their excellence and their non-traditional perspective. As an important part of the Women in Science and Engineering book series, the work highlights the contribution of women leaders in computational intelligence, inspiring women and men, girls, and boys to enter and apply themselves to this exciting multi-disciplinary field.
Computational Collective Intelligence
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Author : Manuel Núñez
language : en
Publisher: Springer
Release Date : 2015-09-09
Computational Collective Intelligence written by Manuel Núñez and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-09-09 with Computers categories.
This two-volume set (LNAI 9329 and LNAI 9330) constitutes the refereed proceedings of the 7th International Conference on Collective Intelligence, ICCCI 2014, held in Madrid, Spain, in September 2015. The 110 full papers presented were carefully reviewed and selected from 186 submissions. They are organized in topical sections such as multi-agent systems; social networks and NLP; sentiment analysis; computational intelligence and games; ontologies and information extraction; formal methods and simulation; neural networks, SMT and MIS; collective intelligence in Web systems – Web systems analysis; computational swarm intelligence; cooperative strategies for decision making and optimization; advanced networking and security technologies; IT in biomedicine; collective computational intelligence in educational context; science intelligence and data analysis; computational intelligence in financial markets; ensemble learning; big data mining and searching.
Emerging Intelligent Technologies In Industry
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Author : Dominik Ryżko
language : en
Publisher: Springer Science & Business Media
Release Date : 2011-08-20
Emerging Intelligent Technologies In Industry written by Dominik Ryżko and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-08-20 with Computers categories.
Intelligent technologies are the essential factors of innovation, and enable the industry to overcome technological limitations and explore the new frontiers. Therefore it is necessary for scientists and practitioners to cooperate and inspire each other, and use the latest research results in creating new designs and products. The idea of this book came out with the industrial workshop organized at the ISMIS conference in Warsaw, 2011. The book covers several applications of emerging, intelligent technologies in various branches of the industry. The contributions describe modern intelligent tools, algorithms and architectures, which have the potential to solve real problems, experienced by practitioners in various industry sectors. We hope this volume will show new directions for cooperation between science and industry and will facilitate efficient transfer of knowledge in the area of intelligent information systems.