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1 593 kr
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This work presents developments and applications in the area of computational intelligence, which essentially describes methods and approaches that mimic biologically intelligent behaviour in order to solve problems that have been difficult to solve by classical mathematics. Fuzzy technology, artificial neural nets and evolutionary computing are considered to be such approaches. The Editors have assembled contributions in the areas of fuzzy sets, neural sets and machine learning, as well as combinations of them (so-called hybrid methods) in the first part of the book. The second part of the book is dedicated to applications in the areas that are considered to be most relevant to computational intelligence.
536 kr
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Irrespective of whether we use economic or societal metrics, the Internet is one of the most important technical infrastructures in existence today. It will serve as a catalyst for much of our innovation and prosperity in the future. A competitive Europe will require Internet connectivity and services beyond the capabilities offered by current technologies. Future Internet research is therefore a must.The Future Internet Assembly (FIA) is a successful and unique bi-annual conference that brings together participants of over 150 projects from several distinct but interrelated areas in the EU Framework Programme 7. The 20 full papers included in this volume were selected from 40 submissions, and are preceded by a vision paper describing the FIA Roadmap. The papers have been organized into topical sections on the foundations of Future Internet, the applications of Future Internet, Smart Cities, and Future Internet infrastructures.
1 593 kr
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Advances in Computational Intelligence and Learning: Methods and Applications presents new developments and applications in the area of Computational Intelligence, which essentially describes methods and approaches that mimic biologically intelligent behavior in order to solve problems that have been difficult to solve by classical mathematics. Generally Fuzzy Technology, Artificial Neural Nets and Evolutionary Computing are considered to be such approaches.The Editors have assembled new contributions in the areas of fuzzy sets, neural sets and machine learning, as well as combinations of them (so called hybrid methods) in the first part of the book. The second part of the book is dedicated to applications in the areas that are considered to be most relevant to Computational Intelligence.