Advances in computational intelligence

Lecture Notes in Computer Science, 2011

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Fuzzy Optimization and Decision Making, 2008

Computational Intelligence (CI) is an emerging field covering a highly interdisciplinary methodological framework that is useful for supporting the design, analysis, and deployment of intelligent systems. According to Bezdek (1994), ".. . a system is computationally intelligent when it: deals only with numerical (low-level) data, has a pattern recognition component, and does not use knowledge in the AI sense; and additionally when it (begins to) exhibit (i) computational adaptivity; (ii) computational fault tolerance; (iii) speed approaching human-like turnaround, and (iv) error rates that approximate human performance. . .". Indeed, CI involves innovative models with a high level of machine learning quotient that combine elements of learning, adaptation, and evaluation. Examples of CI paradigms include fuzzy computing, neural computing, evolutionary computing, probabilistic computing, rough set theory, knowledge-based systems, adaptive learning algorithms, and hybrids of these paradigms. These techniques can be applied to a wide range of problems including optimization, decision making, information processing, pattern recognition, and intelligent data analysis. In this special issue, a number of papers that address theoretical advances as well as practical applications of various CI techniques are presented. The first two papers cover investigation into fuzzy measures and intelligent data analysis. The next two

Springer eBooks, 2021

The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. The publisher, the authors and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication. Neither the publisher nor the authors or the editors give a warranty, expressed or implied, with respect to the material contained herein or for any errors or omissions that may have been made. The publisher remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Springer , 2020

The series "Studies in Computational Intelligence" (SCI) publishes new developments and advances in the various areas of computational intelligence-quickly and with a high quality. The intent is to cover the theory, applications, and design methods of computational intelligence, as embedded in the fields of engineering, computer science, physics and life sciences, as well as the methodologies behind them. The series contains monographs, lecture notes and edited volumes in computational intelligence spanning the areas of neural networks, connectionist systems, genetic algorithms, evolutionary computation, artificial intelligence, cellular automata, self-organizing systems, soft computing, fuzzy systems, and hybrid intelligent systems. Of particular value to both the contributors and the readership are the short publication timeframe and the worldwide distribution, which enable both wide and rapid dissemination of research output.

IEEE Computational Intelligence Magazine, 2011

This book is about methods and techniques popularly employed in the field of computational intelligence (CI). According to [1], CI can be broadly defined as ??the branch of science studying problems for which there are no effective computational algorithms??. These include problems such as extracting meaning from perception, understanding language, solving illdefined vision tasks, for which formulating exact, analytical algorithms is either not possible or computationally very demanding. Seeing from this viewpoint, it is instructive to define CI based on the problems studied, rather than the types of method used for solutions.

Springer eBooks, 2019

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IFIP The International Federation for Information Processing, 2007

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Neurocomputing, 2007

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Studies in computational intelligence, 2007

The use of general descriptive names, registered names, trademarks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use.

Springer eBooks, 2009

, except for brief excerpts in connection with reviews or scholarly analysis. Use in connection with any form of information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed is forbidden. The use in this publication of trade names, trademarks, service marks and similar terms, even if they are not identified as such, is not to be taken as an expression of opinion as to whether or not they are subject to proprietary rights.