New Classification Method Based on Modular Neural Networks with the LVQ Algorithm and Type-2 Fuzzy Logic
In this book a new model for data classification was developed. This new model is based on the competitive neural network Learning Vector Quantization (LVQ) and type-2 fuzzy logic. This computational model consists of the hybridization of the aforem
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Jonathan Amezcua Patricia Melin Oscar Castillo
New Classification Method Based on Modular Neural Networks with the LVQ Algorithm and Type-2 Fuzzy Logic
SpringerBriefs in Applied Sciences and Technology Computational Intelligence
Series editor Janusz Kacprzyk, Polish Academy of Sciences, Systems Research Institute, Warsaw, Poland
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 world-wide distribution, which enable both wide and rapid dissemination of research output.
More information about this series at http://www.springer.com/series/10618
Jonathan Amezcua Patricia Melin Oscar Castillo •
New Classification Method Based on Modular Neural Networks with the LVQ Algorithm and Type-2 Fuzzy Logic
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Jonathan Amezcua Division of Graduate Studies Tijuana Institute of Technology Tijuana, Baja California Mexico
Oscar Castillo Division of Graduate Studies Tijuana Institute of Technology Tijuana, Baja California Mexico
Patricia Melin Division of Graduate Studies Tijuana Institute of Technology Tijuana, Baja California Mexico
ISSN 2191-530X ISSN 2191-5318 (electronic) SpringerBriefs in Applied Sciences and Technology ISSN 2520-8551 ISSN 2520-856X (electronic) SpringerBriefs in Computational Intelligence ISBN 978-3-319-73772-0 ISBN 978-3-319-73773-7 (eBook) https://doi.org/10.1007/978-3-319-73773-7 Library of Congress Control Number: 2017962995 © The Author(s), under exclusive licence to Springer International Publishing AG, part of Springer Nature 2018 This work is subject to copyright. All rights are reserved by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. 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 s
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