Identifying Patterns in Financial Markets New Approach Combining Rul
This book describes a new pattern discovery approach based on the combination among rules between Perceptually Important Points (PIPs) and the Symbolic Aggregate approximation (SAX) representation optimized by Genetic Algorithm (GA). The proposed approach
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João Leitão Rui Ferreira Neves Nuno C. G. Horta
Identifying Patterns in Financial Markets New Approach Combining Rules Between PIPs and SAX 123
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
João Leitão Rui Ferreira Neves Nuno C. G. Horta •
Identifying Patterns in Financial Markets New Approach Combining Rules Between PIPs and SAX
123
João Leitão Instituto de Telecomunicações Instituto Superior Técnico Lisbon Portugal
Nuno C. G. Horta Instituto de Telecomunicações Instituto Superior Técnico Lisbon Portugal
Rui Ferreira Neves Instituto de Telecomunicações Instituto Superior Técnico Lisbon Portugal
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 978-3-319-70159-2 ISBN 978-3-319-70160-8 (eBook) https://doi.org/10.1007/978-3-319-70160-8 Library of Congress Control Number: 2017957186 © The Author(s) 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 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
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