Evolving Improved Neural Network Classifiers for Bankruptcy Prediction by Hybridization of Nature Inspired Algorithms
Bankruptcy prediction is a hard classification problem, as data are high-dimensional, non-Gaussian, and exceptions are common. Nature inspired algorithms have proven successful in evolving better classifiers due to their fine balance between exploration a
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Raúl León · María Jesús Muñoz-Torres Jose M. Moneva (Eds.)
Modeling and Simulation in Engineering, Economics and Management International Conference, MS 2016 Teruel, Spain, July 4–5, 2016 Proceedings
123
Lecture Notes in Business Information Processing Series Editors Wil van der Aalst Eindhoven Technical University, Eindhoven, The Netherlands John Mylopoulos University of Trento, Trento, Italy Michael Rosemann Queensland University of Technology, Brisbane, QLD, Australia Michael J. Shaw University of Illinois, Urbana-Champaign, IL, USA Clemens Szyperski Microsoft Research, Redmond, WA, USA
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More information about this series at http://www.springer.com/series/7911
Raúl León María Jesús Muñoz-Torres Jose M. Moneva (Eds.) •
Modeling and Simulation in Engineering, Economics and Management International Conference, MS 2016 Teruel, Spain, July 4–5, 2016 Proceedings
123
Editors Raúl León Department of Accounting and Finance University of Zaragoza Zaragoza Spain
Jose M. Moneva Department of Accounting and Finance University of Zaragoza Zaragoza Spain
María Jesús Muñoz-Torres University Jaume I Castellón de la Plana Spain
ISSN 1865-1348 ISSN 1865-1356 (electronic) Lecture Notes in Business Information Processing ISBN 978-3-319-40505-6 ISBN 978-3-319-40506-3 (eBook) DOI 10.1007/978-3-319-40506-3 Library of Congress Control Number: 2016941607 © Springer International Publishing Switzerland 2016 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 editors give a warranty, express or implied, with respect to the material contained herein or for any errors or omissions that may have been made. Printed on acid-free paper This Springer imprint is published by Springer Nature The registered company is Springer International Publishing AG Switzerland
Preface
The Association for the Advancement of Modelling and Simulation Techniques in Enterprises (AMSE) and the University of Zaragoza are pleased to present the main results of the International Conference on Modelling and Simulation in Engineering, Economics, and Management, held in Teruel, Spain, July 4–5, 2016, through this book of proceedings published with Springer in t
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