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Real-life Applications with Membrane Computing

  • Book
  • © 2017

Overview

Authors:
  1. Gexiang Zhang

    1. Robotics Research Center, Xihua University, Chengdu, China

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  2. Mario J. Pérez-Jiménez

    1. Department of Computer Science and Artificial Intelligence, University of Seville, Sevilla, Spain

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  3. Marian Gheorghe

    1. School of Electrical Engineering and Computer Science, University of Bradford, Bradford, United Kingdom

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  • Presents a novel approach relying on a combination of different membrane system models and evolutionary methods or fuzzy reasoning systems, applied to a wide range of contexts from various engineering areas
  • Includes unprecedented information on a new set of real-life complex and challenging applications modeled and analyzed with the help of membrane computing tools
  • Written by respected researchers in the field, actively involved in designing real applications of membrane computing and building adequate tools
  • Includes supplementary material: sn.pub/extras

Part of the book series: Emergence, Complexity and Computation (ECC, volume 25)

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Table of contents (7 chapters)

  1. Front Matter

    Pages i-xii
    Download chapter PDF

  2. Membrane Computing - Key Concepts and Definitions

    • Gexiang Zhang, Mario J. Pérez-Jiménez, Marian Gheorghe
    Pages 1-9

  3. Fundamentals of Evolutionary Computation

    • Gexiang Zhang, Mario J. Pérez-Jiménez, Marian Gheorghe
    Pages 11-32

  4. Membrane Algorithms

    • Gexiang Zhang, Mario J. Pérez-Jiménez, Marian Gheorghe
    Pages 33-115

  5. Engineering Optimization with Membrane Algorithms

    • Gexiang Zhang, Mario J. Pérez-Jiménez, Marian Gheorghe
    Pages 117-158

  6. Electric Power System Fault Diagnosis with Membrane Systems

    • Gexiang Zhang, Mario J. Pérez-Jiménez, Marian Gheorghe
    Pages 159-212

  7. Robot Control with Membrane Systems

    • Gexiang Zhang, Mario J. Pérez-Jiménez, Marian Gheorghe
    Pages 213-258

  8. Data Modeling with Membrane Systems: Applications to Real Ecosystems

    • Gexiang Zhang, Mario J. Pérez-Jiménez, Marian Gheorghe
    Pages 259-355
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Keywords

About this book

This book thoroughly investigates the underlying theoretical basis of membrane computing models, and reveals their latest applications. In addition, to date there have been no illustrative case studies or complex real-life applications that capitalize on the full potential of the sophisticated membrane systems computational apparatus; gaps that this book remedies. By studying various complex applications – including engineering optimization, power systems fault diagnosis, mobile robot controller design, and complex biological systems involving data modeling and process interactions – the book also extends the capabilities of membrane systems models with features such as formal verification techniques, evolutionary approaches, and fuzzy reasoning methods.

 As such, the book offers a comprehensive and up-to-date guide for all researchers, PhDs and undergraduate students in the fields of computer science, engineering and the bio-sciences who are interested in the applications of natural computing models.

Authors and Affiliations

  • Robotics Research Center, Xihua University, Chengdu, China

    Gexiang Zhang

  • Department of Computer Science and Artificial Intelligence, University of Seville, Sevilla, Spain

    Mario J. Pérez-Jiménez

  • School of Electrical Engineering and Computer Science, University of Bradford, Bradford, United Kingdom

    Marian Gheorghe

Bibliographic Information

  • Book Title: Real-life Applications with Membrane Computing

  • Authors: Gexiang Zhang, Mario J. Pérez-Jiménez, Marian Gheorghe

  • Series Title: Emergence, Complexity and Computation

  • DOI: https://doi.org/10.1007/978-3-319-55989-6

  • Publisher: Springer Cham

  • eBook Packages: Engineering, Engineering (R0)

  • Copyright Information: Springer International Publishing AG 2017

  • Hardcover ISBN: 978-3-319-55987-2Published: 13 April 2017

  • Softcover ISBN: 978-3-319-85798-5Published: 25 July 2018

  • eBook ISBN: 978-3-319-55989-6Published: 05 April 2017

  • Series ISSN: 2194-7287

  • Series E-ISSN: 2194-7295

  • Edition Number: 1

  • Number of Pages: XII, 355

  • Number of Illustrations: 94 b/w illustrations, 54 illustrations in colour

  • Topics: Computational Intelligence, Artificial Intelligence, Complexity

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