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Learning and Analytics in Intelligent Systems

Biologically Inspired Techniques in Many-Criteria Decision Making

International Conference on Biologically Inspired Techniques in Many-Criteria Decision Making (BITMDM-2019)

Editors: Dehuri, S., Prasad Mishra, B.S., Mallick, P.K., Cho, S.-B., Favorskaya, M. (Eds.)

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  • Addresses recent challenges in optimization methods and techniques associated with the exponential growth in data production
  • Gathers the Proceedings of the International Conference on Biologically Inspired Techniques in Many-Criteria Decision Making (BITMDM-2019), held in Balasore, India, on December 19–20, 2019
  • Demonstrates how to derive optimal solutions for data-driven problems
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eBook 181,89 €
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  • ISBN 978-3-030-39033-4
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Hardcover 228,79 €
price for Spain (gross)
  • ISBN 978-3-030-39032-7
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About this book

This book addresses many-criteria decision-making (MCDM), a process used to find a solution in an environment with several criteria. In many real-world problems, there are several different objectives that need to be taken into account. Solving these problems is a challenging task and requires careful consideration. In real applications, often simple and easy to understand methods are used; as a result, the solutions accepted by decision makers are not always optimal solutions. On the other hand, algorithms that would provide better outcomes are very time consuming. The greatest challenge facing researchers is how to create effective algorithms that will yield optimal solutions with low time complexity. Accordingly, many current research efforts are focused on the implementation of biologically inspired algorithms (BIAs), which are well suited to solving uni-objective problems.

This book introduces readers to state-of-the-art developments in biologically inspired techniques and their applications, with a major emphasis on the MCDM process. To do so, it presents a wide range of contributions on e.g. BIAs, MCDM, nature-inspired algorithms, multi-criteria optimization, machine learning and soft computing. 

Table of contents (23 chapters)

Table of contents (23 chapters)
  • Classification of Arrhythmia Using Artificial Neural Network with Grey Wolf Optimization

    Pages 3-10

    Mohapatra, Saumendra Kumar (et al.)

  • Multi-objective Biogeography-Based Optimization for Influence Maximization-Cost Minimization in Social Networks

    Pages 11-34

    De, Sagar S. (et al.)

  • Classification of Credit Dataset Using Improved Particle Swarm Optimization Tuned Radial Basis Function Neural Networks

    Pages 35-45

    Pandey, Trilok Nath (et al.)

  • Multi-Verse Optimization of Multilayer Perceptrons (MV-MLPs) for Efficient Modeling and Forecasting of Crude Oil Prices Data

    Pages 46-54

    Nayak, Sarat Chandra (et al.)

  • Application of Machine Learning to Predict Diseases Based on Symptoms in Rural India

    Pages 55-61

    Biswal, Suvasree S. (et al.)

Buy this book

eBook 181,89 €
price for Spain (gross)
  • ISBN 978-3-030-39033-4
  • Digitally watermarked, DRM-free
  • Included format: EPUB, PDF
  • ebooks can be used on all reading devices
  • Immediate eBook download after purchase
Hardcover 228,79 €
price for Spain (gross)
  • ISBN 978-3-030-39032-7
  • Free shipping for individuals worldwide
  • Immediate ebook access, if available*, with your print order
  • Usually dispatched within 3 to 5 business days.
  • The final prices may differ from the prices shown due to specifics of VAT rules
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Bibliographic Information

Bibliographic Information
Book Title
Biologically Inspired Techniques in Many-Criteria Decision Making
Book Subtitle
International Conference on Biologically Inspired Techniques in Many-Criteria Decision Making (BITMDM-2019)
Editors
  • Satchidananda Dehuri
  • Bhabani Shankar Prasad Mishra
  • Pradeep Kumar Mallick
  • Sung-Bae Cho
  • Margarita Favorskaya
Series Title
Learning and Analytics in Intelligent Systems
Series Volume
10
Copyright
2020
Publisher
Springer International Publishing
Copyright Holder
Springer Nature Switzerland AG
eBook ISBN
978-3-030-39033-4
DOI
10.1007/978-3-030-39033-4
Hardcover ISBN
978-3-030-39032-7
Series ISSN
2662-3447
Edition Number
1
Number of Pages
XV, 258
Number of Illustrations
32 b/w illustrations, 65 illustrations in colour
Topics

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