Bio-inspired algorithms for engineering

• Verfasst von: Alanis, Alma Y. [VerfasserIn]
• Titel: Bio-inspired algorithms for engineering
• Mitwirkende: Arana-Daniel, Nancy [MitwirkendeR]
• Mitwirkende: Lopez-Franco, Carlos [MitwirkendeR]
• Verf.angabe: Alma Y. Alanis, Nancy Arana-Daniel, Carlos López-Franco.
• Ausgabe: First edition.
• Verlagsort: Kidlington, Oxford, United Kingdom ; ; Cambridge, MA
• Verlag: Butterworth-Heinemann
• E-Jahr: 2018
• Jahr: [2018]
• Umfang: 1 online resource (1 volume)
• Illustrationen: illustrations
• Fussnoten: Includes bibliographical references and index. - Description based on online resource; title from title page (Safari, viewed January 16, 2019)
• ISBN: 978-0-12-813789-5
• ISBN: 0-12-813789-4
• Datenträger: Online-Ressource
• Sprache: eng
• Sach-SW: Computer algorithms
• Sach-SW: Natural computation ; Industrial applications
• Sach-SW: Evolutionary computation ; Industrial applications
• Sach-SW: Natural computation ; Scientific applications
• Sach-SW: Evolutionary computation ; Scientific applications
• Sach-SW: Electronic books ; local
• Sach-SW: Electronic books
• K10plus-PPN: 1680146025
• K10plus-PPN:
  Universitätsbibliothek
• Lokale URL UB: Zum Volltext
• Lokale URL UB: Bibliothek der Medizinischen Fakultät Mannheim der Universität Heidelberg
• Bibliothek/Idn: UW / m3607360499
• Lokale URL Inst.: Zum Volltext

Abstract

Bio-inspired Algorithms for Engineering builds a bridge between the proposed bio-inspired algorithms developed in the past few decades and their applications in real-life problems, not only in an academic context, but also in the real world. The book proposes novel algorithms to solve real-life, complex problems, combining well-known bio-inspired algorithms with new concepts, including both rigorous analyses and unique applications. It covers both theoretical and practical methodologies, allowing readers to learn more about the implementation of bio-inspired algorithms. This book is a useful resource for both academic and industrial engineers working on artificial intelligence, robotics, machine learning, vision, classification, pattern recognition, identification and control. Presents real-time implementation and simulation results for all the proposed schemes Offers a comparative analysis and rigorous analysis of the convergence of proposed algorithms Provides a guide for implementing each application at the end of each chapter Includes illustrations, tables and figures that facilitate the reader's comprehension of the proposed schemes and applications