Bio-inspired algorithms for engineering
"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, allow…
Read More ↓Title Statements
- Full title :Bio-inspired algorithms for engineering / Alma Y. Alanis, Nancy Arana-Daniel, Carlos López-Franc, University of Guadalajar, University Center of Exact Sciences and Engineering Department of Computer Sciences Intelligent Systems Research Group.
Summary
"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 chapterIncludes illustrations, tables and figures that facilitate the reader’s comprehension of the proposed schemes and applications"--.
Read More ↓Edition Statements
- Publication Date:2018
- Edition:First edition
Publication Statements
- Publisher(s):Butterworth-Heinemann, an imprint of Elsevier
- Place of Publication:Oxford, United Kingdom
- Language:eng
- Publication Date:2018
The Physical Object
- Description:1 Online-Ressource.
Edition Identifiers
- ISBN:9780128137888, 0128137886
- oclc:on1045017841
- Dewey Decimal:005.1
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