Bio-inspired Algorithms for Engineering
Nonfiction, Science & Nature, Technology, Automation, Engineering, Mechanical
| Author: | Nancy Arana-Daniel, Carlos Lopez-Franco, Alma Y. Alanis | ISBN: | 9780128137895 |
| Publisher: | Elsevier Science | Publication: | February 3, 2018 |
| Imprint: | Butterworth-Heinemann | Language: | English |
| Author: | Nancy Arana-Daniel, Carlos Lopez-Franco, Alma Y. Alanis |
| ISBN: | 9780128137895 |
| Publisher: | Elsevier Science |
| Publication: | February 3, 2018 |
| Imprint: | Butterworth-Heinemann |
| Language: | English |
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
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
