Bio-inspired Algorithms for Engineering (eBook)

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

Nancy Arana-Daniel received the M.S. and Ph.D. degrees in Computer Science, both from the Center of Research and Advanced Studies, CINVESTAV Unidad Guadalajara, Jalisco, México. She is currently a Research Fellow with the Department of Computer Science, University of Guadalajara, Guadalajara, Jalisco, where she is working, in the Intelligent Systems Research Group. She is director of the research center on artificial intelligence at CUCEI, Universidad de Guadalajara. Her current research interests include applications of geometric algebra, machine learning, optimization, computer vision, pattern recognition, and visually guided robotics.

---

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