Beschreibung:
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.
1. Bio-inspired Algorithms2. Data Classification Using Support Vector Machines Trained with Evolutionary Algorithms Employing Kernel Adatron3. Reconstruction of 3D Surfaces Using RBF Adjusted with PSO4. Soft Computing Applications in Robot Vision5. Soft Computing Applications inMobile Robotics6. Particle Swarm Optimization to Improve Neural Identifiers for Discrete-time Unknown Nonlinear Systems7. Bio-inspired Algorithms to Improve Neural Controllers for Discrete-time Unknown Nonlinear System8. Final Remarks