Screen LibraryBio-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-lif...
Saved in:
| Main Authors: | |
|---|---|
| Group Author: | ; |
| Published: |
Butterworth-Heinemann, an imprint of Elsevier,
|
| Publisher Address: | Oxford, UK : |
| Publication Dates: | [2018] |
| Literature type: | Book |
| Language: | English |
| Subjects: | |
| 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"-- |
| Carrier Form: | xv, 136 pages : illustrations, forms ; 23 cm |
| Bibliography: | Includes bibliographical references and index. |
| ISBN: |
9780128137888 (paperback) : 0128137886 (paperback) |
| Index Number: | QA76 |
| CLC: |
TP183 TP301.6 |
| Call Number: | TP301.6/A319 |
| Contents: | Bio-inspired algorithms -- Data classification using support vector machines trained with evolutionary algorithms employing Kernel-Adatron -- Reconstruction of 3D surfaces using RBF adjusted with PSO -- Soft computing applications in robot vision -- Soft computing applications in mobile robotics -- Partical swarm optimization to improve neural identifiers for discrete-time unknown nonlinear systems -- Bio-inspired algorithms to improve neural controllers for discrete-time unknown nonlinear system -- Final remarks. |