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Autore: |
Alanis Alma Y.
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Titolo: |
Bio-inspired algorithms for engineering / / Alma Y. Alanis, Nancy Arana-Daniel, Carlos Lopez-Franco
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Pubblicazione: | Kidlington, England ; ; Cambridge, Massachusetts : , : Butterworth-Heinemann, , 2018 |
©2018 | |
Edizione: | First edition. |
Descrizione fisica: | 1 online resource (137 pages) : illustrations |
Disciplina: | 005.1 |
Soggetto topico: | Computer algorithms |
Natural computation - Industrial applications | |
Persona (resp. second.): | Arana-DanielNancy |
Lopez-FrancoCarlos | |
Nota di bibliografia: | Includes bibliographical references at the end of each chapters and index. |
Sommario/riassunto: | 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 |
Titolo autorizzato: | Bio-inspired algorithms for engineering ![]() |
ISBN: | 0-12-813789-4 |
0-12-813788-6 | |
Formato: | Materiale a stampa ![]() |
Livello bibliografico | Monografia |
Lingua di pubblicazione: | Inglese |
Record Nr.: | 9910583383203321 |
Lo trovi qui: | Univ. Federico II |
Opac: | Controlla la disponibilità qui |