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  xmlns:dcterms="http://purl.org/dc/terms/"><dc:Title>Bio-inspired algorithms for engineering /  Alma Y. Alanis, Nancy Arana-Daniel, Carlos López-Franco.</dc:Title>
<dc:Creator>Alanis, Alma Y.</dc:Creator>
<dc:Creator>Arana-Daniel, Nancy. jt. aut.</dc:Creator>
<dc:Creator>López-Franco, Carlos. jt. aut.</dc:Creator>
<dc:Subject>Robots (Algorithms).</dc:Subject>
<dc:Subject>Neural computers.</dc:Subject>
<dc:Subject>QA76.9.A43 A39 2018</dc:Subject>
<dc:Subject>629.892632 ALB</dc:Subject>
<dc:Description>Includes bibliographical references and index.</dc:Description>
<dc:Description>"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"-- Provided by publisher.</dc:Description>
<dc:Date>2018</dc:Date>
<dc:Type>Text</dc:Type>
<dc:Format>xv, 136 p. :</dc:Format>
<dc:Language>eng</dc:Language>

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