Shengyong chen (67 risultati)

Condizione: New. pp. xii + 266 1st Edition.

Condizione: New. pp. xii + 266.

Condizione: New. pp. xii + 266.

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Condizione: Brand New. New. US edition. Expediting shipping for all USA and Europe orders excluding PO Box. Excellent Customer Service.

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Condizione: New. pp. 221.

Taschenbuch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book introduces readers to the background, general framework, main operators, and other basic characteristics of biogeography-based optimization (BBO), which is an emerging branch of bio-inspired computation. In particular, the book presents the authors' recent work on improved variants of BBO, hybridization of BBO with other algorithms, and the application of BBO to a variety of domains including transportation, image processing, and neural network learning. The content will help to advance research into and application of not only BBO but also the whole field of bio-inspired computation. The algorithms and applications are organized in a step-by-step manner and clearly described with the help of pseudo-codes and flowcharts. The readers will learn not only the basic concepts of BBO but also how to apply and adapt the algorithms to the engineering optimization problems they actually encounter.…

Buch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book introduces readers to the background, general framework, main operators, and other basic characteristics of biogeography-based optimization (BBO), which is an emerging branch of bio-inspired computation. In particular, the book presents the authors' recent work on improved variants of BBO, hybridization of BBO with other algorithms, and the application of BBO to a variety of domains including transportation, image processing, and neural network learning. The content will help to advance research into and application of not only BBO but also the whole field of bio-inspired computation. The algorithms and applications are organized in a step-by-step manner and clearly described with the help of pseudo-codes and flowcharts. The readers will learn not only the basic concepts of BBO but also how to apply and adapt the algorithms to the engineering optimization problems they actually encounter.…

Condizione: New. 1st ed. 2019 edition NO-PA16APR2015-KAP.

HRD. Condizione: New. New Book. Shipped from UK. Established seller since 2000.

Hardcover. Condizione: Brand New. 221 pages. 9.25x6.25x0.75 inches. In Stock.

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Paperback. Condizione: Brand New. reprint edition. 232 pages. 9.25x6.10x0.54 inches. In Stock.

Gebundene Ausgabe. Condizione: Neu. This book introduces readers to the background, general framework, main operators, and other basic characteristics of biogeography-based optimization (BBO), which is an emerging branch of bio-inspired computation. In particular, the book presents the authors' recent work on improved variants of BBO, hybridization of BBO with other algorithms, and the application of BBO to a variety of domains including transportation, image processing, and neural network learning. The content will help to advance research into and application of not only BBO but also the whole field of bio-inspired computation. The algorithms and applications are organized in a step-by-step manner and clearly described with the help of pseudo-codes and flowcharts. The readers will learn not only the basic concepts of BBO but also how to apply and adapt the algorithms to the engineering optimization problems they actually encounter. Sprache: Englisch Gewicht in Gramm: 472. …

Condizione: New.

Condizione: As New. Unread book in perfect condition.

Condizione: New. In English.

Condizione: New. In English.

Taschenbuch. Condizione: Neu. Active Sensor Planning for Multiview Vision Tasks | Shengyong Chen (u. a.) | Taschenbuch | xi | Englisch | 2014 | Springer | EAN 9783642437373 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu. …

Taschenbuch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book thoroughly explores the realm of data-driven blade-icing detection for wind turbines, focusing on multivariate time series classification to enhance the reliability and efficiency of wind energy utilization. The widespread prevalence of sensor technology in wind turbines, coupled with substantial data collection, has paved the way for advanced data-driven methodologies, which do not require extensive domain knowledge or additional mechanical tools. The interdisciplinary appeal of this study has drawn attention from experts in fields like computer science, mechanical engineering, and renewable energy systems. Adopting a comprehensive approach, the book lays down a foundational framework for blade-icing detection, stressing the critical role of sensor data integration and the profound impact of machine learning techniques in refining the detection processes. The book is designed for undergraduate and graduate students keen on renewable energy technologies, researchers delving into machine learning applications in energy systems, and engineers focusing on sustainable solutions for enhancing wind turbine performance. …