xuewei qi (8 resultados)

Condición: New. pp. 140.

Taschenbuch. Condición: Neu. Swarm Intelligence Inspired Engineering Optimization | Concepts, Modeling, Evaluation | Xuewei Qi | Taschenbuch | 140 S. | Englisch | 2014 | LAP LAMBERT Academic Publishing | EAN 9783659356810 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu.

Taschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Swarm intelligence is usually observed in the collective behavior of decentralized, self-organized swarm systems, especially biological swarm systems (e.g. fish school, bird flock). Swarm intelligence algorithms realize the computational systems inspired by the swarm intelligence which always involves cooperation of large numbers of homogeneous agents in certain environment. In this book, several new swarm intelligence inspired algorithms are proposed to solve a real world engineering optimization problem. Machine Learning is also utilized to further enhance these algorithms. All of the proposed algorithms are tested, evaluated and compared extensively. This book may satisfy many groups of people in different ways: research scientists may borrow algorithmic inspirations to model and investigate a new swarm system; software developers may follow the technical guidelines by comparing the performance of different algorithms and obtain a big picture of how to design, implement, apply and evaluate these state-of-art algorithms to address real world needs; other interested individuals can simply enjoy these beautiful nature-inspired algorithm models presented in the book. 140 pp. Englisch.

Condición: New. Print on Demand pp. 140 2:B&W 6 x 9 in or 229 x 152 mm Perfect Bound on Creme w/Gloss Lam.

Condición: New. PRINT ON DEMAND pp. 140.

Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Qi XueweiThe author received his second M.S. engineering degree from University of Georgia, Athens, USA in 2013. He is now pursing his Ph.D. degree in Electrical Engineering at University of California, Riverside. His research intere.

Taschenbuch. Condición: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Swarm intelligence is usually observed in the collective behavior of decentralized, self-organized swarm systems, especially biological swarm systems (e.g. fish school, bird flock). Swarm intelligence algorithms realize the computational systems inspired by the swarm intelligence which always involves cooperation of large numbers of homogeneous agents in certain environment. In this book, several new swarm intelligence inspired algorithms are proposed to solve a real world engineering optimization problem. Machine Learning is also utilized to further enhance these algorithms. All of the proposed algorithms are tested, evaluated and compared extensively. This book may satisfy many groups of people in different ways: research scientists may borrow algorithmic inspirations to model and investigate a new swarm system; software developers may follow the technical guidelines by comparing the performance of different algorithms and obtain a big picture of how to design, implement, apply and evaluate these state-of-art algorithms to address real world needs; other interested individuals can simply enjoy these beautiful nature-inspired algorithm models presented in the book.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 140 pp. Englisch.

Taschenbuch. Condición: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Swarm intelligence is usually observed in the collective behavior of decentralized, self-organized swarm systems, especially biological swarm systems (e.g. fish school, bird flock). Swarm intelligence algorithms realize the computational systems inspired by the swarm intelligence which always involves cooperation of large numbers of homogeneous agents in certain environment. In this book, several new swarm intelligence inspired algorithms are proposed to solve a real world engineering optimization problem. Machine Learning is also utilized to further enhance these algorithms. All of the proposed algorithms are tested, evaluated and compared extensively. This book may satisfy many groups of people in different ways: research scientists may borrow algorithmic inspirations to model and investigate a new swarm system; software developers may follow the technical guidelines by comparing the performance of different algorithms and obtain a big picture of how to design, implement, apply and evaluate these state-of-art algorithms to address real world needs; other interested individuals can simply enjoy these beautiful nature-inspired algorithm models presented in the book.