Título: |
Cuckoo Search and Firefly Algorithm Theory and Applications edited by Xin-She Yang. |
Otros autores: |
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Yang, Xin-She, ed.
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Editado por: |
Springer International Publishing :;Imprint: Springer,
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Año de publicación: |
2014.
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Lugar de publicación: |
Cham :
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Descripción física: |
xi, 360 p. : il. |
ISBN: |
9783319021416
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Colección: |
Studies in Computational Intelligence,
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Materias: |
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Computer Vision. |
Computational intelligence. |
Image processing. |
Engineering. |
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Notas: |
From the Contents: Cuckoo Search and Firefly Algorithm: Overview and Analysis -- On the Randomization Firefly Algorithm -- Cuckoo Search: A Brief Literature Review -- Discrete cuckoo search for travelling salesman problem -- Comparative analysis of the cuckoo search algorithm -- Multilevel Image Processing by Cuckoo Search -- Binary Cuckoo Search -- Training spiking neural models using cuckoo search -- Multi-Objective Optimization of a Real-World Manufacturing Process using Cuckoo Search. |
Sumario: |
Nature-inspired algorithms such as cuckoo search and firefly algorithm have become popular and widely used in recent years in many applications. These algorithms are flexible, efficient and easy to implement. New progress has been made in the last few years, and it is timely to summarize the latest developments of cuckoo search and firefly algorithm and their diverse applications. This book will review both theoretical studies and applications with detailed algorithm analysis, implementation and case studies so that readers can benefit most from this book. Application topics are contributed by many leading experts in the field. Topics include cuckoo search, firefly algorithm, algorithm analysis, feature selection, image processing, travelling salesman problem, neural network, GPU optimization, scheduling, queuing, multi-objective manufacturing optimization, semantic web service, shape optimization, and others.  This book can serve as an ideal reference for both graduates and researchers in computer science, evolutionary computing, machine learning, computational intelligence, and optimization, as well as engineers in business intelligence, knowledge management and information technology.  . |
URL: |
http://dx.doi.org/10.1007/978-3-319-02141-6
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