Natural Computing Algorithms - Brabazon, Anthony;O'Neill, Michael;McGarraghy, Seán
47,99 €
inkl. MwSt.
Versandkostenfrei*
Versandfertig in 6-10 Tagen
payback
24 °P sammeln
  • Gebundenes Buch

The field of natural computing has been the focus of a substantial research effort in recent decades. One particular strand of this research concerns the development of computational algorithms using metaphorical inspiration from systems and phenomena that occur in the natural world. These naturally inspired computing algorithms have proven to be successful problem-solvers across domains as diverse as management science, bioinformatics, finance, marketing, engineering, architecture and design. This book is a comprehensive introduction to natural computing algorithms, suitable for academic and…mehr

Andere Kunden interessierten sich auch für
Produktbeschreibung
The field of natural computing has been the focus of a substantial research effort in recent decades. One particular strand of this research concerns the development of computational algorithms using metaphorical inspiration from systems and phenomena that occur in the natural world. These naturally inspired computing algorithms have proven to be successful problem-solvers across domains as diverse as management science, bioinformatics, finance, marketing, engineering, architecture and design.
This book is a comprehensive introduction to natural computing algorithms, suitable for academic and industrial researchers and for undergraduate and graduate courses on natural computing in computer science, engineering and management science.
Autorenporträt
Prof. Anthony Brabazon is currently Dean of the UCD College of Business. Previous positions held in UCD include Associate Dean and Director of the Smurfit Graduate School of Business, Vice-Principal of Research and Innovation for the College of Business and Law, and Head of Research for the School of Business. His primary research interests concern the development of natural computing theory and the application of related algorithms to real-world problems, particularly in the domain of business and finance, and he has pioneered multidisciplinary collaborations with industry in areas such as financial mathematics, financial economics, and computer science. He is cofounder and codirector of the Natural Computing Research and Applications Group at UCD, among the most successful research groups dedicated to this subject. Among his publications are the successful coauthored books 'Natural Computing Algorithms', 'Foundations in Grammatical Evolution for DynamicEnvironments', and 'Biologically Inspired Algorithms for Financial Modelling'. Dr. Seán McGarraghy is the director of the UCD Centre for Business Analytics, he was formerly director of the UCD Smurfit Graduate School of Business MSc in Business Analytics. He has qualifications in electronics, mathematics and management and his teaching and academic publications cover many aspects of business analytics and operations research. Particular topics of interests include combinatorial enumeration and optimization, network algorithms, supply chain management, quadratic forms and K-theory. Among his publications are the successful coauthored book 'Natural Computing Algorithms'.
Rezensionen
"The book is very well organized. ... the book is not only suitable for beginners in natural computing, it can also serve as a valuable reference for experts. ... the book can be thought of not only as a collection of algorithms illustrating many methods and tools used in natural computing, but also as a textbook covering many aspects of the area which can be used in an introductory course on natural computing." (Miguel A. Gutiérrez-Naranjo, Mathematical Reviews, June, 2016)

"One interesting advantage of the volume is that it was prepared by and for scholars that are not necessarily in computer science. The book is definitely a good reference and a well-written and well-explained introduction to natural computing ... ." (Hector Zenil, Computing Reviews, April, 2016)

"I very much enjoyed reading this book and found it to be very comprehensive, well-structured, and well-written. It provides good coverage of natural computing approaches as well as a thorough description of each algorithm with its variants. ... suitable as a textbook for a graduate student course as well as a self-study guide for research students, since there are a good number of examples provided throughout. Furthermore, the algorithm descriptions, figures and tables facilitate the learning of the different concepts." (Simone A. Ludwig, Genetic Programming and Evolvable Machines, March, 2016)