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03929nam a2200541 4500 |
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978-3-030-11593-7 |
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20191022112045.0 |
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190111s2019 gw | s |||| 0|eng d |
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|a 9783030115937
|9 978-3-030-11593-7
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|a 10.1007/978-3-030-11593-7
|2 doi
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|a 006.3
|2 23
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|a Cuevas, Erik.
|e author.
|4 aut
|4 http://id.loc.gov/vocabulary/relators/aut
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|a Metaheuristics Algorithms in Power Systems
|h [electronic resource] /
|c by Erik Cuevas, Emilio Barocio Espejo, Arturo Conde Enríquez.
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|a 1st ed. 2019.
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|a Cham :
|b Springer International Publishing :
|b Imprint: Springer,
|c 2019.
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|a XII, 221 p.
|b online resource.
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|a text
|b txt
|2 rdacontent
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|a computer
|b c
|2 rdamedia
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|a online resource
|b cr
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|a text file
|b PDF
|2 rda
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|a Studies in Computational Intelligence,
|x 1860-949X ;
|v 822
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|a Chapter 1. Introduction to metaheuristics methods -- Chapter 2. Metaheuristic schemes for parameter estimation in induction motors -- Chapter 3. Non-conventional overcurrent relays coordination -- Chapter 4. Overcurrent relay coordination, robustness and fast solutions etc.
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|a This book discusses the use of efficient metaheuristic algorithms to solve diverse power system problems, providing an overview of the various aspects of metaheuristic methods to enable readers to gain a comprehensive understanding of the field and of conducting studies on specific metaheuristic algorithms related to power-system applications. By bridging the gap between recent metaheuristic techniques and novel power system methods that benefit from the convenience of metaheuristic methods, it offers power system practitioners who are not metaheuristic computation researchers insights into the techniques, which go beyond simple theoretical tools and have been adapted to solve important problems that commonly arise. On the other hand, members of the metaheuristic computation community learn how power engineering problems can be translated into optimization tasks, and it is also of interest to engineers and application developers. Further, since each chapter can be read independently, the relevant information can be quickly found. Power systems is a multidisciplinary field that addresses the multiple approaches used for design and analysis in areas ranging from signal processing, and electronics to computational intelligence, including the current trend of metaheuristic computation.
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|a Computational intelligence.
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|a Energy systems.
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|a Power electronics.
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|a Artificial intelligence.
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|a Computational Intelligence.
|0 http://scigraph.springernature.com/things/product-market-codes/T11014
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2 |
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|a Energy Systems.
|0 http://scigraph.springernature.com/things/product-market-codes/115000
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|a Power Electronics, Electrical Machines and Networks.
|0 http://scigraph.springernature.com/things/product-market-codes/T24070
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2 |
4 |
|a Artificial Intelligence.
|0 http://scigraph.springernature.com/things/product-market-codes/I21000
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|a Barocio Espejo, Emilio.
|e author.
|4 aut
|4 http://id.loc.gov/vocabulary/relators/aut
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1 |
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|a Conde Enríquez, Arturo.
|e author.
|4 aut
|4 http://id.loc.gov/vocabulary/relators/aut
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710 |
2 |
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|a SpringerLink (Online service)
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|t Springer eBooks
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776 |
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|i Printed edition:
|z 9783030115920
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776 |
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|i Printed edition:
|z 9783030115944
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830 |
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|a Studies in Computational Intelligence,
|x 1860-949X ;
|v 822
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856 |
4 |
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|u https://doi.org/10.1007/978-3-030-11593-7
|z Full Text via HEAL-Link
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|a ZDB-2-INR
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950 |
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|a Intelligent Technologies and Robotics (Springer-42732)
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