Please use this identifier to cite or link to this item:
http://localhost/handle/Hannan/493
Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Brabazon, Anthony. ; | en_US |
dc.contributor.author | McGarraghy, Seeen. ; | en_US |
dc.date.accessioned | 2013 | en_US |
dc.date.accessioned | 2020-05-17T08:17:41Z | - |
dc.date.available | 2020-05-17T08:17:41Z | - |
dc.date.issued | 2018 | en_US |
dc.identifier.isbn | 9783319591568 ; | en_US |
dc.identifier.isbn | 9783319591551 (print) ; | en_US |
dc.identifier.isbn | 9783319591575 (print) ; | en_US |
dc.identifier.uri | http://localhost/handle/Hannan/493 | - |
dc.description | en_US | |
dc.description | en_US | |
dc.description | en_US | |
dc.description | SpringerLink (Online service) ; | en_US |
dc.description | Printed edition: ; 9783319591551. ; | en_US |
dc.description | QA75.5-76.95 ; | en_US |
dc.description | en_US | |
dc.description | Printed edition: ; 9783319591575. ; | en_US |
dc.description | en_US | |
dc.description.abstract | This book is an introduction to relevant aspects of the foraging literature for algorithmic design, and an overview of key families of optimization algorithms that stem from a foraging metaphor. The authors first offer perspectives on foraging and foraging-inspired algorithms for optimization, they then explain the techniques inspired by the behaviors of vertebrates, invertebrates, and non-neuronal organisms, and they then discuss algorithms based on formal models of foraging, how to evolve a foraging strategy, and likely future developments. No prior knowledge of natural computing is assumed. This book will be of particular interest to graduate students, academics and practitioners in computer science, informatics, data science, management science, and other application domains. ; | en_US |
dc.description.statementofresponsibility | by Anthony Brabazon, Seeen McGarraghy. | en_US |
dc.description.tableofcontents | Introduction -- Formal Models of Foraging -- Sensor Modalities -- Individual and Social Learning -- Introduction to Foraging Algorithms -- Mammals -- Bird Foraging Algorithms -- Fish Algorithms -- Ant Foraging Algorithms -- Honeybee Inspired Algorithms -- Bioluminescence Algorithms -- Spider Algorithms -- Worm Algorithm -- Bacteria Inspired Algorithms -- Slime Mould Foraging -- Plant Foraging Algorithms -- Group Search and Predatory Search -- Evolving Foraging Algorithms -- Conclusions. ; | en_US |
dc.format.extent | XVIII, 478 p. ; online resource. ; | en_US |
dc.publisher | Springer International Publishing : | en_US |
dc.publisher | Imprint: Springer, | en_US |
dc.relation.ispartofseries | Natural Computing Series, ; 1619-7127. ; | en_US |
dc.relation.ispartofseries | Natural Computing Series, ; 1619-7127. ; | en_US |
dc.relation.haspart | 9783319591551.pdf | en_US |
dc.subject | Information theory. ; | en_US |
dc.subject | Engineering | en_US |
dc.subject | Artificial Intelligence | en_US |
dc.subject | Operations research. ; | en_US |
dc.subject | Theory of Computation. ; http://scigraph.springernature.com/things/product-market-codes/I16005. ; | en_US |
dc.subject | Computational Intelligence. ; http://scigraph.springernature.com/things/product-market-codes/T11014. ; | en_US |
dc.subject | Artificial Intelligence and Robotics | en_US |
dc.subject | Operations Research, Management Science. ; http://scigraph.springernature.com/things/product-market-codes/M26024. ; | en_US |
dc.subject | Operations Research/Decision Theory. ; http://scigraph.springernature.com/things/product-market-codes/521000. ; | en_US |
dc.subject.ddc | 004.0151 ; 23 ; | en_US |
dc.title | Foraging-Inspired Optimisation Algorithms | en_US |
dc.type | Book | en_US |
dc.publisher.place | Cham : | en_US |
Appears in Collections: | مدیریت فناوری اطلاعات |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
9783319591551.pdf | 7.8 MB | Adobe PDF | Preview File |
Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Brabazon, Anthony. ; | en_US |
dc.contributor.author | McGarraghy, Seeen. ; | en_US |
dc.date.accessioned | 2013 | en_US |
dc.date.accessioned | 2020-05-17T08:17:41Z | - |
dc.date.available | 2020-05-17T08:17:41Z | - |
dc.date.issued | 2018 | en_US |
dc.identifier.isbn | 9783319591568 ; | en_US |
dc.identifier.isbn | 9783319591551 (print) ; | en_US |
dc.identifier.isbn | 9783319591575 (print) ; | en_US |
dc.identifier.uri | http://localhost/handle/Hannan/493 | - |
dc.description | en_US | |
dc.description | en_US | |
dc.description | en_US | |
dc.description | SpringerLink (Online service) ; | en_US |
dc.description | Printed edition: ; 9783319591551. ; | en_US |
dc.description | QA75.5-76.95 ; | en_US |
dc.description | en_US | |
dc.description | Printed edition: ; 9783319591575. ; | en_US |
dc.description | en_US | |
dc.description.abstract | This book is an introduction to relevant aspects of the foraging literature for algorithmic design, and an overview of key families of optimization algorithms that stem from a foraging metaphor. The authors first offer perspectives on foraging and foraging-inspired algorithms for optimization, they then explain the techniques inspired by the behaviors of vertebrates, invertebrates, and non-neuronal organisms, and they then discuss algorithms based on formal models of foraging, how to evolve a foraging strategy, and likely future developments. No prior knowledge of natural computing is assumed. This book will be of particular interest to graduate students, academics and practitioners in computer science, informatics, data science, management science, and other application domains. ; | en_US |
dc.description.statementofresponsibility | by Anthony Brabazon, Seeen McGarraghy. | en_US |
dc.description.tableofcontents | Introduction -- Formal Models of Foraging -- Sensor Modalities -- Individual and Social Learning -- Introduction to Foraging Algorithms -- Mammals -- Bird Foraging Algorithms -- Fish Algorithms -- Ant Foraging Algorithms -- Honeybee Inspired Algorithms -- Bioluminescence Algorithms -- Spider Algorithms -- Worm Algorithm -- Bacteria Inspired Algorithms -- Slime Mould Foraging -- Plant Foraging Algorithms -- Group Search and Predatory Search -- Evolving Foraging Algorithms -- Conclusions. ; | en_US |
dc.format.extent | XVIII, 478 p. ; online resource. ; | en_US |
dc.publisher | Springer International Publishing : | en_US |
dc.publisher | Imprint: Springer, | en_US |
dc.relation.ispartofseries | Natural Computing Series, ; 1619-7127. ; | en_US |
dc.relation.ispartofseries | Natural Computing Series, ; 1619-7127. ; | en_US |
dc.relation.haspart | 9783319591551.pdf | en_US |
dc.subject | Information theory. ; | en_US |
dc.subject | Engineering | en_US |
dc.subject | Artificial Intelligence | en_US |
dc.subject | Operations research. ; | en_US |
dc.subject | Theory of Computation. ; http://scigraph.springernature.com/things/product-market-codes/I16005. ; | en_US |
dc.subject | Computational Intelligence. ; http://scigraph.springernature.com/things/product-market-codes/T11014. ; | en_US |
dc.subject | Artificial Intelligence and Robotics | en_US |
dc.subject | Operations Research, Management Science. ; http://scigraph.springernature.com/things/product-market-codes/M26024. ; | en_US |
dc.subject | Operations Research/Decision Theory. ; http://scigraph.springernature.com/things/product-market-codes/521000. ; | en_US |
dc.subject.ddc | 004.0151 ; 23 ; | en_US |
dc.title | Foraging-Inspired Optimisation Algorithms | en_US |
dc.type | Book | en_US |
dc.publisher.place | Cham : | en_US |
Appears in Collections: | مدیریت فناوری اطلاعات |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
9783319591551.pdf | 7.8 MB | Adobe PDF | Preview File |
Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Brabazon, Anthony. ; | en_US |
dc.contributor.author | McGarraghy, Seeen. ; | en_US |
dc.date.accessioned | 2013 | en_US |
dc.date.accessioned | 2020-05-17T08:17:41Z | - |
dc.date.available | 2020-05-17T08:17:41Z | - |
dc.date.issued | 2018 | en_US |
dc.identifier.isbn | 9783319591568 ; | en_US |
dc.identifier.isbn | 9783319591551 (print) ; | en_US |
dc.identifier.isbn | 9783319591575 (print) ; | en_US |
dc.identifier.uri | http://localhost/handle/Hannan/493 | - |
dc.description | en_US | |
dc.description | en_US | |
dc.description | en_US | |
dc.description | SpringerLink (Online service) ; | en_US |
dc.description | Printed edition: ; 9783319591551. ; | en_US |
dc.description | QA75.5-76.95 ; | en_US |
dc.description | en_US | |
dc.description | Printed edition: ; 9783319591575. ; | en_US |
dc.description | en_US | |
dc.description.abstract | This book is an introduction to relevant aspects of the foraging literature for algorithmic design, and an overview of key families of optimization algorithms that stem from a foraging metaphor. The authors first offer perspectives on foraging and foraging-inspired algorithms for optimization, they then explain the techniques inspired by the behaviors of vertebrates, invertebrates, and non-neuronal organisms, and they then discuss algorithms based on formal models of foraging, how to evolve a foraging strategy, and likely future developments. No prior knowledge of natural computing is assumed. This book will be of particular interest to graduate students, academics and practitioners in computer science, informatics, data science, management science, and other application domains. ; | en_US |
dc.description.statementofresponsibility | by Anthony Brabazon, Seeen McGarraghy. | en_US |
dc.description.tableofcontents | Introduction -- Formal Models of Foraging -- Sensor Modalities -- Individual and Social Learning -- Introduction to Foraging Algorithms -- Mammals -- Bird Foraging Algorithms -- Fish Algorithms -- Ant Foraging Algorithms -- Honeybee Inspired Algorithms -- Bioluminescence Algorithms -- Spider Algorithms -- Worm Algorithm -- Bacteria Inspired Algorithms -- Slime Mould Foraging -- Plant Foraging Algorithms -- Group Search and Predatory Search -- Evolving Foraging Algorithms -- Conclusions. ; | en_US |
dc.format.extent | XVIII, 478 p. ; online resource. ; | en_US |
dc.publisher | Springer International Publishing : | en_US |
dc.publisher | Imprint: Springer, | en_US |
dc.relation.ispartofseries | Natural Computing Series, ; 1619-7127. ; | en_US |
dc.relation.ispartofseries | Natural Computing Series, ; 1619-7127. ; | en_US |
dc.relation.haspart | 9783319591551.pdf | en_US |
dc.subject | Information theory. ; | en_US |
dc.subject | Engineering | en_US |
dc.subject | Artificial Intelligence | en_US |
dc.subject | Operations research. ; | en_US |
dc.subject | Theory of Computation. ; http://scigraph.springernature.com/things/product-market-codes/I16005. ; | en_US |
dc.subject | Computational Intelligence. ; http://scigraph.springernature.com/things/product-market-codes/T11014. ; | en_US |
dc.subject | Artificial Intelligence and Robotics | en_US |
dc.subject | Operations Research, Management Science. ; http://scigraph.springernature.com/things/product-market-codes/M26024. ; | en_US |
dc.subject | Operations Research/Decision Theory. ; http://scigraph.springernature.com/things/product-market-codes/521000. ; | en_US |
dc.subject.ddc | 004.0151 ; 23 ; | en_US |
dc.title | Foraging-Inspired Optimisation Algorithms | en_US |
dc.type | Book | en_US |
dc.publisher.place | Cham : | en_US |
Appears in Collections: | مدیریت فناوری اطلاعات |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
9783319591551.pdf | 7.8 MB | Adobe PDF | Preview File |