Hybrid Metaheuristics in Structural Engineering: Including Machine Learning Applications

From the start of life, people used their brains to make something better in design in ordinary works. Due to that, metaheuristics are essential to living things, and several inspirations from life have been used in the generation of new algorithms. These algorithms have unique features, but the usa...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Hauptverfasser: Bekdaş, Gebrail, Nigdeli, Sinan Melih
Format: Buch
Sprache:eng
Schlagworte:
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
container_end_page
container_issue
container_start_page
container_title
container_volume 480
creator Bekdaş, Gebrail
Nigdeli, Sinan Melih
description From the start of life, people used their brains to make something better in design in ordinary works. Due to that, metaheuristics are essential to living things, and several inspirations from life have been used in the generation of new algorithms. These algorithms have unique features, but the usage of different features of different algorithms may give more effective optimum results in means of precision in optimum results, computational effort, and convergence.     This book is a timely book to summarize the latest developments in the optimization of structural engineering systems covering all classical approaches and new trends including hybrids metaheuristic algorithms. Also, artificial intelligence and machine learning methods are included to predict optimum results by skipping long optimization processes. The main objective of this book is to introduce the fundamentals and current development of methods and their applications in structural engineering.  
doi_str_mv 10.1007/978-3-031-34728-3
format Book
fullrecord <record><control><sourceid>proquest_askew</sourceid><recordid>TN_cdi_askewsholts_vlebooks_9783031347283</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>EBC30601957</sourcerecordid><originalsourceid>FETCH-LOGICAL-a11287-4e4a3c58c0540234a17be93e9f853677cfb6277881b12e2eabab2ae8205010093</originalsourceid><addsrcrecordid>eNpFkE9PwzAMxcNfwcY-ALcd4VDmxGmTHGEaDGmIA4hrlBZvK6va0bQgvj3pisbJtvx71vNj7JLDDQdQE6N0hBEgj1AqEfoDNsAw7qb4kJ0LbnQkuYGj_4VSx_uFFqdswFFLGRsj8YyNvP8AAKF1IkCes8n8J63z9_ETNW5NbZ37Js_8OC_HL03dZk1bu2I8K1d5SVTn5eqCnSxd4Wn0V4fs7X72Op1Hi-eHx-ntInKcC60iSdJhFusMYgkCpeMqJYNkljrGRKlsmSbBqdY85YIEudSlwpEWEEN43eCQXfeHnd_Qt19XRePtV0FpVW28DcHsc8DATnrWbzuPVNue4mC7GDvaog283Qlsp7jqFdu6-mzJN3Z3OKOyCQ_b2d0UIQFuYoW_89tpNQ</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>book</recordtype><pqid>EBC30601957</pqid></control><display><type>book</type><title>Hybrid Metaheuristics in Structural Engineering: Including Machine Learning Applications</title><source>Springer Books</source><creator>Bekdaş, Gebrail ; Nigdeli, Sinan Melih</creator><contributor>Nigdeli, Sinan Melih ; Bekdaş, Gebrail</contributor><creatorcontrib>Bekdaş, Gebrail ; Nigdeli, Sinan Melih ; Nigdeli, Sinan Melih ; Bekdaş, Gebrail</creatorcontrib><description>From the start of life, people used their brains to make something better in design in ordinary works. Due to that, metaheuristics are essential to living things, and several inspirations from life have been used in the generation of new algorithms. These algorithms have unique features, but the usage of different features of different algorithms may give more effective optimum results in means of precision in optimum results, computational effort, and convergence.     This book is a timely book to summarize the latest developments in the optimization of structural engineering systems covering all classical approaches and new trends including hybrids metaheuristic algorithms. Also, artificial intelligence and machine learning methods are included to predict optimum results by skipping long optimization processes. The main objective of this book is to introduce the fundamentals and current development of methods and their applications in structural engineering.  </description><edition>1</edition><identifier>ISSN: 2198-4182</identifier><identifier>ISBN: 3031347277</identifier><identifier>ISBN: 9783031347276</identifier><identifier>EISSN: 2198-4190</identifier><identifier>EISBN: 3031347285</identifier><identifier>EISBN: 9783031347283</identifier><identifier>DOI: 10.1007/978-3-031-34728-3</identifier><identifier>OCLC: 1384459943</identifier><language>eng</language><publisher>Cham: Springer</publisher><subject>Artificial Intelligence ; Computational Intelligence ; Engineering ; Machine learning ; Metaheuristics ; Structural engineering</subject><creationdate>2023</creationdate><tpages>306</tpages><format>306</format><rights>The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2023</rights><woscitedreferencessubscribed>false</woscitedreferencessubscribed><relation>Studies in Systems, Decision and Control</relation></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Uhttps://media.springernature.com/w306/springer-static/cover-hires/book/978-3-031-34728-3</thumbnail><linktohtml>$$Uhttps://link.springer.com/10.1007/978-3-031-34728-3$$EHTML$$P50$$Gspringer$$H</linktohtml><link.rule.ids>307,781,785,787,27927,38257,42513</link.rule.ids></links><search><contributor>Nigdeli, Sinan Melih</contributor><contributor>Bekdaş, Gebrail</contributor><creatorcontrib>Bekdaş, Gebrail</creatorcontrib><creatorcontrib>Nigdeli, Sinan Melih</creatorcontrib><title>Hybrid Metaheuristics in Structural Engineering: Including Machine Learning Applications</title><description>From the start of life, people used their brains to make something better in design in ordinary works. Due to that, metaheuristics are essential to living things, and several inspirations from life have been used in the generation of new algorithms. These algorithms have unique features, but the usage of different features of different algorithms may give more effective optimum results in means of precision in optimum results, computational effort, and convergence.     This book is a timely book to summarize the latest developments in the optimization of structural engineering systems covering all classical approaches and new trends including hybrids metaheuristic algorithms. Also, artificial intelligence and machine learning methods are included to predict optimum results by skipping long optimization processes. The main objective of this book is to introduce the fundamentals and current development of methods and their applications in structural engineering.  </description><subject>Artificial Intelligence</subject><subject>Computational Intelligence</subject><subject>Engineering</subject><subject>Machine learning</subject><subject>Metaheuristics</subject><subject>Structural engineering</subject><issn>2198-4182</issn><issn>2198-4190</issn><isbn>3031347277</isbn><isbn>9783031347276</isbn><isbn>3031347285</isbn><isbn>9783031347283</isbn><fulltext>true</fulltext><rsrctype>book</rsrctype><creationdate>2023</creationdate><recordtype>book</recordtype><sourceid/><recordid>eNpFkE9PwzAMxcNfwcY-ALcd4VDmxGmTHGEaDGmIA4hrlBZvK6va0bQgvj3pisbJtvx71vNj7JLDDQdQE6N0hBEgj1AqEfoDNsAw7qb4kJ0LbnQkuYGj_4VSx_uFFqdswFFLGRsj8YyNvP8AAKF1IkCes8n8J63z9_ETNW5NbZ37Js_8OC_HL03dZk1bu2I8K1d5SVTn5eqCnSxd4Wn0V4fs7X72Op1Hi-eHx-ntInKcC60iSdJhFusMYgkCpeMqJYNkljrGRKlsmSbBqdY85YIEudSlwpEWEEN43eCQXfeHnd_Qt19XRePtV0FpVW28DcHsc8DATnrWbzuPVNue4mC7GDvaog283Qlsp7jqFdu6-mzJN3Z3OKOyCQ_b2d0UIQFuYoW_89tpNQ</recordid><startdate>2023</startdate><enddate>2023</enddate><creator>Bekdaş, Gebrail</creator><creator>Nigdeli, Sinan Melih</creator><general>Springer</general><general>Springer Nature Switzerland</general><scope/></search><sort><creationdate>2023</creationdate><title>Hybrid Metaheuristics in Structural Engineering</title><author>Bekdaş, Gebrail ; Nigdeli, Sinan Melih</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-a11287-4e4a3c58c0540234a17be93e9f853677cfb6277881b12e2eabab2ae8205010093</frbrgroupid><rsrctype>books</rsrctype><prefilter>books</prefilter><language>eng</language><creationdate>2023</creationdate><topic>Artificial Intelligence</topic><topic>Computational Intelligence</topic><topic>Engineering</topic><topic>Machine learning</topic><topic>Metaheuristics</topic><topic>Structural engineering</topic><toplevel>online_resources</toplevel><creatorcontrib>Bekdaş, Gebrail</creatorcontrib><creatorcontrib>Nigdeli, Sinan Melih</creatorcontrib></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Bekdaş, Gebrail</au><au>Nigdeli, Sinan Melih</au><au>Nigdeli, Sinan Melih</au><au>Bekdaş, Gebrail</au><format>book</format><genre>book</genre><ristype>BOOK</ristype><btitle>Hybrid Metaheuristics in Structural Engineering: Including Machine Learning Applications</btitle><seriestitle>Studies in Systems, Decision and Control</seriestitle><date>2023</date><risdate>2023</risdate><volume>480</volume><issn>2198-4182</issn><eissn>2198-4190</eissn><isbn>3031347277</isbn><isbn>9783031347276</isbn><eisbn>3031347285</eisbn><eisbn>9783031347283</eisbn><abstract>From the start of life, people used their brains to make something better in design in ordinary works. Due to that, metaheuristics are essential to living things, and several inspirations from life have been used in the generation of new algorithms. These algorithms have unique features, but the usage of different features of different algorithms may give more effective optimum results in means of precision in optimum results, computational effort, and convergence.     This book is a timely book to summarize the latest developments in the optimization of structural engineering systems covering all classical approaches and new trends including hybrids metaheuristic algorithms. Also, artificial intelligence and machine learning methods are included to predict optimum results by skipping long optimization processes. The main objective of this book is to introduce the fundamentals and current development of methods and their applications in structural engineering.  </abstract><cop>Cham</cop><pub>Springer</pub><doi>10.1007/978-3-031-34728-3</doi><oclcid>1384459943</oclcid><tpages>306</tpages><edition>1</edition></addata></record>
fulltext fulltext
identifier ISSN: 2198-4182
ispartof
issn 2198-4182
2198-4190
language eng
recordid cdi_askewsholts_vlebooks_9783031347283
source Springer Books
subjects Artificial Intelligence
Computational Intelligence
Engineering
Machine learning
Metaheuristics
Structural engineering
title Hybrid Metaheuristics in Structural Engineering: Including Machine Learning Applications
url https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2024-12-17T16%3A57%3A48IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_askew&rft_val_fmt=info:ofi/fmt:kev:mtx:book&rft.genre=book&rft.btitle=Hybrid%20Metaheuristics%20in%20Structural%20Engineering:%20Including%20Machine%20Learning%20Applications&rft.au=Bekda%C5%9F,%20Gebrail&rft.date=2023&rft.volume=480&rft.issn=2198-4182&rft.eissn=2198-4190&rft.isbn=3031347277&rft.isbn_list=9783031347276&rft_id=info:doi/10.1007/978-3-031-34728-3&rft_dat=%3Cproquest_askew%3EEBC30601957%3C/proquest_askew%3E%3Curl%3E%3C/url%3E&rft.eisbn=3031347285&rft.eisbn_list=9783031347283&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=EBC30601957&rft_id=info:pmid/&rfr_iscdi=true