GA neural network of the cost of the building graphic of the analysis and understanding

GA neural network of the cost of the building graphic of the analysis and understanding

The costs of pre-building graphic in the construction project management is a very important job, based on neural network theory and the characteristics of the costs of building graphic, raised GA neural network to solve the cost of building graphic problem, applied BP network model and used GA to o...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Hauptverfasser: Kuancheng Zou, Ye Qian, Yafei Li, Pengfei Zhang
Format: Tagungsbericht
Sprache:eng
Schlagworte:
Adaptation model
BP algorithm
Gallium
Neural network
the cost of building graphic
Online-Zugang:Volltext bestellen
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
container_end_page 308
container_issue
container_start_page 305
container_title
container_volume 1
creator Kuancheng Zou
Ye Qian
Yafei Li
Pengfei Zhang
description The costs of pre-building graphic in the construction project management is a very important job, based on neural network theory and the characteristics of the costs of building graphic, raised GA neural network to solve the cost of building graphic problem, applied BP network model and used GA to optimize the weight based on BP algorithm. The calculation examples showed that the accuracy of the cost estimation met the requirements basically.
doi_str_mv 10.1109/CMCE.2010.5610497
format Conference Proceeding
fullrecord <record><control><sourceid>ieee_6IE</sourceid><recordid>TN_cdi_ieee_primary_5610497</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><ieee_id>5610497</ieee_id><sourcerecordid>5610497</sourcerecordid><originalsourceid>FETCH-LOGICAL-i90t-6bb34707e7c14a5aadb6917548db4975f48d95b1f51d7627552500f73dfccaab3</originalsourceid><addsrcrecordid>eNo1kMtKAzEYhSMqWOs8gLjJC0zN_bIsQ61CxU3BZUkmSRsdZ0oyRfr2BuyszncOPz-cA8AjRguMkX5u3pvVgqBiucCIaXkF7jEjjEnNFbsGlZZq8pLegBnBXNcCEXEHqpy_EEIUK6WkmoHP9RL2_pRMV2T8HdI3HAIcDx62Qx4ntqfYudjv4T6Z4yG2U256051zzAUcPPXOpzwWLJcP4DaYLvvqonOwfVltm9d687F-a5abOmo01sJayiSSXraYGW6Ms0JjyZlytvTioYDmFgeOnRREck44QkFSF9rWGEvn4On_bfTe744p_ph03l1moX-HB1Qi</addsrcrecordid><sourcetype>Publisher</sourcetype><iscdi>true</iscdi><recordtype>conference_proceeding</recordtype></control><display><type>conference_proceeding</type><title>GA neural network of the cost of the building graphic of the analysis and understanding</title><source>IEEE Electronic Library (IEL) Conference Proceedings</source><creator>Kuancheng Zou ; Ye Qian ; Yafei Li ; Pengfei Zhang</creator><creatorcontrib>Kuancheng Zou ; Ye Qian ; Yafei Li ; Pengfei Zhang</creatorcontrib><description>The costs of pre-building graphic in the construction project management is a very important job, based on neural network theory and the characteristics of the costs of building graphic, raised GA neural network to solve the cost of building graphic problem, applied BP network model and used GA to optimize the weight based on BP algorithm. The calculation examples showed that the accuracy of the cost estimation met the requirements basically.</description><identifier>ISSN: 2159-6026</identifier><identifier>ISBN: 9781424479573</identifier><identifier>ISBN: 1424479576</identifier><identifier>EISBN: 1424479584</identifier><identifier>EISBN: 9781424479580</identifier><identifier>EISBN: 9781424479559</identifier><identifier>EISBN: 142447955X</identifier><identifier>DOI: 10.1109/CMCE.2010.5610497</identifier><language>eng</language><publisher>IEEE</publisher><subject>Adaptation model ; BP algorithm ; Gallium ; Neural network ; the cost of building graphic</subject><ispartof>2010 International Conference on Computer, Mechatronics, Control and Electronic Engineering, 2010, Vol.1, p.305-308</ispartof><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/5610497$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>309,310,780,784,789,790,2058,27925,54920</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/5610497$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc></links><search><creatorcontrib>Kuancheng Zou</creatorcontrib><creatorcontrib>Ye Qian</creatorcontrib><creatorcontrib>Yafei Li</creatorcontrib><creatorcontrib>Pengfei Zhang</creatorcontrib><title>GA neural network of the cost of the building graphic of the analysis and understanding</title><title>2010 International Conference on Computer, Mechatronics, Control and Electronic Engineering</title><addtitle>CMCE</addtitle><description>The costs of pre-building graphic in the construction project management is a very important job, based on neural network theory and the characteristics of the costs of building graphic, raised GA neural network to solve the cost of building graphic problem, applied BP network model and used GA to optimize the weight based on BP algorithm. The calculation examples showed that the accuracy of the cost estimation met the requirements basically.</description><subject>Adaptation model</subject><subject>BP algorithm</subject><subject>Gallium</subject><subject>Neural network</subject><subject>the cost of building graphic</subject><issn>2159-6026</issn><isbn>9781424479573</isbn><isbn>1424479576</isbn><isbn>1424479584</isbn><isbn>9781424479580</isbn><isbn>9781424479559</isbn><isbn>142447955X</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2010</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><sourceid>RIE</sourceid><recordid>eNo1kMtKAzEYhSMqWOs8gLjJC0zN_bIsQ61CxU3BZUkmSRsdZ0oyRfr2BuyszncOPz-cA8AjRguMkX5u3pvVgqBiucCIaXkF7jEjjEnNFbsGlZZq8pLegBnBXNcCEXEHqpy_EEIUK6WkmoHP9RL2_pRMV2T8HdI3HAIcDx62Qx4ntqfYudjv4T6Z4yG2U256051zzAUcPPXOpzwWLJcP4DaYLvvqonOwfVltm9d687F-a5abOmo01sJayiSSXraYGW6Ms0JjyZlytvTioYDmFgeOnRREck44QkFSF9rWGEvn4On_bfTe744p_ph03l1moX-HB1Qi</recordid><startdate>201008</startdate><enddate>201008</enddate><creator>Kuancheng Zou</creator><creator>Ye Qian</creator><creator>Yafei Li</creator><creator>Pengfei Zhang</creator><general>IEEE</general><scope>6IE</scope><scope>6IL</scope><scope>CBEJK</scope><scope>RIE</scope><scope>RIL</scope></search><sort><creationdate>201008</creationdate><title>GA neural network of the cost of the building graphic of the analysis and understanding</title><author>Kuancheng Zou ; Ye Qian ; Yafei Li ; Pengfei Zhang</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-i90t-6bb34707e7c14a5aadb6917548db4975f48d95b1f51d7627552500f73dfccaab3</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2010</creationdate><topic>Adaptation model</topic><topic>BP algorithm</topic><topic>Gallium</topic><topic>Neural network</topic><topic>the cost of building graphic</topic><toplevel>online_resources</toplevel><creatorcontrib>Kuancheng Zou</creatorcontrib><creatorcontrib>Ye Qian</creatorcontrib><creatorcontrib>Yafei Li</creatorcontrib><creatorcontrib>Pengfei Zhang</creatorcontrib><collection>IEEE Electronic Library (IEL) Conference Proceedings</collection><collection>IEEE Proceedings Order Plan All Online (POP All Online) 1998-present by volume</collection><collection>IEEE Xplore All Conference Proceedings</collection><collection>IEEE Electronic Library (IEL)</collection><collection>IEEE Proceedings Order Plans (POP All) 1998-Present</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Kuancheng Zou</au><au>Ye Qian</au><au>Yafei Li</au><au>Pengfei Zhang</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>GA neural network of the cost of the building graphic of the analysis and understanding</atitle><btitle>2010 International Conference on Computer, Mechatronics, Control and Electronic Engineering</btitle><stitle>CMCE</stitle><date>2010-08</date><risdate>2010</risdate><volume>1</volume><spage>305</spage><epage>308</epage><pages>305-308</pages><issn>2159-6026</issn><isbn>9781424479573</isbn><isbn>1424479576</isbn><eisbn>1424479584</eisbn><eisbn>9781424479580</eisbn><eisbn>9781424479559</eisbn><eisbn>142447955X</eisbn><abstract>The costs of pre-building graphic in the construction project management is a very important job, based on neural network theory and the characteristics of the costs of building graphic, raised GA neural network to solve the cost of building graphic problem, applied BP network model and used GA to optimize the weight based on BP algorithm. The calculation examples showed that the accuracy of the cost estimation met the requirements basically.</abstract><pub>IEEE</pub><doi>10.1109/CMCE.2010.5610497</doi><tpages>4</tpages></addata></record>
fulltext fulltext_linktorsrc
identifier ISSN: 2159-6026
ispartof 2010 International Conference on Computer, Mechatronics, Control and Electronic Engineering, 2010, Vol.1, p.305-308
issn 2159-6026
language eng
recordid cdi_ieee_primary_5610497
source IEEE Electronic Library (IEL) Conference Proceedings
subjects Adaptation model
BP algorithm
Gallium
Neural network
the cost of building graphic
title GA neural network of the cost of the building graphic of the analysis and understanding
url https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-06T12%3A52%3A51IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-ieee_6IE&rft_val_fmt=info:ofi/fmt:kev:mtx:book&rft.genre=proceeding&rft.atitle=GA%20neural%20network%20of%20the%20cost%20of%20the%20building%20graphic%20of%20the%20analysis%20and%20understanding&rft.btitle=2010%20International%20Conference%20on%20Computer,%20Mechatronics,%20Control%20and%20Electronic%20Engineering&rft.au=Kuancheng%20Zou&rft.date=2010-08&rft.volume=1&rft.spage=305&rft.epage=308&rft.pages=305-308&rft.issn=2159-6026&rft.isbn=9781424479573&rft.isbn_list=1424479576&rft_id=info:doi/10.1109/CMCE.2010.5610497&rft_dat=%3Cieee_6IE%3E5610497%3C/ieee_6IE%3E%3Curl%3E%3C/url%3E&rft.eisbn=1424479584&rft.eisbn_list=9781424479580&rft.eisbn_list=9781424479559&rft.eisbn_list=142447955X&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_id=info:pmid/&rft_ieee_id=5610497&rfr_iscdi=true