Skill and tactic diagnosis for table tennis matches based on artificial neural network and genetic algorithm
Due to the complexity, multiplicity and randomness of table tennis matches, the paper presents skill and tactic diagnostic model for table-tennis matches of elite athletes with artificial neural network and genetic algorithm. A back propagation network is used to build basic structure of the model a...
Gespeichert in:
Hauptverfasser: | , , , , , |
---|---|
Format: | Tagungsbericht |
Sprache: | eng |
Schlagworte: | |
Online-Zugang: | Volltext bestellen |
Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
container_end_page | 1851 |
---|---|
container_issue | |
container_start_page | 1847 |
container_title | |
container_volume | 4 |
creator | Wenwu Mao Lijuan Yu Hui Zhang Peiliang Ling Haihang Wang Jie Wang |
description | Due to the complexity, multiplicity and randomness of table tennis matches, the paper presents skill and tactic diagnostic model for table-tennis matches of elite athletes with artificial neural network and genetic algorithm. A back propagation network is used to build basic structure of the model and genetic algorithm is established to optimize the connection weights and threshold values of the neural network to improve the prediction precision and congestion performance. The application results show that it is an effective tool to provide decision support for table-tennis players. |
doi_str_mv | 10.1109/ICNC.2010.5584534 |
format | Conference Proceeding |
fullrecord | <record><control><sourceid>ieee_6IE</sourceid><recordid>TN_cdi_ieee_primary_5584534</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><ieee_id>5584534</ieee_id><sourcerecordid>5584534</sourcerecordid><originalsourceid>FETCH-LOGICAL-i90t-a414980060958ffde15fda33977194da6c8e1a8daa2ddb15a1400779ab8c16e93</originalsourceid><addsrcrecordid>eNo9kMtOwzAURI0AiVL6AYiNfyDFN7bjeIkiHpUqWNB9dRM7qambINsI8fdYpWI1OrM4Gg0ht8CWAEzfr5rXZlmyjFLWQnJxRq5BlEJIXQE__wdZ8wsyK0GqQkspr8gixg_GGAelFNMz4t_3znuKo6EJu-Q6ahwO4xRdpP0Uctl6S5Mdx1wcMHU7G2mL0Ro6jRRDcr3rHHo62q9wjPQ9hf1RONhM2Yh-mIJLu8MNuezRR7s45Zxsnh43zUuxfnteNQ_rwmmWChQgdM1YxfL8vjcWZG-Qc60UaGGw6moLWBvE0pgWJIJgTCmNbd1BZTWfk7s_rbPWbj-DO2D42Z6O4r-KM1vm</addsrcrecordid><sourcetype>Publisher</sourcetype><iscdi>true</iscdi><recordtype>conference_proceeding</recordtype></control><display><type>conference_proceeding</type><title>Skill and tactic diagnosis for table tennis matches based on artificial neural network and genetic algorithm</title><source>IEEE Electronic Library (IEL) Conference Proceedings</source><creator>Wenwu Mao ; Lijuan Yu ; Hui Zhang ; Peiliang Ling ; Haihang Wang ; Jie Wang</creator><creatorcontrib>Wenwu Mao ; Lijuan Yu ; Hui Zhang ; Peiliang Ling ; Haihang Wang ; Jie Wang</creatorcontrib><description>Due to the complexity, multiplicity and randomness of table tennis matches, the paper presents skill and tactic diagnostic model for table-tennis matches of elite athletes with artificial neural network and genetic algorithm. A back propagation network is used to build basic structure of the model and genetic algorithm is established to optimize the connection weights and threshold values of the neural network to improve the prediction precision and congestion performance. The application results show that it is an effective tool to provide decision support for table-tennis players.</description><identifier>ISSN: 2157-9555</identifier><identifier>ISBN: 1424459583</identifier><identifier>ISBN: 9781424459582</identifier><identifier>EISBN: 1424459613</identifier><identifier>EISBN: 9781424459612</identifier><identifier>EISBN: 9781424459599</identifier><identifier>EISBN: 1424459591</identifier><identifier>DOI: 10.1109/ICNC.2010.5584534</identifier><language>eng</language><publisher>IEEE</publisher><subject>artificial neural network ; Artificial neural networks ; Data acquisition ; Educational institutions ; genetic algorithm ; Indexes ; Joints ; Sensitivity analysis ; skill and tactic diagnosis ; table-tennis match ; Training</subject><ispartof>2010 Sixth International Conference on Natural Computation, 2010, Vol.4, p.1847-1851</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/5584534$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>309,310,777,781,786,787,2052,27906,54901</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/5584534$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc></links><search><creatorcontrib>Wenwu Mao</creatorcontrib><creatorcontrib>Lijuan Yu</creatorcontrib><creatorcontrib>Hui Zhang</creatorcontrib><creatorcontrib>Peiliang Ling</creatorcontrib><creatorcontrib>Haihang Wang</creatorcontrib><creatorcontrib>Jie Wang</creatorcontrib><title>Skill and tactic diagnosis for table tennis matches based on artificial neural network and genetic algorithm</title><title>2010 Sixth International Conference on Natural Computation</title><addtitle>ICNC</addtitle><description>Due to the complexity, multiplicity and randomness of table tennis matches, the paper presents skill and tactic diagnostic model for table-tennis matches of elite athletes with artificial neural network and genetic algorithm. A back propagation network is used to build basic structure of the model and genetic algorithm is established to optimize the connection weights and threshold values of the neural network to improve the prediction precision and congestion performance. The application results show that it is an effective tool to provide decision support for table-tennis players.</description><subject>artificial neural network</subject><subject>Artificial neural networks</subject><subject>Data acquisition</subject><subject>Educational institutions</subject><subject>genetic algorithm</subject><subject>Indexes</subject><subject>Joints</subject><subject>Sensitivity analysis</subject><subject>skill and tactic diagnosis</subject><subject>table-tennis match</subject><subject>Training</subject><issn>2157-9555</issn><isbn>1424459583</isbn><isbn>9781424459582</isbn><isbn>1424459613</isbn><isbn>9781424459612</isbn><isbn>9781424459599</isbn><isbn>1424459591</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2010</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><sourceid>RIE</sourceid><recordid>eNo9kMtOwzAURI0AiVL6AYiNfyDFN7bjeIkiHpUqWNB9dRM7qambINsI8fdYpWI1OrM4Gg0ht8CWAEzfr5rXZlmyjFLWQnJxRq5BlEJIXQE__wdZ8wsyK0GqQkspr8gixg_GGAelFNMz4t_3znuKo6EJu-Q6ahwO4xRdpP0Uctl6S5Mdx1wcMHU7G2mL0Ro6jRRDcr3rHHo62q9wjPQ9hf1RONhM2Yh-mIJLu8MNuezRR7s45Zxsnh43zUuxfnteNQ_rwmmWChQgdM1YxfL8vjcWZG-Qc60UaGGw6moLWBvE0pgWJIJgTCmNbd1BZTWfk7s_rbPWbj-DO2D42Z6O4r-KM1vm</recordid><startdate>201008</startdate><enddate>201008</enddate><creator>Wenwu Mao</creator><creator>Lijuan Yu</creator><creator>Hui Zhang</creator><creator>Peiliang Ling</creator><creator>Haihang Wang</creator><creator>Jie Wang</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>Skill and tactic diagnosis for table tennis matches based on artificial neural network and genetic algorithm</title><author>Wenwu Mao ; Lijuan Yu ; Hui Zhang ; Peiliang Ling ; Haihang Wang ; Jie Wang</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-i90t-a414980060958ffde15fda33977194da6c8e1a8daa2ddb15a1400779ab8c16e93</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2010</creationdate><topic>artificial neural network</topic><topic>Artificial neural networks</topic><topic>Data acquisition</topic><topic>Educational institutions</topic><topic>genetic algorithm</topic><topic>Indexes</topic><topic>Joints</topic><topic>Sensitivity analysis</topic><topic>skill and tactic diagnosis</topic><topic>table-tennis match</topic><topic>Training</topic><toplevel>online_resources</toplevel><creatorcontrib>Wenwu Mao</creatorcontrib><creatorcontrib>Lijuan Yu</creatorcontrib><creatorcontrib>Hui Zhang</creatorcontrib><creatorcontrib>Peiliang Ling</creatorcontrib><creatorcontrib>Haihang Wang</creatorcontrib><creatorcontrib>Jie Wang</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>Wenwu Mao</au><au>Lijuan Yu</au><au>Hui Zhang</au><au>Peiliang Ling</au><au>Haihang Wang</au><au>Jie Wang</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>Skill and tactic diagnosis for table tennis matches based on artificial neural network and genetic algorithm</atitle><btitle>2010 Sixth International Conference on Natural Computation</btitle><stitle>ICNC</stitle><date>2010-08</date><risdate>2010</risdate><volume>4</volume><spage>1847</spage><epage>1851</epage><pages>1847-1851</pages><issn>2157-9555</issn><isbn>1424459583</isbn><isbn>9781424459582</isbn><eisbn>1424459613</eisbn><eisbn>9781424459612</eisbn><eisbn>9781424459599</eisbn><eisbn>1424459591</eisbn><abstract>Due to the complexity, multiplicity and randomness of table tennis matches, the paper presents skill and tactic diagnostic model for table-tennis matches of elite athletes with artificial neural network and genetic algorithm. A back propagation network is used to build basic structure of the model and genetic algorithm is established to optimize the connection weights and threshold values of the neural network to improve the prediction precision and congestion performance. The application results show that it is an effective tool to provide decision support for table-tennis players.</abstract><pub>IEEE</pub><doi>10.1109/ICNC.2010.5584534</doi><tpages>5</tpages></addata></record> |
fulltext | fulltext_linktorsrc |
identifier | ISSN: 2157-9555 |
ispartof | 2010 Sixth International Conference on Natural Computation, 2010, Vol.4, p.1847-1851 |
issn | 2157-9555 |
language | eng |
recordid | cdi_ieee_primary_5584534 |
source | IEEE Electronic Library (IEL) Conference Proceedings |
subjects | artificial neural network Artificial neural networks Data acquisition Educational institutions genetic algorithm Indexes Joints Sensitivity analysis skill and tactic diagnosis table-tennis match Training |
title | Skill and tactic diagnosis for table tennis matches based on artificial neural network and genetic algorithm |
url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-21T01%3A53%3A05IST&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=Skill%20and%20tactic%20diagnosis%20for%20table%20tennis%20matches%20based%20on%20artificial%20neural%20network%20and%20genetic%20algorithm&rft.btitle=2010%20Sixth%20International%20Conference%20on%20Natural%20Computation&rft.au=Wenwu%20Mao&rft.date=2010-08&rft.volume=4&rft.spage=1847&rft.epage=1851&rft.pages=1847-1851&rft.issn=2157-9555&rft.isbn=1424459583&rft.isbn_list=9781424459582&rft_id=info:doi/10.1109/ICNC.2010.5584534&rft_dat=%3Cieee_6IE%3E5584534%3C/ieee_6IE%3E%3Curl%3E%3C/url%3E&rft.eisbn=1424459613&rft.eisbn_list=9781424459612&rft.eisbn_list=9781424459599&rft.eisbn_list=1424459591&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_id=info:pmid/&rft_ieee_id=5584534&rfr_iscdi=true |