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Application study on BP network in identifying reliability life distribution types
It is important to select reasonable life distribution types on product reliability analysis. After analyzed a few reliability life distinguish types, the paper put forward a method of selecting reliability life distribution types based on Artificial Neural Network. On basis of theory analysis, the...
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creator | Junyuan Gu Tingxue Xu Haijian Chen |
description | It is important to select reasonable life distribution types on product reliability analysis. After analyzed a few reliability life distinguish types, the paper put forward a method of selecting reliability life distribution types based on Artificial Neural Network. On basis of theory analysis, the method is tested by computer simulated data. The character of this method is simple principle, easy calculated and convenient applied. |
doi_str_mv | 10.1109/ICNC.2010.5582970 |
format | conference_proceeding |
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After analyzed a few reliability life distinguish types, the paper put forward a method of selecting reliability life distribution types based on Artificial Neural Network. On basis of theory analysis, the method is tested by computer simulated data. 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After analyzed a few reliability life distinguish types, the paper put forward a method of selecting reliability life distribution types based on Artificial Neural Network. On basis of theory analysis, the method is tested by computer simulated data. The character of this method is simple principle, easy calculated and convenient applied.</description><subject>artificial Neural Network</subject><subject>Artificial neural networks</subject><subject>Computer network reliability</subject><subject>life distinguish types</subject><subject>Neurons</subject><subject>pattern recognition</subject><subject>Random variables</subject><subject>reliability</subject><subject>Reliability theory</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><recordid>eNo9kMtOwzAQRY0AiVL6AYiNfyDF40cdL0vEo1IFCHVfxfEYDYQ0il2h_D0VVKzuOZuzuIxdg5gDCHe7qp6ruRQHNaaUzooTdglaam3cAtTpv5hSnbGJBGMLZ4y5YLOUPoQQCqy1wk3Y27LvW2rqTLuOp7wPIz_A3SvvMH_vhk9OHaeAXaY4UvfOB2yp9tRSHnlLEXmglAfy-99AHntMV-w81m3C2XGnbPNwv6meivXL46pargtyIhdRYQxQgndSSuVqbJRtmhgVBPTeRVdGNN6XUC-CbqRVKDV69AsbrHYS1JTd_GUJEbf9QF_1MG6Pd6gfFy1T9A</recordid><startdate>201008</startdate><enddate>201008</enddate><creator>Junyuan Gu</creator><creator>Tingxue Xu</creator><creator>Haijian Chen</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>Application study on BP network in identifying reliability life distribution types</title><author>Junyuan Gu ; Tingxue Xu ; Haijian Chen</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-i90t-f3efd181b922239aec37ccff31debb9f98fe5bb81a6d4c273e24ebeb67d749213</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>Computer network reliability</topic><topic>life distinguish types</topic><topic>Neurons</topic><topic>pattern recognition</topic><topic>Random variables</topic><topic>reliability</topic><topic>Reliability theory</topic><topic>Training</topic><toplevel>online_resources</toplevel><creatorcontrib>Junyuan Gu</creatorcontrib><creatorcontrib>Tingxue Xu</creatorcontrib><creatorcontrib>Haijian Chen</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 Explore</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>Junyuan Gu</au><au>Tingxue Xu</au><au>Haijian Chen</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>Application study on BP network in identifying reliability life distribution types</atitle><btitle>2010 Sixth International Conference on Natural Computation</btitle><stitle>ICNC</stitle><date>2010-08</date><risdate>2010</risdate><volume>1</volume><spage>185</spage><epage>188</epage><pages>185-188</pages><issn>2157-9555</issn><isbn>1424459583</isbn><isbn>9781424459582</isbn><eisbn>1424459613</eisbn><eisbn>9781424459612</eisbn><eisbn>9781424459599</eisbn><eisbn>1424459591</eisbn><abstract>It is important to select reasonable life distribution types on product reliability analysis. After analyzed a few reliability life distinguish types, the paper put forward a method of selecting reliability life distribution types based on Artificial Neural Network. On basis of theory analysis, the method is tested by computer simulated data. The character of this method is simple principle, easy calculated and convenient applied.</abstract><pub>IEEE</pub><doi>10.1109/ICNC.2010.5582970</doi><tpages>4</tpages></addata></record> |
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subjects | artificial Neural Network Artificial neural networks Computer network reliability life distinguish types Neurons pattern recognition Random variables reliability Reliability theory Training |
title | Application study on BP network in identifying reliability life distribution types |
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