Bridge health condition evaluation method and system based on radial base function neural network
The invention provides a bridge health condition evaluation method based on a radial base function neural network. The method includes the following steps that S1, network evaluation parameters and adata value set of physical quantities of a bridge are obtained; S2, according to the network evaluati...
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creator | TAN LINGSHENG SU JIAN HUANG XIAODAN LI JIEMING JI XUAN |
description | The invention provides a bridge health condition evaluation method based on a radial base function neural network. The method includes the following steps that S1, network evaluation parameters and adata value set of physical quantities of a bridge are obtained; S2, according to the network evaluation parameters and the data value set, a bridge health condition evaluation value is calculated through the radial base function neural network; S3, the evaluation value and a bridge damage index grade are compared, so that the health condition grade of the bridge is judged. The evaluation process of the method has high objectivity and scientificity. Meanwhile, the invention further provides an evaluation system based on the method. The evaluation system is used for achieving automation of the evaluation process, manual calculation of an evaluator is not needed, and the bridge evaluation efficiency is greatly improved.
本发明提供的种基于径向基函数神经网络的桥梁健康状况的评估方法,包括以下步骤:S1:获取网络评估参数和桥梁的物理量的数据值组;S2:根据所述网络评估参数和所述数据值组,通过径向基函数神经网络计算桥梁 |
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本发明提供的种基于径向基函数神经网络的桥梁健康状况的评估方法,包括以下步骤:S1:获取网络评估参数和桥梁的物理量的数据值组;S2:根据所述网络评估参数和所述数据值组,通过径向基函数神经网络计算桥梁</description><language>chi ; eng</language><subject>CALCULATING ; COMPUTING ; COUNTING ; ELECTRIC DIGITAL DATA PROCESSING ; PHYSICS</subject><creationdate>2018</creationdate><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://worldwide.espacenet.com/publicationDetails/biblio?FT=D&date=20180608&DB=EPODOC&CC=CN&NR=108133070A$$EHTML$$P50$$Gepo$$Hfree_for_read</linktohtml><link.rule.ids>230,308,776,881,25544,76293</link.rule.ids><linktorsrc>$$Uhttps://worldwide.espacenet.com/publicationDetails/biblio?FT=D&date=20180608&DB=EPODOC&CC=CN&NR=108133070A$$EView_record_in_European_Patent_Office$$FView_record_in_$$GEuropean_Patent_Office$$Hfree_for_read</linktorsrc></links><search><creatorcontrib>TAN LINGSHENG</creatorcontrib><creatorcontrib>SU JIAN</creatorcontrib><creatorcontrib>HUANG XIAODAN</creatorcontrib><creatorcontrib>LI JIEMING</creatorcontrib><creatorcontrib>JI XUAN</creatorcontrib><title>Bridge health condition evaluation method and system based on radial base function neural network</title><description>The invention provides a bridge health condition evaluation method based on a radial base function neural network. The method includes the following steps that S1, network evaluation parameters and adata value set of physical quantities of a bridge are obtained; S2, according to the network evaluation parameters and the data value set, a bridge health condition evaluation value is calculated through the radial base function neural network; S3, the evaluation value and a bridge damage index grade are compared, so that the health condition grade of the bridge is judged. The evaluation process of the method has high objectivity and scientificity. Meanwhile, the invention further provides an evaluation system based on the method. The evaluation system is used for achieving automation of the evaluation process, manual calculation of an evaluator is not needed, and the bridge evaluation efficiency is greatly improved.
本发明提供的种基于径向基函数神经网络的桥梁健康状况的评估方法,包括以下步骤:S1:获取网络评估参数和桥梁的物理量的数据值组;S2:根据所述网络评估参数和所述数据值组,通过径向基函数神经网络计算桥梁</description><subject>CALCULATING</subject><subject>COMPUTING</subject><subject>COUNTING</subject><subject>ELECTRIC DIGITAL DATA PROCESSING</subject><subject>PHYSICS</subject><fulltext>true</fulltext><rsrctype>patent</rsrctype><creationdate>2018</creationdate><recordtype>patent</recordtype><sourceid>EVB</sourceid><recordid>eNqNijsOwjAQRNNQIOAOywGQHLmAFiIQFRV9tNgbbMVZR_6AuD2WxQGoZubNWzZ4ClY_CQyhSwaUZ22T9Qz0Qpex1omS8RqQNcRPTDTBAyNpKFdAbdHVDUNmVX2mHApkSm8fxnWzGNBF2vxy1Wwv53t33dHse4ozKipm391acWilFHtxlP84XxucPcw</recordid><startdate>20180608</startdate><enddate>20180608</enddate><creator>TAN LINGSHENG</creator><creator>SU JIAN</creator><creator>HUANG XIAODAN</creator><creator>LI JIEMING</creator><creator>JI XUAN</creator><scope>EVB</scope></search><sort><creationdate>20180608</creationdate><title>Bridge health condition evaluation method and system based on radial base function neural network</title><author>TAN LINGSHENG ; SU JIAN ; HUANG XIAODAN ; LI JIEMING ; JI XUAN</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-epo_espacenet_CN108133070A3</frbrgroupid><rsrctype>patents</rsrctype><prefilter>patents</prefilter><language>chi ; eng</language><creationdate>2018</creationdate><topic>CALCULATING</topic><topic>COMPUTING</topic><topic>COUNTING</topic><topic>ELECTRIC DIGITAL DATA PROCESSING</topic><topic>PHYSICS</topic><toplevel>online_resources</toplevel><creatorcontrib>TAN LINGSHENG</creatorcontrib><creatorcontrib>SU JIAN</creatorcontrib><creatorcontrib>HUANG XIAODAN</creatorcontrib><creatorcontrib>LI JIEMING</creatorcontrib><creatorcontrib>JI XUAN</creatorcontrib><collection>esp@cenet</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>TAN LINGSHENG</au><au>SU JIAN</au><au>HUANG XIAODAN</au><au>LI JIEMING</au><au>JI XUAN</au><format>patent</format><genre>patent</genre><ristype>GEN</ristype><title>Bridge health condition evaluation method and system based on radial base function neural network</title><date>2018-06-08</date><risdate>2018</risdate><abstract>The invention provides a bridge health condition evaluation method based on a radial base function neural network. The method includes the following steps that S1, network evaluation parameters and adata value set of physical quantities of a bridge are obtained; S2, according to the network evaluation parameters and the data value set, a bridge health condition evaluation value is calculated through the radial base function neural network; S3, the evaluation value and a bridge damage index grade are compared, so that the health condition grade of the bridge is judged. The evaluation process of the method has high objectivity and scientificity. Meanwhile, the invention further provides an evaluation system based on the method. The evaluation system is used for achieving automation of the evaluation process, manual calculation of an evaluator is not needed, and the bridge evaluation efficiency is greatly improved.
本发明提供的种基于径向基函数神经网络的桥梁健康状况的评估方法,包括以下步骤:S1:获取网络评估参数和桥梁的物理量的数据值组;S2:根据所述网络评估参数和所述数据值组,通过径向基函数神经网络计算桥梁</abstract><oa>free_for_read</oa></addata></record> |
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subjects | CALCULATING COMPUTING COUNTING ELECTRIC DIGITAL DATA PROCESSING PHYSICS |
title | Bridge health condition evaluation method and system based on radial base function neural network |
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