<?xml version="1.0" encoding="UTF-8"?><xml><records><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Qingqing, Z.</style></author><author><style face="normal" font="default" size="100%">Qifeng, Z.</style></author><author><style face="normal" font="default" size="100%">Yongpeng, N.</style></author><author><style face="normal" font="default" size="100%">Fan, Y.</style></author><author><style face="normal" font="default" size="100%">Jiayan, L.</style></author><author><style face="normal" font="default" size="100%">Run, T.</style></author><author><style face="normal" font="default" size="100%">Minda, L.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">A comparison of pattern classification approaches for structural damage identification</style></title><secondary-title><style face="normal" font="default" size="100%">Journal of Digital Information Management</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Extraction algorithms</style></keyword><keyword><style  face="normal" font="default" size="100%">Pattern matching</style></keyword><keyword><style  face="normal" font="default" size="100%">Sensor identificaiton</style></keyword><keyword><style  face="normal" font="default" size="100%">Wavelet packet decomposition</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2012</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2012</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://www.scopus.com/inward/record.url?eid=2-s2.0-84866443034&amp;partnerID=40&amp;md5=17335eb07404e2de90828f9bb812e1da</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">10</style></volume><pages><style face="normal" font="default" size="100%">126 - 130</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">A structural damage identification approach based on wavelet packet decomposition (WPD) and random forests (RF) was proposed and compared with other pattern classification approachs. The main procedure involves extracting energy features from vibration acceleration data through wavelet packet decomposition and then using these features as input for a RF classifier. The experiment was carried on an 8-storey steel shear building model in the case verification. The results show that the proposed method is effective for structure damage detection and can achieve a higher accuracy than other commonly used methods.</style></abstract><issue><style face="normal" font="default" size="100%">2</style></issue><notes><style face="normal" font="default" size="100%">Export Date: 10 July 2014</style></notes></record></records></xml>