{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,10,29]],"date-time":"2024-10-29T19:11:47Z","timestamp":1730229107729,"version":"3.28.0"},"reference-count":29,"publisher":"IEEE","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2018,7]]},"DOI":"10.1109\/icarm.2018.8610714","type":"proceedings-article","created":{"date-parts":[[2019,1,15]],"date-time":"2019-01-15T08:57:56Z","timestamp":1547542676000},"page":"195-200","source":"Crossref","is-referenced-by-count":0,"title":["Spectral quantitative analysis based on AdaBoost kernel extreme learning machine for gas component prediction of underground cable channel"],"prefix":"10.1109","author":[{"given":"Guang","family":"Shen","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Rongjie","family":"Han","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zhenjie","family":"Wu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Haifeng","family":"Qiu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hua","family":"Fan","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jian","family":"Ye","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1002\/cem.2518"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1007\/s11738-011-0790-0"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1080\/01431160110114943"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1155\/2013\/797302"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2005.12.126"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2010.11.030"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/TSMCB.2011.2168604"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2015.2424995"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.3390\/rs6065795"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1016\/j.jastp.2015.09.014"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2013.09.072"},{"key":"ref4","first-page":"2089","article-title":"Research on the combustion mechanism of asphalt and the composition of harmful gas based on infrared spectral analysis","volume":"32","author":"wu","year":"2012","journal-title":"Spectroscopy and Spectral Analysis"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1016\/j.patrec.2014.12.003"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1016\/j.chemolab.2017.04.004"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1016\/j.chemolab.2012.07.010"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1080\/2150704X.2014.978952"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1016\/j.chemolab.2015.08.024"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1016\/j.geoderma.2010.03.001"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1080\/10739149.2014.908388"},{"key":"ref2","first-page":"3066","article-title":"Spectral quantitative analysis by nonlinear partial least squares based on neural network internal model for flue gas of thermal power plant","volume":"34","author":"cao","year":"2014","journal-title":"Spectroscopy and Spectral Analysis"},{"key":"ref9","doi-asserted-by":"crossref","first-page":"673","DOI":"10.3390\/rs2030673","article-title":"Application of vegetation indices for agricultural crop yield prediction using neural network techniques","volume":"2","author":"panda","year":"2010","journal-title":"Remote Sensing"},{"key":"ref1","first-page":"139","article-title":"Underground power cable environment on-line monitoring and analysis","volume":"33","author":"lyall","year":"2015","journal-title":"International Journal of Comparative Sociology"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1016\/j.inffus.2013.04.006"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1039\/C7AY00353F"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1016\/j.jhydrol.2016.09.035"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1162\/neco.1994.6.6.1289"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2014.10.095"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1109\/TASE.2008.2005640"},{"key":"ref25","first-page":"1","article-title":"Classification with boosting of extreme learning machine over arbitrarily partitioned data","author":"catak","year":"2016","journal-title":"Soft Computing"}],"event":{"name":"2018 3rd International Conference on Advanced Robotics and Mechatronics (ICARM)","start":{"date-parts":[[2018,7,18]]},"location":"Singapore","end":{"date-parts":[[2018,7,20]]}},"container-title":["2018 3rd International Conference on Advanced Robotics and Mechatronics (ICARM)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/8594694\/8610663\/08610714.pdf?arnumber=8610714","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,1,26]],"date-time":"2022-01-26T00:02:05Z","timestamp":1643155325000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/8610714\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018,7]]},"references-count":29,"URL":"https:\/\/doi.org\/10.1109\/icarm.2018.8610714","relation":{},"subject":[],"published":{"date-parts":[[2018,7]]}}}