{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,13]],"date-time":"2025-11-13T07:12:58Z","timestamp":1763017978667,"version":"3.37.3"},"reference-count":46,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","license":[{"start":{"date-parts":[[2019,1,1]],"date-time":"2019-01-01T00:00:00Z","timestamp":1546300800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/OAPA.html"}],"funder":[{"DOI":"10.13039\/501100003091","name":"Shandong Province","doi-asserted-by":"publisher","award":["2017GGX10140"],"award-info":[{"award-number":["2017GGX10140"]}],"id":[{"id":"10.13039\/501100003091","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100012226","name":"Fundamental Research Funds for the Central Universities","doi-asserted-by":"crossref","award":["2015020031"],"award-info":[{"award-number":["2015020031"]}],"id":[{"id":"10.13039\/501100012226","id-type":"DOI","asserted-by":"crossref"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61309024"],"award-info":[{"award-number":["61309024"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Access"],"published-print":{"date-parts":[[2019]]},"DOI":"10.1109\/access.2019.2902865","type":"journal-article","created":{"date-parts":[[2019,3,4]],"date-time":"2019-03-04T14:47:21Z","timestamp":1551710841000},"page":"32754-32764","source":"Crossref","is-referenced-by-count":28,"title":["Modeling IoT Equipment With Graph Neural Networks"],"prefix":"10.1109","volume":"7","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-9800-1068","authenticated-orcid":false,"given":"Weishan","family":"Zhang","sequence":"first","affiliation":[]},{"given":"Yafei","family":"Zhang","sequence":"additional","affiliation":[]},{"given":"Liang","family":"Xu","sequence":"additional","affiliation":[]},{"given":"Jiehan","family":"Zhou","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6747-8151","authenticated-orcid":false,"given":"Yan","family":"Liu","sequence":"additional","affiliation":[]},{"given":"Mu","family":"Gu","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7357-6671","authenticated-orcid":false,"given":"Xin","family":"Liu","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6706-6640","authenticated-orcid":false,"given":"Su","family":"Yang","sequence":"additional","affiliation":[]}],"member":"263","reference":[{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1007\/s11071-015-2571-6"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2017.03.023"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1016\/j.measurement.2008.08.013"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1016\/j.compag.2008.12.004"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1103\/PhysRevX.6.011021"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1103\/PhysRevLett.120.024102"},{"key":"ref37","first-page":"42","article-title":"Study on energy use pattern, optimization of energy consumption and CO2 emission for greenhouse tomato production","volume":"7","author":"abdi","year":"2013","journal-title":"International Journal of Natural Science and Engineering IJNSE"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1016\/j.enbuild.2005.09.007"},{"key":"ref35","doi-asserted-by":"crossref","first-page":"436","DOI":"10.1038\/nature14539","article-title":"Deep learning","volume":"521","author":"lecun","year":"2015","journal-title":"Nature"},{"key":"ref34","first-page":"73","article-title":"An analysis of energy input-output and emissions of greenhouse gases from agricultural productions","volume":"6","author":"abdi","year":"2012","journal-title":"International Journal of Natural Science and Engineering IJNSE"},{"journal-title":"Relational inductive biases deep learning and graph networks","year":"2018","author":"battaglia","key":"ref10"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1016\/j.proeng.2017.03.240"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-93417-4_38"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2016.2582924"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.2307\/2284333"},{"journal-title":"Auto-encoding variational bayes","year":"2013","author":"kingma","key":"ref14"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.90"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1145\/170035.170072"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-94289-6_27"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2018.2825538"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1002\/spe.2426"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1126\/science.1091277"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/MNET.2018.1800029"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1103\/PhysRevE.92.010902"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1016\/j.inpa.2018.01.003"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/TII.2018.2804669"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1038\/s41598-017-10257-6"},{"journal-title":"Deep learning algorithm for data-driven simulation of noisy dynamical system","year":"2018","author":"yeo","key":"ref5"},{"journal-title":"Deep convolutional networks on graph-structured data","year":"2015","author":"henaff","key":"ref8"},{"key":"ref7","first-page":"2204","article-title":"Recurrent models of visual attention","author":"mnih","year":"2014","journal-title":"Proc Adv Neural Inf Process Syst"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/LCOMM.2018.2803054"},{"journal-title":"Mapping images to scene graphs with permutation-invariant structured prediction","year":"2018","author":"herzig","key":"ref9"},{"key":"ref1","first-page":"36","article-title":"Optimization via simulation based on neural network","volume":"30","author":"wu","year":"2018","journal-title":"J Syst Simul"},{"key":"ref46","first-page":"1","article-title":"Automatic differentiation in pytorch","author":"paszke","year":"2017","journal-title":"Proc 31st Conf Neural Inf Process Syst"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1016\/j.wsj.2017.04.001"},{"journal-title":"Adam A method for stochastic optimization","year":"2014","author":"kingma","key":"ref45"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1007\/s10956-015-9581-5"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1007\/s00450-017-0346-7"},{"journal-title":"Deep nets What have they ever done for vision?","year":"2018","author":"yuille","key":"ref42"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1109\/TPWRS.2010.2080325"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1016\/j.apenergy.2016.11.111"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1121\/1.2931959"},{"journal-title":"Categorical reparameterization with gumbel-softmax","year":"2016","author":"jang","key":"ref44"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1109\/IYCE.2017.8003734"},{"journal-title":"Neural message passing for quantum chemistry","year":"2017","author":"gilmer","key":"ref43"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1109\/MCOM.2017.1700168"}],"container-title":["IEEE Access"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/6287639\/8600701\/08658112.pdf?arnumber=8658112","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,1,12]],"date-time":"2022-01-12T11:54:57Z","timestamp":1641988497000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/8658112\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019]]},"references-count":46,"URL":"https:\/\/doi.org\/10.1109\/access.2019.2902865","relation":{},"ISSN":["2169-3536"],"issn-type":[{"type":"electronic","value":"2169-3536"}],"subject":[],"published":{"date-parts":[[2019]]}}}