{"id":"https://openalex.org/W4296916682","doi":"https://doi.org/10.1109/tim.2022.3208651","title":"A Soft-Sensing Model for Predicting Cement-Specific Surface Area Based on Inception-Residual-Quasi-Recurrent Neural Networks","display_name":"A Soft-Sensing Model for Predicting Cement-Specific Surface Area Based on Inception-Residual-Quasi-Recurrent Neural Networks","publication_year":2022,"publication_date":"2022-01-01","ids":{"openalex":"https://openalex.org/W4296916682","doi":"https://doi.org/10.1109/tim.2022.3208651"},"language":"en","primary_location":{"id":"doi:10.1109/tim.2022.3208651","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tim.2022.3208651","pdf_url":null,"source":{"id":"https://openalex.org/S10892749","display_name":"IEEE Transactions on Instrumentation and Measurement","issn_l":"0018-9456","issn":["0018-9456","1557-9662"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Instrumentation and Measurement","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100682380","display_name":"Chao Sun","orcid":"https://orcid.org/0000-0001-5598-077X"},"institutions":[{"id":"https://openalex.org/I39333907","display_name":"Yanshan University","ror":"https://ror.org/02txfnf15","country_code":"CN","type":"education","lineage":["https://openalex.org/I39333907"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Chao Sun","raw_affiliation_strings":["Instrumentation Department, School of Electrical Engineering, Yanshan University, Qinhuangdao, Hebei, China"],"affiliations":[{"raw_affiliation_string":"Instrumentation Department, School of Electrical Engineering, Yanshan University, Qinhuangdao, Hebei, China","institution_ids":["https://openalex.org/I39333907"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5071783779","display_name":"Haichao Zhao","orcid":"https://orcid.org/0000-0003-3153-1173"},"institutions":[{"id":"https://openalex.org/I39333907","display_name":"Yanshan University","ror":"https://ror.org/02txfnf15","country_code":"CN","type":"education","lineage":["https://openalex.org/I39333907"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Haichao Zhao","raw_affiliation_strings":["Instrumentation Department, Yanshan University, Qinhuangdao, Hebei, China"],"affiliations":[{"raw_affiliation_string":"Instrumentation Department, Yanshan University, Qinhuangdao, Hebei, China","institution_ids":["https://openalex.org/I39333907"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5014558582","display_name":"Yuan Zhang","orcid":"https://orcid.org/0000-0002-8643-0014"},"institutions":[{"id":"https://openalex.org/I39333907","display_name":"Yanshan University","ror":"https://ror.org/02txfnf15","country_code":"CN","type":"education","lineage":["https://openalex.org/I39333907"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuan Zhang","raw_affiliation_strings":["Instrumentation Department, Yanshan University, Qinhuangdao, Hebei, China"],"affiliations":[{"raw_affiliation_string":"Instrumentation Department, Yanshan University, Qinhuangdao, Hebei, China","institution_ids":["https://openalex.org/I39333907"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100319901","display_name":"Yuxuan Zhang","orcid":"https://orcid.org/0000-0002-0751-8908"},"institutions":[{"id":"https://openalex.org/I39333907","display_name":"Yanshan University","ror":"https://ror.org/02txfnf15","country_code":"CN","type":"education","lineage":["https://openalex.org/I39333907"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuxuan Zhang","raw_affiliation_strings":["Instrumentation Department, Yanshan University, Qinhuangdao, Hebei, China"],"affiliations":[{"raw_affiliation_string":"Instrumentation Department, Yanshan University, Qinhuangdao, Hebei, China","institution_ids":["https://openalex.org/I39333907"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5012328712","display_name":"Haoran Guo","orcid":"https://orcid.org/0000-0001-9026-6344"},"institutions":[{"id":"https://openalex.org/I39333907","display_name":"Yanshan University","ror":"https://ror.org/02txfnf15","country_code":"CN","type":"education","lineage":["https://openalex.org/I39333907"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Haoran Guo","raw_affiliation_strings":["Instrumentation Department, Yanshan University, Qinhuangdao, Hebei, China"],"affiliations":[{"raw_affiliation_string":"Instrumentation Department, Yanshan University, Qinhuangdao, Hebei, China","institution_ids":["https://openalex.org/I39333907"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5028273122","display_name":"Xiaochen Hao","orcid":"https://orcid.org/0000-0001-6948-0995"},"institutions":[{"id":"https://openalex.org/I39333907","display_name":"Yanshan University","ror":"https://ror.org/02txfnf15","country_code":"CN","type":"education","lineage":["https://openalex.org/I39333907"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaochen Hao","raw_affiliation_strings":["Instrumentation Department, School of Electrical Engineering, Yanshan University, Qinhuangdao, Hebei, China"],"affiliations":[{"raw_affiliation_string":"Instrumentation Department, School of Electrical Engineering, Yanshan University, Qinhuangdao, Hebei, China","institution_ids":["https://openalex.org/I39333907"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5100682380"],"corresponding_institution_ids":["https://openalex.org/I39333907"],"apc_list":null,"apc_paid":null,"fwci":0.5732,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.62856364,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":"71","issue":null,"first_page":"1","last_page":"15"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11606","display_name":"Infrastructure Maintenance and Monitoring","score":0.996399998664856,"subfield":{"id":"https://openalex.org/subfields/2205","display_name":"Civil and Structural Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11606","display_name":"Infrastructure Maintenance and Monitoring","score":0.996399998664856,"subfield":{"id":"https://openalex.org/subfields/2205","display_name":"Civil and Structural Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T12169","display_name":"Non-Destructive Testing Techniques","score":0.9929999709129333,"subfield":{"id":"https://openalex.org/subfields/2210","display_name":"Mechanical Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T12111","display_name":"Industrial Vision Systems and Defect Detection","score":0.9908999800682068,"subfield":{"id":"https://openalex.org/subfields/2209","display_name":"Industrial and Manufacturing Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.7026942372322083},{"id":"https://openalex.org/keywords/residual","display_name":"Residual","score":0.6432182788848877},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5756215453147888},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5228614807128906},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.443930447101593},{"id":"https://openalex.org/keywords/kernel","display_name":"Kernel (algebra)","score":0.41870641708374023},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3973860740661621},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.34936386346817017},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3435806632041931},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.24932602047920227},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.17267179489135742}],"concepts":[{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.7026942372322083},{"id":"https://openalex.org/C155512373","wikidata":"https://www.wikidata.org/wiki/Q287450","display_name":"Residual","level":2,"score":0.6432182788848877},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5756215453147888},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5228614807128906},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.443930447101593},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.41870641708374023},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3973860740661621},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.34936386346817017},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3435806632041931},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.24932602047920227},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.17267179489135742},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tim.2022.3208651","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tim.2022.3208651","pdf_url":null,"source":{"id":"https://openalex.org/S10892749","display_name":"IEEE Transactions on Instrumentation and Measurement","issn_l":"0018-9456","issn":["0018-9456","1557-9662"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Instrumentation and Measurement","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G7684738659","display_name":null,"funder_award_id":"62073281","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8758957212","display_name":null,"funder_award_id":"F2022203088","funder_id":"https://openalex.org/F4320322163","funder_display_name":"Natural Science Foundation of Hebei Province"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320322163","display_name":"Natural Science Foundation of Hebei Province","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":39,"referenced_works":["https://openalex.org/W1885403314","https://openalex.org/W1953428116","https://openalex.org/W2012714481","https://openalex.org/W2023347674","https://openalex.org/W2047152380","https://openalex.org/W2092700057","https://openalex.org/W2094475848","https://openalex.org/W2096864444","https://openalex.org/W2194775991","https://openalex.org/W2305489430","https://openalex.org/W2357880271","https://openalex.org/W2508457857","https://openalex.org/W2547707148","https://openalex.org/W2783780959","https://openalex.org/W2789241652","https://openalex.org/W2801822775","https://openalex.org/W2804987248","https://openalex.org/W2896320980","https://openalex.org/W2899852195","https://openalex.org/W2944436518","https://openalex.org/W2985259273","https://openalex.org/W2990346675","https://openalex.org/W3020903588","https://openalex.org/W3037969311","https://openalex.org/W3045997366","https://openalex.org/W3117821338","https://openalex.org/W3125838117","https://openalex.org/W3126873503","https://openalex.org/W3160886584","https://openalex.org/W3211764498","https://openalex.org/W3213102846","https://openalex.org/W4206339405","https://openalex.org/W4210445554","https://openalex.org/W4210750366","https://openalex.org/W4224706198","https://openalex.org/W4226430688","https://openalex.org/W4246193833","https://openalex.org/W6639393398","https://openalex.org/W7030414093"],"related_works":["https://openalex.org/W2973451922","https://openalex.org/W3093612317","https://openalex.org/W4287776258","https://openalex.org/W3027997911","https://openalex.org/W2175746458","https://openalex.org/W2732542196","https://openalex.org/W2760085659","https://openalex.org/W2883200793","https://openalex.org/W2738221750","https://openalex.org/W3012978760"],"abstract_inverted_index":{"The":[0,105,228],"cement":[1,10,62,94],"specific":[2,95],"surface":[3,96],"area":[4,97],"is":[5,64,75,100,217,220,226,233],"a":[6,35,115,212],"critical":[7,127],"indicator":[8],"of":[9,13,46,50,61,71,118,126,184,230],"quality.":[11],"Most":[12],"the":[14,44,48,55,59,68,72,87,108,123,146,168,174,185,189,200,205,231],"relevant":[15],"detection":[16],"instruments":[17],"are":[18,197],"now":[19],"used":[20],"for":[21],"offline":[22],"detection,":[23],"which":[24],"has":[25],"high":[26,77],"cost":[27],"and":[28,66,78,121,163,188,207,223],"poor":[29,131],"real-time":[30],"performance.":[31],"For":[32],"this":[33,103],"reason,":[34],"soft":[36],"sensing":[37],"model":[38,74,99,106,232],"can":[39,79],"be":[40],"developed":[41],"to":[42,54,113,159],"achieve":[43,81],"purpose":[45],"predicting":[47],"quality":[49],"cement.":[51],"However,":[52],"due":[53],"data":[56,119,165],"features":[57],"in":[58,102,137,141],"process":[60],"grinding":[63],"complexity":[65],"coupling,":[67],"prediction":[69,83,98,133],"accuracy":[70],"universal":[73],"not":[76,80],"good":[82],"results.":[84],"Based":[85],"on":[86],"above":[88],"problems,":[89],"an":[90],"Inception-Residual-Quasi-recurrent":[91],"Neural":[92],"Networks-based":[93],"proposed":[101],"paper.":[104],"uses":[107],"inception":[109,206],"module\u2019s":[110],"parallel":[111],"structure":[112],"extract":[114],"wider":[116],"variety":[117],"characteristics":[120],"enhance":[122],"reuse":[124],"rate":[125],"features,":[128],"successfully":[129],"avoiding":[130],"network":[132,216],"caused":[134],"by":[135,199,235],"discrepancies":[136],"convolutional":[138,143,149,171],"kernel":[139],"selection":[140],"superimposed":[142],"layers.":[144],"In":[145],"meantime,":[147],"distinct":[148],"modules":[150,209],"use":[151],"independent":[152],"spatial":[153,161],"aggregation":[154,162],"kernels":[155],"from":[156],"different":[157],"channels":[158],"improve":[160],"reduce":[164],"coupling.":[166],"Then,":[167],"traditional":[169],"QRNN":[170],"layers":[172],"at":[173],"previous":[175],"moment":[176],"output":[177],"<italic":[178,191],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[179,182,192,195],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">c</i>":[180],"<sub":[181,194],"xmlns:xlink=\"http://www.w3.org/1999/xlink\"><i>t</i>-1</sub>":[183],"hidden":[186],"layer":[187],"input":[190],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">x</i>":[193],"xmlns:xlink=\"http://www.w3.org/1999/xlink\"><i>t</i></sub>":[196],"replaced":[198],"residual":[201,208],"modules.":[202],"By":[203],"integrating":[204],"with":[210],"QRNN,":[211],"novel":[213],"Inception-R-QRNN":[214],"neural":[215],"constructed.":[218],"Overfitting":[219],"effectively":[221],"avoided,":[222],"generalization":[224],"ability":[225],"improved.":[227],"validity":[229],"verified":[234],"experiments.":[236]},"counts_by_year":[{"year":2025,"cited_by_count":3},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}
