{"id":"https://openalex.org/W4313595068","doi":"https://doi.org/10.1007/s44196-022-00175-5","title":"The CTCN-LightGBM Joint Model for Industrial Balanced Loading Prediction","display_name":"The CTCN-LightGBM Joint Model for Industrial Balanced Loading Prediction","publication_year":2023,"publication_date":"2023-01-04","ids":{"openalex":"https://openalex.org/W4313595068","doi":"https://doi.org/10.1007/s44196-022-00175-5"},"language":"en","primary_location":{"id":"doi:10.1007/s44196-022-00175-5","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s44196-022-00175-5","pdf_url":"https://link.springer.com/content/pdf/10.1007/s44196-022-00175-5.pdf","source":{"id":"https://openalex.org/S190680769","display_name":"International Journal of Computational Intelligence Systems","issn_l":"1875-6883","issn":["1875-6883","1875-6891"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319965","host_organization_name":"Springer Nature","host_organization_lineage":["https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Computational Intelligence Systems","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://link.springer.com/content/pdf/10.1007/s44196-022-00175-5.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5108056724","display_name":"Zihua Chen","orcid":"https://orcid.org/0000-0002-2034-448X"},"institutions":[{"id":"https://openalex.org/I184681353","display_name":"Anhui University of Science and Technology","ror":"https://ror.org/00q9atg80","country_code":"CN","type":"education","lineage":["https://openalex.org/I184681353"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Zihua Chen","raw_affiliation_strings":["School of Mechanical Engineering, Anhui University of Science and Technology, Huainan, 232001, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Mechanical Engineering, Anhui University of Science and Technology, Huainan, 232001, China","institution_ids":["https://openalex.org/I184681353"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101568488","display_name":"Chuanli Wang","orcid":"https://orcid.org/0000-0002-0016-8650"},"institutions":[{"id":"https://openalex.org/I184681353","display_name":"Anhui University of Science and Technology","ror":"https://ror.org/00q9atg80","country_code":"CN","type":"education","lineage":["https://openalex.org/I184681353"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chuanli Wang","raw_affiliation_strings":["School of Mechanical Engineering, Anhui University of Science and Technology, Huainan, 232001, China"],"raw_orcid":"https://orcid.org/0000-0002-0016-8650","affiliations":[{"raw_affiliation_string":"School of Mechanical Engineering, Anhui University of Science and Technology, Huainan, 232001, China","institution_ids":["https://openalex.org/I184681353"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5037469759","display_name":"Huawei Jin","orcid":"https://orcid.org/0000-0003-0836-5525"},"institutions":[{"id":"https://openalex.org/I184681353","display_name":"Anhui University of Science and Technology","ror":"https://ror.org/00q9atg80","country_code":"CN","type":"education","lineage":["https://openalex.org/I184681353"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Huawei Jin","raw_affiliation_strings":["School of Mechanical Engineering, Anhui University of Science and Technology, Huainan, 232001, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Mechanical Engineering, Anhui University of Science and Technology, Huainan, 232001, China","institution_ids":["https://openalex.org/I184681353"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103166173","display_name":"Jingzhao Li","orcid":"https://orcid.org/0009-0008-0389-6224"},"institutions":[{"id":"https://openalex.org/I184681353","display_name":"Anhui University of Science and Technology","ror":"https://ror.org/00q9atg80","country_code":"CN","type":"education","lineage":["https://openalex.org/I184681353"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jingzhao Li","raw_affiliation_strings":["School of Computer Science and Engineering, Anhui University of Science and Technology, Huainan, 232001, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, Anhui University of Science and Technology, Huainan, 232001, China","institution_ids":["https://openalex.org/I184681353"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5005506675","display_name":"Shunxiang Zhang","orcid":null},"institutions":[{"id":"https://openalex.org/I184681353","display_name":"Anhui University of Science and Technology","ror":"https://ror.org/00q9atg80","country_code":"CN","type":"education","lineage":["https://openalex.org/I184681353"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shunxiang Zhang","raw_affiliation_strings":["School of Computer Science and Engineering, Anhui University of Science and Technology, Huainan, 232001, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, Anhui University of Science and Technology, Huainan, 232001, China","institution_ids":["https://openalex.org/I184681353"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5085506466","display_name":"Qichun Ouyang","orcid":null},"institutions":[{"id":"https://openalex.org/I4210096896","display_name":"Huaibei Mining (China)","ror":"https://ror.org/00tpvmh02","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210096896"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qichun Ouyang","raw_affiliation_strings":["Huaibei Mining Co., Ltd, Huaibei, 235000, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Huaibei Mining Co., Ltd, Huaibei, 235000, China","institution_ids":["https://openalex.org/I4210096896"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5108056724"],"corresponding_institution_ids":["https://openalex.org/I184681353"],"apc_list":{"value":1390,"currency":"GBP","value_usd":1704},"apc_paid":{"value":1390,"currency":"GBP","value_usd":1704},"fwci":1.1394,"has_fulltext":true,"cited_by_count":8,"citation_normalized_percentile":{"value":0.73605972,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":98},"biblio":{"volume":"16","issue":"1","first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11606","display_name":"Infrastructure Maintenance and Monitoring","score":0.9984999895095825,"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":0.9984999895095825,"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/T10534","display_name":"Structural Health Monitoring Techniques","score":0.9696999788284302,"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/T10264","display_name":"Asphalt Pavement Performance Evaluation","score":0.9659000039100647,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7193818688392639},{"id":"https://openalex.org/keywords/normalization","display_name":"Normalization (sociology)","score":0.6698669195175171},{"id":"https://openalex.org/keywords/boosting","display_name":"Boosting (machine learning)","score":0.6386418342590332},{"id":"https://openalex.org/keywords/residual","display_name":"Residual","score":0.6294020414352417},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5926564931869507},{"id":"https://openalex.org/keywords/feature-selection","display_name":"Feature selection","score":0.5851023197174072},{"id":"https://openalex.org/keywords/preprocessor","display_name":"Preprocessor","score":0.5439366102218628},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5266292691230774},{"id":"https://openalex.org/keywords/gradient-boosting","display_name":"Gradient boosting","score":0.5250556468963623},{"id":"https://openalex.org/keywords/block","display_name":"Block (permutation group theory)","score":0.4969988167285919},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.44776850938796997},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3498120903968811},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.25974732637405396},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1908637285232544},{"id":"https://openalex.org/keywords/random-forest","display_name":"Random forest","score":0.18170562386512756}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7193818688392639},{"id":"https://openalex.org/C136886441","wikidata":"https://www.wikidata.org/wiki/Q926129","display_name":"Normalization (sociology)","level":2,"score":0.6698669195175171},{"id":"https://openalex.org/C46686674","wikidata":"https://www.wikidata.org/wiki/Q466303","display_name":"Boosting (machine learning)","level":2,"score":0.6386418342590332},{"id":"https://openalex.org/C155512373","wikidata":"https://www.wikidata.org/wiki/Q287450","display_name":"Residual","level":2,"score":0.6294020414352417},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5926564931869507},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.5851023197174072},{"id":"https://openalex.org/C34736171","wikidata":"https://www.wikidata.org/wiki/Q918333","display_name":"Preprocessor","level":2,"score":0.5439366102218628},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5266292691230774},{"id":"https://openalex.org/C70153297","wikidata":"https://www.wikidata.org/wiki/Q5591907","display_name":"Gradient boosting","level":3,"score":0.5250556468963623},{"id":"https://openalex.org/C2777210771","wikidata":"https://www.wikidata.org/wiki/Q4927124","display_name":"Block (permutation group theory)","level":2,"score":0.4969988167285919},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.44776850938796997},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3498120903968811},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.25974732637405396},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1908637285232544},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.18170562386512756},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C19165224","wikidata":"https://www.wikidata.org/wiki/Q23404","display_name":"Anthropology","level":1,"score":0.0},{"id":"https://openalex.org/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1007/s44196-022-00175-5","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s44196-022-00175-5","pdf_url":"https://link.springer.com/content/pdf/10.1007/s44196-022-00175-5.pdf","source":{"id":"https://openalex.org/S190680769","display_name":"International Journal of Computational Intelligence Systems","issn_l":"1875-6883","issn":["1875-6883","1875-6891"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319965","host_organization_name":"Springer Nature","host_organization_lineage":["https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Computational Intelligence Systems","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:cdd94d98550945d4b65f1ccbb17b36bd","is_oa":true,"landing_page_url":"https://doaj.org/article/cdd94d98550945d4b65f1ccbb17b36bd","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"International Journal of Computational Intelligence Systems, Vol 16, Iss 1, Pp 1-20 (2023)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1007/s44196-022-00175-5","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s44196-022-00175-5","pdf_url":"https://link.springer.com/content/pdf/10.1007/s44196-022-00175-5.pdf","source":{"id":"https://openalex.org/S190680769","display_name":"International Journal of Computational Intelligence Systems","issn_l":"1875-6883","issn":["1875-6883","1875-6891"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319965","host_organization_name":"Springer Nature","host_organization_lineage":["https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Computational Intelligence Systems","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/9","score":0.5299999713897705,"display_name":"Industry, innovation and infrastructure"}],"awards":[{"id":"https://openalex.org/G4387331689","display_name":null,"funder_award_id":"No.51675003","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G4744907508","display_name":null,"funder_award_id":"51675003","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7062155526","display_name":null,"funder_award_id":"No.51874010","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7740326052","display_name":"\u77ff\u5c71\u4fe1\u606f\u4e0e\u7269\u7406\u63a5\u53e3\u673a\u5236\u4e0e\u5b89\u5168\u4ea4\u4e92\u65b9\u6cd5\u7814\u7a76","funder_award_id":"51874010","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":true,"grobid_xml":false},"content_urls":{"pdf":"https://content.openalex.org/works/W4313595068.pdf"},"referenced_works_count":32,"referenced_works":["https://openalex.org/W2740570963","https://openalex.org/W2776458183","https://openalex.org/W2940914091","https://openalex.org/W2968704627","https://openalex.org/W3006045819","https://openalex.org/W3010176271","https://openalex.org/W3010200560","https://openalex.org/W3011556060","https://openalex.org/W3025111165","https://openalex.org/W3038216073","https://openalex.org/W3040694753","https://openalex.org/W3042046988","https://openalex.org/W3047647423","https://openalex.org/W3088482463","https://openalex.org/W3090516321","https://openalex.org/W3124419131","https://openalex.org/W3124526397","https://openalex.org/W3126332733","https://openalex.org/W3136021864","https://openalex.org/W3156724860","https://openalex.org/W3158482614","https://openalex.org/W3171438403","https://openalex.org/W3173651219","https://openalex.org/W3177704699","https://openalex.org/W3193386362","https://openalex.org/W3197961530","https://openalex.org/W3198120912","https://openalex.org/W3198933754","https://openalex.org/W3200849552","https://openalex.org/W3202593572","https://openalex.org/W3204914169","https://openalex.org/W4225822768"],"related_works":["https://openalex.org/W2967733078","https://openalex.org/W3204430031","https://openalex.org/W3137904399","https://openalex.org/W4310492845","https://openalex.org/W2885778889","https://openalex.org/W4310224730","https://openalex.org/W2766514146","https://openalex.org/W4289703016","https://openalex.org/W2885516856","https://openalex.org/W3094138326"],"abstract_inverted_index":{"Abstract":[0],"Balanced":[1],"industrial":[2],"loading":[3,25],"mainly":[4],"relies":[5],"on":[6],"accurate":[7],"multi-adjustment":[8,36,133,158],"values,":[9],"including":[10],"the":[11,18,28,33,40,49,55,64,89,100,108,116,123,126,139,146],"truck":[12],"speed":[13],"and":[14,54,68,77,145],"chute":[15],"flow.":[16],"However,":[17],"existing":[19],"models":[20],"are":[21,72],"weak":[22],"in":[23,88],"real-time":[24],"prediction":[26],"because":[27],"single-objective":[29],"regression":[30],"may":[31],"ignore":[32],"correlation":[34],"of":[35,125],"parameters.":[37],"To":[38],"solve":[39],"problem,":[41],"we":[42,80,137],"propose":[43,81],"a":[44,82],"joint":[45],"model":[46,152],"that":[47,150],"fuses":[48],"composited-residual-block":[50,90],"temporal":[51,91],"convolutional":[52,86,92],"network":[53,93],"light":[56,127],"gradient":[57,128],"boosting":[58,129],"machine":[59,130],"(i.e.,":[60],"called":[61],"CTCN-LightGBM).":[62],"First,":[63],"instance":[65],"selection":[66],"deviations":[67],"abnormal":[69],"supplement":[70],"methods":[71],"used":[73],"for":[74,157],"data":[75],"preprocessing":[76],"normalization.":[78],"Second,":[79],"side-road":[83],"dimensionality":[84],"reduction":[85],"branch":[87],"to":[94,111,131],"extract":[95],"collaborative":[96],"features":[97,106,110],"effectively.":[98],"Third,":[99],"feature":[101,118],"re-enlargement":[102],"method":[103],"reconstructs":[104],"extracted":[105],"with":[107,141],"original":[109],"improve":[112],"extraction":[113],"accuracy.":[114],"Fourth,":[115],"reconstructed":[117],"matrix":[119],"is":[120],"utilized":[121],"as":[122],"input":[124],"predict":[132],"values":[134],"parallelly.":[135],"Finally,":[136],"compare":[138],"CTCN-LightGBM":[140],"other":[142],"related":[143],"models,":[144],"experimental":[147],"results":[148],"show":[149],"our":[151],"can":[153],"obtain":[154],"superior":[155],"effects":[156],"value":[159],"prediction.":[160]},"counts_by_year":[{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":2}],"updated_date":"2026-06-06T09:05:17.133730","created_date":"2025-10-10T00:00:00"}
