{"id":"https://openalex.org/W3013045010","doi":"https://doi.org/10.2298/tsci191218128y","title":"Thermal energy diagnosis of boiler plant by computer image processing and neural network technology","display_name":"Thermal energy diagnosis of boiler plant by computer image processing and neural network technology","publication_year":2020,"publication_date":"2020-01-01","ids":{"openalex":"https://openalex.org/W3013045010","doi":"https://doi.org/10.2298/tsci191218128y","mag":"3013045010"},"language":"en","primary_location":{"id":"doi:10.2298/tsci191218128y","doi":"https://doi.org/10.2298/tsci191218128y","is_oa":true,"landing_page_url":"https://doi.org/10.2298/tsci191218128y","pdf_url":"http://www.doiserbia.nb.rs/ft.aspx?id=0354-98362000128Y","source":{"id":"https://openalex.org/S177423656","display_name":"Thermal Science","issn_l":"0354-9836","issn":["0354-9836","2334-7163"],"is_oa":true,"is_in_doaj":false,"is_core":true,"listed_in":["cwts-core","dongbi-c","jufo-1","ki-jl-1","norway-1","poland-40","russia-white-list-3"],"host_organization":"https://openalex.org/P4310322021","host_organization_name":"Vin\u010da Institute of Nuclear Sciences","host_organization_lineage":["https://openalex.org/P4310322021"],"host_organization_lineage_names":["Vin\u010da Institute of Nuclear Sciences"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Thermal Science","raw_type":"journal-article"},"volume":null,"type":"article","is_traditional":true,"indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"http://www.doiserbia.nb.rs/ft.aspx?id=0354-98362000128Y","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5032554136","display_name":"Guoli Yu","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I4405279598","display_name":"Cangzhou Vocational and Technical College","ror":"https://ror.org/01qm8tb49","country_code":"CN","type":"education","lineage":["https://openalex.org/I4405279598"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Guoli Yu","raw_affiliation_strings":["Cangzhou Technical College, Cangzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Cangzhou Technical College, Cangzhou, China","institution_ids":["https://openalex.org/I4405279598"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5010581835","display_name":"Jinge Sang","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I4405279598","display_name":"Cangzhou Vocational and Technical College","ror":"https://ror.org/01qm8tb49","country_code":"CN","type":"education","lineage":["https://openalex.org/I4405279598"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jinge Sang","raw_affiliation_strings":["Cangzhou Technical College, Cangzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Cangzhou Technical College, Cangzhou, China","institution_ids":["https://openalex.org/I4405279598"]}]},{"author_position":"last","author":{"id":null,"display_name":"Yafei Sun","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I4405279598","display_name":"Cangzhou Vocational and Technical College","ror":"https://ror.org/01qm8tb49","country_code":"CN","type":"education","lineage":["https://openalex.org/I4405279598"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yafei Sun","raw_affiliation_strings":["Cangzhou Technical College, Cangzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Cangzhou Technical College, Cangzhou, China","institution_ids":["https://openalex.org/I4405279598"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I4405279598"],"apc_list":{"value":150,"currency":"EUR","value_usd":161},"apc_paid":{"value":150,"currency":"EUR","value_usd":161},"fwci":0.4191,"has_fulltext":true,"cited_by_count":11,"citation_normalized_percentile":{"value":0.552696,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":87,"max":97},"biblio":{"volume":"24","issue":"5 Part B","first_page":"3367","last_page":"3374"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10220","display_name":"Machine Fault Diagnosis Techniques","score":0.510699987411499,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems 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/T10220","display_name":"Machine Fault Diagnosis Techniques","score":0.510699987411499,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems 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/T11856","display_name":"Thermography and Photoacoustic Techniques","score":0.21289999783039093,"subfield":{"id":"https://openalex.org/subfields/2211","display_name":"Mechanics of Materials"},"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/T10876","display_name":"Fault Detection and Control Systems","score":0.14180000126361847,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems 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/infrared-thermography","display_name":"infrared thermography","score":0.9110000133514404},{"id":"https://openalex.org/keywords/convolutional-neural-networks","display_name":"convolutional neural networks","score":0.984000027179718},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"support vector machine","score":0.996999979019165},{"id":"https://openalex.org/keywords/genetic-algorithm-parameter-optimization","display_name":"genetic algorithm parameter optimization","score":0.8970000147819519},{"id":"https://openalex.org/keywords/grey-forecasting-model","display_name":"grey prediction model","score":0.9959999918937683},{"id":"https://openalex.org/keywords/image-processing","display_name":"image processing","score":0.6169999837875366},{"id":"https://openalex.org/keywords/temperature-monitoring","display_name":"temperature monitoring","score":0.35100001096725464}],"concepts":[{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.6964671611785889},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.6478959321975708},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6420415639877319},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6182059049606323},{"id":"https://openalex.org/C2780013297","wikidata":"https://www.wikidata.org/wiki/Q19596153","display_name":"Boiler (water heating)","level":2,"score":0.5287917256355286},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5077091455459595},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4617782533168793},{"id":"https://openalex.org/C139945424","wikidata":"https://www.wikidata.org/wiki/Q1940696","display_name":"Mean squared error","level":2,"score":0.4547502398490906},{"id":"https://openalex.org/C2780092901","wikidata":"https://www.wikidata.org/wiki/Q3433612","display_name":"Correlation coefficient","level":2,"score":0.44159775972366333},{"id":"https://openalex.org/C120793396","wikidata":"https://www.wikidata.org/wiki/Q173350","display_name":"Printed circuit board","level":2,"score":0.43801552057266235},{"id":"https://openalex.org/C175551986","wikidata":"https://www.wikidata.org/wiki/Q47089","display_name":"Fault (geology)","level":2,"score":0.4199534058570862},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.35099685192108154},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.21092179417610168},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.1782282590866089},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.13315358757972717},{"id":"https://openalex.org/C548081761","wikidata":"https://www.wikidata.org/wiki/Q180388","display_name":"Waste management","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.0},{"id":"https://openalex.org/C165205528","wikidata":"https://www.wikidata.org/wiki/Q83371","display_name":"Seismology","level":1,"score":0.0},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.2298/tsci191218128y","doi":"https://doi.org/10.2298/tsci191218128y","is_oa":true,"landing_page_url":"https://doi.org/10.2298/tsci191218128y","pdf_url":"http://www.doiserbia.nb.rs/ft.aspx?id=0354-98362000128Y","source":{"id":"https://openalex.org/S177423656","display_name":"Thermal Science","issn_l":"0354-9836","issn":["0354-9836","2334-7163"],"is_oa":true,"is_in_doaj":false,"is_core":true,"listed_in":["cwts-core","dongbi-c","jufo-1","ki-jl-1","norway-1","poland-40","russia-white-list-3"],"host_organization":"https://openalex.org/P4310322021","host_organization_name":"Vin\u010da Institute of Nuclear Sciences","host_organization_lineage":["https://openalex.org/P4310322021"],"host_organization_lineage_names":["Vin\u010da Institute of Nuclear Sciences"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Thermal Science","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:5e52622e00c348b3ae29176938c1efe6","doi":null,"is_oa":false,"landing_page_url":"https://doaj.org/article/5e52622e00c348b3ae29176938c1efe6","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,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Thermal Science, Vol 24, Iss 5 Part B, Pp 3367-3374 (2020)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.2298/tsci191218128y","doi":"https://doi.org/10.2298/tsci191218128y","is_oa":true,"landing_page_url":"https://doi.org/10.2298/tsci191218128y","pdf_url":"http://www.doiserbia.nb.rs/ft.aspx?id=0354-98362000128Y","source":{"id":"https://openalex.org/S177423656","display_name":"Thermal Science","issn_l":"0354-9836","issn":["0354-9836","2334-7163"],"is_oa":true,"is_in_doaj":false,"is_core":true,"listed_in":["cwts-core","dongbi-c","jufo-1","ki-jl-1","norway-1","poland-40","russia-white-list-3"],"host_organization":"https://openalex.org/P4310322021","host_organization_name":"Vin\u010da Institute of Nuclear Sciences","host_organization_lineage":["https://openalex.org/P4310322021"],"host_organization_lineage_names":["Vin\u010da Institute of Nuclear Sciences"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Thermal Science","raw_type":"journal-article"},"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3013045010.pdf","grobid_xml":"https://content.openalex.org/works/W3013045010.grobid-xml"},"referenced_works_count":20,"referenced_works":["https://openalex.org/W1959733216","https://openalex.org/W2262538465","https://openalex.org/W2530283512","https://openalex.org/W2538797481","https://openalex.org/W2555882221","https://openalex.org/W2598642395","https://openalex.org/W2610770679","https://openalex.org/W2611953050","https://openalex.org/W2752031630","https://openalex.org/W2756672180","https://openalex.org/W2760341224","https://openalex.org/W2781110478","https://openalex.org/W2944903969","https://openalex.org/W6600553734","https://openalex.org/W6600751047","https://openalex.org/W6602610147","https://openalex.org/W6604285789","https://openalex.org/W6604305791","https://openalex.org/W6604972855","https://openalex.org/W6776670870"],"related_works":["https://openalex.org/W3010963936","https://openalex.org/W4391640165","https://openalex.org/W4309216594","https://openalex.org/W2141127622","https://openalex.org/W2367613980","https://openalex.org/W4407477161","https://openalex.org/W3007798320","https://openalex.org/W2534880760","https://openalex.org/W2164239412","https://openalex.org/W4412183645"],"abstract_inverted_index":{"The":[0,173],"paper":[1],"aims":[2],"to":[3,69,141],"study":[4],"the":[5,20,32,44,50,55,59,63,71,75,78,83,89,96,102,106,112,117,123,131,143,148,152,159,163,177,180,190,200,205,224,243,251],"identification":[6],"and":[7,30,39,95,145,189,242],"diagnosis":[8,109,156,210,233],"of":[9,13,17,22,34,46,77,85,111,116,158,162,179,202,207,226],"infrared":[10,26,153],"thermal":[11,27,47,107,154,208,268],"fault":[12,28,108,155,209,232,269],"airborne":[14,51],"circuit":[15,52,79,114,160],"board":[16,53,115,161],"equipment,":[18],"expand":[19],"application":[21],"intelligent":[23,135],"algorithm":[24,138],"in":[25,43,54,93],"diagnosis,":[29],"promote":[31],"development":[33],"computer":[35],"image":[36],"processing":[37],"technology":[38,42],"neural":[40,87,125],"network":[41,126],"field":[45],"diagnosis.":[48,270],"Taking":[49],"boiler":[56,118,168],"plant":[57,119,169],"as":[58,101],"research":[60],"object,":[61],"first,":[62],"sequential":[64],"analysis":[65],"method":[66,110],"was":[67,91,99,139,171,185,194,217,234,240,246],"selected":[68],"collect":[70],"temperature":[72],"changes":[73],"during":[74],"operation":[76],"board.":[80],"Second,":[81],"on":[82,122,130,212],"basis":[84],"convolutional":[86,124],"network,":[88],"program":[90],"written":[92],"Python,":[94],"Relu":[97],"function":[98,104,192],"used":[100,140,266],"activation":[103],"establish":[105],"on-board":[113],"equipment":[120,170],"based":[121,129,211],"model.":[127],"Third,":[128],"support":[132,165,213,227,252],"vector":[133,166,214,228,253],"machine":[134,167,215,229],"algorithm,":[136,204],"genetic":[137,203],"optimize":[142],"parameters,":[144],"combined":[146],"with":[147,220],"grey":[149,221,260],"prediction":[150,222,261],"model,":[151,223,262],"scheme":[157],"multistage":[164],"constructed.":[172],"results":[174],"showed":[175],"that":[176],"accuracy":[178,206,225,258],"model":[181,216,230,255],"after":[182],"6000":[183],"iterations":[184],"stable":[186,195],"between":[187],"0.92-0.96,":[188],"loss":[191],"value":[193,239],"at":[196],"about":[197],"0.17.":[198],"After":[199],"optimization":[201],"optimized.":[218],"Compared":[219],"for":[231,267],"higher,":[235],"mean":[236],"square":[237],"error":[238],"0.0258,":[241],"correlation":[244],"coefficient":[245],"91.55%.":[247],"To":[248],"sum":[249],"up,":[250],"machin":[254],"shows":[256],"higher":[257],"than":[259],"which":[263],"can":[264],"be":[265]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":1}],"updated_date":"2026-09-09T07:26:56.047234","created_date":"2020-04-03T00:00:00"}
