{"id":"https://openalex.org/W2810047517","doi":"https://doi.org/10.1109/fskd.2017.8393030","title":"Infrared image change detection of substation equipment in power system using random forest","display_name":"Infrared image change detection of substation equipment in power system using random forest","publication_year":2017,"publication_date":"2017-07-01","ids":{"openalex":"https://openalex.org/W2810047517","doi":"https://doi.org/10.1109/fskd.2017.8393030","mag":"2810047517"},"language":"en","primary_location":{"id":"doi:10.1109/fskd.2017.8393030","is_oa":false,"landing_page_url":"https://doi.org/10.1109/fskd.2017.8393030","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 13th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery (ICNC-FSKD)","raw_type":"proceedings-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/A5101850450","display_name":"Hua Yang","orcid":"https://orcid.org/0009-0000-1050-6177"},"institutions":[{"id":"https://openalex.org/I4210145500","display_name":"Guizhou Electric Power Design and Research Institute","ror":"https://ror.org/055f13495","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210145500"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Hua Yang","raw_affiliation_strings":["Tongren Electric Power Supply Bureau of Guizhou Power Grid Co., Ltd., Tongren, China"],"affiliations":[{"raw_affiliation_string":"Tongren Electric Power Supply Bureau of Guizhou Power Grid Co., Ltd., Tongren, China","institution_ids":["https://openalex.org/I4210145500"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5070156629","display_name":"Jipu Gao","orcid":"https://orcid.org/0000-0001-5272-296X"},"institutions":[{"id":"https://openalex.org/I4210145500","display_name":"Guizhou Electric Power Design and Research Institute","ror":"https://ror.org/055f13495","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210145500"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jipu Gao","raw_affiliation_strings":["Electric Power Research Institute of Guizhou Power Grid Co., Ltd., Guiyang, China"],"affiliations":[{"raw_affiliation_string":"Electric Power Research Institute of Guizhou Power Grid Co., Ltd., Guiyang, China","institution_ids":["https://openalex.org/I4210145500"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5009289126","display_name":"Changbao Xu","orcid":"https://orcid.org/0000-0003-1128-0063"},"institutions":[{"id":"https://openalex.org/I4210145500","display_name":"Guizhou Electric Power Design and Research Institute","ror":"https://ror.org/055f13495","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210145500"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Changbao Xu","raw_affiliation_strings":["Electric Power Research Institute of Guizhou Power Grid Co., Ltd., Guiyang, China"],"affiliations":[{"raw_affiliation_string":"Electric Power Research Institute of Guizhou Power Grid Co., Ltd., Guiyang, China","institution_ids":["https://openalex.org/I4210145500"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5080957757","display_name":"Zheng Long","orcid":null},"institutions":[{"id":"https://openalex.org/I4210145500","display_name":"Guizhou Electric Power Design and Research Institute","ror":"https://ror.org/055f13495","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210145500"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zheng Long","raw_affiliation_strings":["Tongren Electric Power Supply Bureau of Guizhou Power Grid Co., Ltd., Tongren, China"],"affiliations":[{"raw_affiliation_string":"Tongren Electric Power Supply Bureau of Guizhou Power Grid Co., Ltd., Tongren, China","institution_ids":["https://openalex.org/I4210145500"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5087782671","display_name":"Weigang Feng","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Weigang Feng","raw_affiliation_strings":["Wuhan Zhongyuan Huadian Science & Technology Co., Ltd., Wuhan, China"],"affiliations":[{"raw_affiliation_string":"Wuhan Zhongyuan Huadian Science & Technology Co., Ltd., Wuhan, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5089973350","display_name":"Shaohua Xiong","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Shaohua Xiong","raw_affiliation_strings":["Wuhan Zhongyuan Huadian Science & Technology Co., Ltd., Wuhan, China"],"affiliations":[{"raw_affiliation_string":"Wuhan Zhongyuan Huadian Science & Technology Co., Ltd., Wuhan, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5022247937","display_name":"Shuaiwei Liu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Shuaiwei Liu","raw_affiliation_strings":["Wuhan Zhongyuan Huadian Science & Technology Co., Ltd., Wuhan, China"],"affiliations":[{"raw_affiliation_string":"Wuhan Zhongyuan Huadian Science & Technology Co., Ltd., Wuhan, China","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5077232321","display_name":"Shan Tan","orcid":"https://orcid.org/0000-0001-9350-5128"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Shan Tan","raw_affiliation_strings":["Wuhan Zhongyuan Huadian Science & Technology Co., Ltd., Wuhan, China"],"affiliations":[{"raw_affiliation_string":"Wuhan Zhongyuan Huadian Science & Technology Co., Ltd., Wuhan, China","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":8,"corresponding_author_ids":["https://openalex.org/A5101850450"],"corresponding_institution_ids":["https://openalex.org/I4210145500"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.31386225,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":96},"biblio":{"volume":"8334","issue":null,"first_page":"1745","last_page":"1751"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.9990000128746033,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"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/T10689","display_name":"Remote-Sensing Image Classification","score":0.9990000128746033,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"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/T13890","display_name":"Remote Sensing and Land Use","score":0.9954000115394592,"subfield":{"id":"https://openalex.org/subfields/1902","display_name":"Atmospheric Science"},"field":{"id":"https://openalex.org/fields/19","display_name":"Earth and Planetary Sciences"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10640","display_name":"Spectroscopy and Chemometric Analyses","score":0.9794999957084656,"subfield":{"id":"https://openalex.org/subfields/1602","display_name":"Analytical Chemistry"},"field":{"id":"https://openalex.org/fields/16","display_name":"Chemistry"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/change-detection","display_name":"Change detection","score":0.8362473845481873},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7652274370193481},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6834283471107483},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.6369189620018005},{"id":"https://openalex.org/keywords/histogram","display_name":"Histogram","score":0.5929257869720459},{"id":"https://openalex.org/keywords/random-forest","display_name":"Random forest","score":0.5688226222991943},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5642560720443726},{"id":"https://openalex.org/keywords/grayscale","display_name":"Grayscale","score":0.5491204857826233},{"id":"https://openalex.org/keywords/histogram-of-oriented-gradients","display_name":"Histogram of oriented gradients","score":0.544154942035675},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5309134721755981},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.5130907297134399},{"id":"https://openalex.org/keywords/rgb-color-model","display_name":"RGB color model","score":0.4513430595397949},{"id":"https://openalex.org/keywords/principal-component-analysis","display_name":"Principal component analysis","score":0.44380900263786316},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.29724419116973877},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.18796738982200623}],"concepts":[{"id":"https://openalex.org/C203595873","wikidata":"https://www.wikidata.org/wiki/Q25389927","display_name":"Change detection","level":2,"score":0.8362473845481873},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7652274370193481},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6834283471107483},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.6369189620018005},{"id":"https://openalex.org/C53533937","wikidata":"https://www.wikidata.org/wiki/Q185020","display_name":"Histogram","level":3,"score":0.5929257869720459},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.5688226222991943},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5642560720443726},{"id":"https://openalex.org/C78201319","wikidata":"https://www.wikidata.org/wiki/Q685727","display_name":"Grayscale","level":3,"score":0.5491204857826233},{"id":"https://openalex.org/C17426736","wikidata":"https://www.wikidata.org/wiki/Q419918","display_name":"Histogram of oriented gradients","level":4,"score":0.544154942035675},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5309134721755981},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.5130907297134399},{"id":"https://openalex.org/C82990744","wikidata":"https://www.wikidata.org/wiki/Q166194","display_name":"RGB color model","level":2,"score":0.4513430595397949},{"id":"https://openalex.org/C27438332","wikidata":"https://www.wikidata.org/wiki/Q2873","display_name":"Principal component analysis","level":2,"score":0.44380900263786316},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.29724419116973877},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.18796738982200623},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/fskd.2017.8393030","is_oa":false,"landing_page_url":"https://doi.org/10.1109/fskd.2017.8393030","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 13th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery (ICNC-FSKD)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.550000011920929,"id":"https://metadata.un.org/sdg/15","display_name":"Life in Land"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":19,"referenced_works":["https://openalex.org/W1663751385","https://openalex.org/W1974200129","https://openalex.org/W1984729635","https://openalex.org/W1984819514","https://openalex.org/W1989259404","https://openalex.org/W2027781877","https://openalex.org/W2039051707","https://openalex.org/W2113242816","https://openalex.org/W2117085409","https://openalex.org/W2117438495","https://openalex.org/W2131876490","https://openalex.org/W2132222679","https://openalex.org/W2160544350","https://openalex.org/W2163352848","https://openalex.org/W2163808566","https://openalex.org/W2165577558","https://openalex.org/W2172196609","https://openalex.org/W2911964244","https://openalex.org/W3152294918"],"related_works":["https://openalex.org/W1555939286","https://openalex.org/W3153082147","https://openalex.org/W2968833425","https://openalex.org/W2899689856","https://openalex.org/W2071599417","https://openalex.org/W2048716406","https://openalex.org/W1870444468","https://openalex.org/W2183235103","https://openalex.org/W1964725559","https://openalex.org/W3109748140"],"abstract_inverted_index":{"Early":[0],"detection":[1,15,60,147,152,164,173,190,195],"of":[2,16,19,45,116,121,133,141],"equipment":[3,21,48],"faults":[4],"plays":[5],"a":[6,34,46,66,168],"crucial":[7],"role":[8],"in":[9,42,49,149],"power":[10,50],"system,":[11],"and":[12,65,106,113,162,206],"automatic":[13],"change":[14,41,59,80,91,151,194],"working":[17],"status":[18],"an":[20,23],"is":[22],"efficient":[24],"tool":[25],"for":[26,78,90,213],"this":[27,30],"purpose.":[28,215],"In":[29,154],"study,":[31],"we":[32,95,166],"proposed":[33,221],"novel":[35],"method":[36],"to":[37,129,138,156,187],"automatically":[38],"detect":[39],"temperature":[40],"local":[43],"region":[44],"substation":[47,123],"system":[51],"using":[52],"bi-temporal":[53,118],"infrared":[54,119],"images.":[55],"We":[56],"considered":[57],"the":[58,110,117,122,131,139,150,172,189,220],"as":[61,178],"two-class":[62],"classification":[63],"problem,":[64],"supervised":[67],"machine":[68],"learning":[69],"algorithm":[70,222],"-":[71,75],"Random":[72],"Forest":[73],"(RF)":[74],"was":[76,127],"used":[77,128,186],"forecasting":[79],"trend.":[81],"Various":[82],"features":[83,94],"were":[84,185,211],"extracted":[85,96,135],"from":[86,109],"two":[87],"temporal":[88],"images":[89,112,115,120],"detection.":[92],"The":[93],"include":[97],"gray-level,":[98],"weighted":[99],"intensity":[100],"mean,":[101],"RGB,":[102],"LBP,":[103],"gray-level":[104],"histogram,":[105],"texture":[107],"originating":[108],"grayscale":[111],"color":[114],"equipment.":[124],"Cross":[125],"validation":[126],"evaluate":[130,188],"robustness":[132],"these":[134,158,225],"features.":[136],"Due":[137],"existence":[140],"environmental":[142],"noise,":[143],"there":[144],"are":[145],"isolated":[146,159],"points":[148,161],"results.":[153,174],"order":[155],"remove":[157],"noise":[160],"improve":[163],"accuracy,":[165],"performed":[167],"morphological":[169],"filtering":[170],"on":[171],"Evaluation":[175],"indexes":[176],"such":[177],"Dice":[179],"Similarity":[180],"Index":[181],"(DSI),":[182],"kappa":[183],"coefficient":[184],"performance.":[191],"Four":[192],"classical":[193,226],"methods":[196],"i.e.":[197],"Image":[198,200],"Differencing,":[199],"Ratioing,":[201],"Change":[202],"vector":[203],"analysis":[204],"(CVA)":[205],"Principal":[207],"Component":[208],"Analysis":[209],"(PCA)":[210],"tested":[212],"comparison":[214],"Experimental":[216],"results":[217],"demonstrated":[218],"that":[219],"outperformed":[223],"significantly":[224],"methods.":[227]},"counts_by_year":[{"year":2023,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
