{"id":"https://openalex.org/W3033553620","doi":"https://doi.org/10.1145/3385209.3385211","title":"Seismic Data Analysis Regression Model on Reactor Pressure Vessel using Fast Fourier Transform and Machine Learning","display_name":"Seismic Data Analysis Regression Model on Reactor Pressure Vessel using Fast Fourier Transform and Machine Learning","publication_year":2020,"publication_date":"2020-02-19","ids":{"openalex":"https://openalex.org/W3033553620","doi":"https://doi.org/10.1145/3385209.3385211","mag":"3033553620"},"language":"en","primary_location":{"id":"doi:10.1145/3385209.3385211","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3385209.3385211","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2020 5th International Conference on Intelligent Information Technology","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/A5029764225","display_name":"Youjeong Park","orcid":"https://orcid.org/0000-0001-8989-3818"},"institutions":[{"id":"https://openalex.org/I848706","display_name":"Sungkyunkwan University","ror":"https://ror.org/04q78tk20","country_code":"KR","type":"education","lineage":["https://openalex.org/I848706"]}],"countries":["KR"],"is_corresponding":true,"raw_author_name":"Youjeong Park","raw_affiliation_strings":["Dept. of AI, Sungkyunkwan University, Suwon, Republic of Korea"],"affiliations":[{"raw_affiliation_string":"Dept. of AI, Sungkyunkwan University, Suwon, Republic of Korea","institution_ids":["https://openalex.org/I848706"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5049607975","display_name":"Sungho Yoon","orcid":"https://orcid.org/0000-0002-5801-9279"},"institutions":[{"id":"https://openalex.org/I848706","display_name":"Sungkyunkwan University","ror":"https://ror.org/04q78tk20","country_code":"KR","type":"education","lineage":["https://openalex.org/I848706"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Sung-Ho Yoon","raw_affiliation_strings":["School of Mechanical Engineering, Sungkyunkwan University, Suwon, Republic of Korea"],"affiliations":[{"raw_affiliation_string":"School of Mechanical Engineering, Sungkyunkwan University, Suwon, Republic of Korea","institution_ids":["https://openalex.org/I848706"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5112538414","display_name":"Jun Hyeok Choi","orcid":null},"institutions":[{"id":"https://openalex.org/I848706","display_name":"Sungkyunkwan University","ror":"https://ror.org/04q78tk20","country_code":"KR","type":"education","lineage":["https://openalex.org/I848706"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Jun Hyeok Choi","raw_affiliation_strings":["School of Mechanical Engineering, Sungkyunkwan University, Suwon, Republic of Korea"],"affiliations":[{"raw_affiliation_string":"School of Mechanical Engineering, Sungkyunkwan University, Suwon, Republic of Korea","institution_ids":["https://openalex.org/I848706"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5016794944","display_name":"Moon Ki Kim","orcid":"https://orcid.org/0000-0003-0819-5909"},"institutions":[{"id":"https://openalex.org/I848706","display_name":"Sungkyunkwan University","ror":"https://ror.org/04q78tk20","country_code":"KR","type":"education","lineage":["https://openalex.org/I848706"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Moon Ki Kim","raw_affiliation_strings":["School of Mechanical Engineering, Sungkyunkwan University, Suwon, Republic of Korea"],"affiliations":[{"raw_affiliation_string":"School of Mechanical Engineering, Sungkyunkwan University, Suwon, Republic of Korea","institution_ids":["https://openalex.org/I848706"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5109887389","display_name":"Jae\u2010Boong Choi","orcid":null},"institutions":[{"id":"https://openalex.org/I848706","display_name":"Sungkyunkwan University","ror":"https://ror.org/04q78tk20","country_code":"KR","type":"education","lineage":["https://openalex.org/I848706"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Jae-Boong Choi","raw_affiliation_strings":["School of Mechanical Engineering, Sungkyunkwan University, Suwon, Republic of Korea"],"affiliations":[{"raw_affiliation_string":"School of Mechanical Engineering, Sungkyunkwan University, Suwon, Republic of Korea","institution_ids":["https://openalex.org/I848706"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5029764225"],"corresponding_institution_ids":["https://openalex.org/I848706"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.05718559,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"16","last_page":"20"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10876","display_name":"Fault Detection and Control Systems","score":0.9958000183105469,"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/T10876","display_name":"Fault Detection and Control Systems","score":0.9958000183105469,"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/T10534","display_name":"Structural Health Monitoring Techniques","score":0.9704999923706055,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9689000248908997,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/fourier-transform","display_name":"Fourier transform","score":0.6605778932571411},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5946801900863647},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.5856659412384033},{"id":"https://openalex.org/keywords/regression-analysis","display_name":"Regression analysis","score":0.5769281983375549},{"id":"https://openalex.org/keywords/regression","display_name":"Regression","score":0.5603832602500916},{"id":"https://openalex.org/keywords/waveform","display_name":"Waveform","score":0.5468421578407288},{"id":"https://openalex.org/keywords/partial-least-squares-regression","display_name":"Partial least squares regression","score":0.4812288284301758},{"id":"https://openalex.org/keywords/short-time-fourier-transform","display_name":"Short-time Fourier transform","score":0.4499557316303253},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.44985589385032654},{"id":"https://openalex.org/keywords/random-forest","display_name":"Random forest","score":0.42283767461776733},{"id":"https://openalex.org/keywords/gradient-boosting","display_name":"Gradient boosting","score":0.422650545835495},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.41595563292503357},{"id":"https://openalex.org/keywords/intensity","display_name":"Intensity (physics)","score":0.41230231523513794},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.38902711868286133},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3595835268497467},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.33941781520843506},{"id":"https://openalex.org/keywords/fourier-analysis","display_name":"Fourier analysis","score":0.24389806389808655},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.2240496575832367},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.202980637550354}],"concepts":[{"id":"https://openalex.org/C102519508","wikidata":"https://www.wikidata.org/wiki/Q6520159","display_name":"Fourier transform","level":2,"score":0.6605778932571411},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5946801900863647},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.5856659412384033},{"id":"https://openalex.org/C152877465","wikidata":"https://www.wikidata.org/wiki/Q208042","display_name":"Regression analysis","level":2,"score":0.5769281983375549},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.5603832602500916},{"id":"https://openalex.org/C197424946","wikidata":"https://www.wikidata.org/wiki/Q1165717","display_name":"Waveform","level":3,"score":0.5468421578407288},{"id":"https://openalex.org/C22354355","wikidata":"https://www.wikidata.org/wiki/Q422009","display_name":"Partial least squares regression","level":2,"score":0.4812288284301758},{"id":"https://openalex.org/C166386157","wikidata":"https://www.wikidata.org/wiki/Q1477735","display_name":"Short-time Fourier transform","level":4,"score":0.4499557316303253},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.44985589385032654},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.42283767461776733},{"id":"https://openalex.org/C70153297","wikidata":"https://www.wikidata.org/wiki/Q5591907","display_name":"Gradient boosting","level":3,"score":0.422650545835495},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.41595563292503357},{"id":"https://openalex.org/C93038891","wikidata":"https://www.wikidata.org/wiki/Q1061524","display_name":"Intensity (physics)","level":2,"score":0.41230231523513794},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.38902711868286133},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3595835268497467},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.33941781520843506},{"id":"https://openalex.org/C203024314","wikidata":"https://www.wikidata.org/wiki/Q1365258","display_name":"Fourier analysis","level":3,"score":0.24389806389808655},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.2240496575832367},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.202980637550354},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C554190296","wikidata":"https://www.wikidata.org/wiki/Q47528","display_name":"Radar","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3385209.3385211","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3385209.3385211","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2020 5th International Conference on Intelligent Information Technology","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":12,"referenced_works":["https://openalex.org/W1506806321","https://openalex.org/W2033188899","https://openalex.org/W2040895929","https://openalex.org/W2059811068","https://openalex.org/W2070493638","https://openalex.org/W2085454882","https://openalex.org/W2106822551","https://openalex.org/W2115340664","https://openalex.org/W2122483237","https://openalex.org/W2153635508","https://openalex.org/W2159154457","https://openalex.org/W2911964244"],"related_works":["https://openalex.org/W1974895211","https://openalex.org/W2176409448","https://openalex.org/W2129841057","https://openalex.org/W4386690025","https://openalex.org/W3208169454","https://openalex.org/W4322710485","https://openalex.org/W4402664569","https://openalex.org/W4315777889","https://openalex.org/W3201348321","https://openalex.org/W4294691859"],"abstract_inverted_index":{"The":[0],"paper":[1],"presents":[2],"a":[3],"way":[4],"for":[5,48,71,121],"data":[6,10,17,39,49,70,116],"analysis":[7],"of":[8,30],"seismic":[9,37,114],"in":[11,92],"order":[12,93],"to":[13,26,63,94,108],"predict":[14,66],"stress":[15,68,119],"intensity":[16,69,120],"on":[18,98,123],"reactor":[19,32,125],"pressure":[20,33,126],"vessel":[21],"because":[22],"it":[23,105],"is":[24,46,106],"important":[25],"investigate":[27],"the":[28,31,36,67,99,110,113,118,124],"integrity":[29],"vessel.":[34,127],"As":[35],"waveform":[38,115],"are":[40],"time-series":[41],"data,":[42],"fast":[43,55],"Fourier":[44,56],"Transform":[45],"implemented":[47],"processing.":[50],"After":[51],"feature":[52],"extraction":[53],"using":[54],"Transform,":[57],"machine":[58],"learning":[59],"algorithms":[60,91],"were":[61],"used":[62],"analyze":[64],"and":[65,84,88,117],"regression.":[72,100],"We":[73],"applied":[74],"Support":[75],"Vector":[76],"Regression,":[77,80],"Random":[78],"Forest":[79],"K-nearest":[81],"Neighbor":[82],"Regression":[83],"Gradient":[85],"Boosting":[86],"Regressor":[87],"compared":[89],"these":[90],"improve":[95],"good":[96],"accuracy":[97],"This":[101],"research":[102],"shows":[103],"that":[104],"possible":[107],"make":[109],"correlation":[111],"between":[112],"reliability":[122]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
