{"id":"https://openalex.org/W4402263318","doi":"https://doi.org/10.1109/igarss53475.2024.10641958","title":"An Adaptive Noise Reduction Method for Microseismic Data Using Parameter-Free Fuzzy Clustering","display_name":"An Adaptive Noise Reduction Method for Microseismic Data Using Parameter-Free Fuzzy Clustering","publication_year":2024,"publication_date":"2024-07-07","ids":{"openalex":"https://openalex.org/W4402263318","doi":"https://doi.org/10.1109/igarss53475.2024.10641958"},"language":"en","primary_location":{"id":"doi:10.1109/igarss53475.2024.10641958","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/igarss53475.2024.10641958","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IGARSS 2024 - 2024 IEEE International Geoscience and Remote Sensing Symposium","raw_type":"proceedings-article"},"type":"conference-paper","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/A5107865388","display_name":"Yuan Zhang","orcid":"https://orcid.org/0000-0002-7970-6211"},"institutions":[{"id":"https://openalex.org/I3923682","display_name":"Soochow University","ror":"https://ror.org/05t8y2r12","country_code":"CN","type":"education","lineage":["https://openalex.org/I3923682"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuan Zhang","raw_affiliation_strings":["Soochow University,Suzhou,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Soochow University,Suzhou,China","institution_ids":["https://openalex.org/I3923682"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5113749340","display_name":"Jie Wang","orcid":"https://orcid.org/0009-0004-9378-0065"},"institutions":[{"id":"https://openalex.org/I3923682","display_name":"Soochow University","ror":"https://ror.org/05t8y2r12","country_code":"CN","type":"education","lineage":["https://openalex.org/I3923682"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jie Wang","raw_affiliation_strings":["Soochow University,Suzhou,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Soochow University,Suzhou,China","institution_ids":["https://openalex.org/I3923682"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5000861569","display_name":"Kun Zhu","orcid":"https://orcid.org/0000-0001-6784-5583"},"institutions":[{"id":"https://openalex.org/I3923682","display_name":"Soochow University","ror":"https://ror.org/05t8y2r12","country_code":"CN","type":"education","lineage":["https://openalex.org/I3923682"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Kun Zhu","raw_affiliation_strings":["Soochow University,Suzhou,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Soochow University,Suzhou,China","institution_ids":["https://openalex.org/I3923682"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5024075035","display_name":"Zhiqiang Lan","orcid":"https://orcid.org/0000-0002-0345-5807"},"institutions":[{"id":"https://openalex.org/I3923682","display_name":"Soochow University","ror":"https://ror.org/05t8y2r12","country_code":"CN","type":"education","lineage":["https://openalex.org/I3923682"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhiqiang Lan","raw_affiliation_strings":["Soochow University,Suzhou,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Soochow University,Suzhou,China","institution_ids":["https://openalex.org/I3923682"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100357767","display_name":"\u0422\u0430\u043e \u0427\u0435\u043d","orcid":"https://orcid.org/0000-0002-8031-7117"},"institutions":[{"id":"https://openalex.org/I3923682","display_name":"Soochow University","ror":"https://ror.org/05t8y2r12","country_code":"CN","type":"education","lineage":["https://openalex.org/I3923682"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tao Chen","raw_affiliation_strings":["Soochow University,Suzhou,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Soochow University,Suzhou,China","institution_ids":["https://openalex.org/I3923682"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I3923682"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"10281","last_page":"10284"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9994000196456909,"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"}},"topics":[{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9994000196456909,"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"}},{"id":"https://openalex.org/T10688","display_name":"Image and Signal Denoising Methods","score":0.9958000183105469,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T13018","display_name":"Seismology and Earthquake Studies","score":0.9948999881744385,"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/microseism","display_name":"Microseism","score":0.7138445377349854},{"id":"https://openalex.org/keywords/noise-reduction","display_name":"Noise reduction","score":0.6901962161064148},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6650292873382568},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.6362656950950623},{"id":"https://openalex.org/keywords/reduction","display_name":"Reduction (mathematics)","score":0.6243183612823486},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.5501174330711365},{"id":"https://openalex.org/keywords/fuzzy-logic","display_name":"Fuzzy logic","score":0.49831080436706543},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.457466185092926},{"id":"https://openalex.org/keywords/fuzzy-clustering","display_name":"Fuzzy clustering","score":0.4260125756263733},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.33840543031692505},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3264698088169098},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.23417705297470093},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.1325531303882599},{"id":"https://openalex.org/keywords/seismology","display_name":"Seismology","score":0.09439685940742493}],"concepts":[{"id":"https://openalex.org/C7266685","wikidata":"https://www.wikidata.org/wiki/Q1303250","display_name":"Microseism","level":2,"score":0.7138445377349854},{"id":"https://openalex.org/C163294075","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Noise reduction","level":2,"score":0.6901962161064148},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6650292873382568},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.6362656950950623},{"id":"https://openalex.org/C111335779","wikidata":"https://www.wikidata.org/wiki/Q3454686","display_name":"Reduction (mathematics)","level":2,"score":0.6243183612823486},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.5501174330711365},{"id":"https://openalex.org/C58166","wikidata":"https://www.wikidata.org/wiki/Q224821","display_name":"Fuzzy logic","level":2,"score":0.49831080436706543},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.457466185092926},{"id":"https://openalex.org/C17212007","wikidata":"https://www.wikidata.org/wiki/Q5511111","display_name":"Fuzzy clustering","level":3,"score":0.4260125756263733},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.33840543031692505},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3264698088169098},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.23417705297470093},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.1325531303882599},{"id":"https://openalex.org/C165205528","wikidata":"https://www.wikidata.org/wiki/Q83371","display_name":"Seismology","level":1,"score":0.09439685940742493},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/igarss53475.2024.10641958","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/igarss53475.2024.10641958","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IGARSS 2024 - 2024 IEEE International Geoscience and Remote Sensing Symposium","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Affordable and clean energy","score":0.7200000286102295,"id":"https://metadata.un.org/sdg/7"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":8,"referenced_works":["https://openalex.org/W1694307164","https://openalex.org/W2038752786","https://openalex.org/W2243069332","https://openalex.org/W2533471832","https://openalex.org/W2963631813","https://openalex.org/W3042502461","https://openalex.org/W4244917097","https://openalex.org/W4285132771"],"related_works":["https://openalex.org/W2945382830","https://openalex.org/W4224807364","https://openalex.org/W2596632494","https://openalex.org/W2535986621","https://openalex.org/W1980197432","https://openalex.org/W2382432689","https://openalex.org/W2000612978","https://openalex.org/W4388110928","https://openalex.org/W1483228865","https://openalex.org/W4292434959"],"abstract_inverted_index":{"In":[0],"microseismic":[1],"monitoring,":[2],"the":[3,15,31,39,47,94],"collected":[4],"data":[5],"is":[6,28],"distorted":[7],"by":[8,79],"noise,":[9],"bringing":[10],"difficulties":[11],"and":[12,22,84,106,109,114],"challenges":[13],"to":[14,46],"subsequent":[16],"processing":[17],"of":[18,30,41,51],"event":[19],"identification,":[20],"localization,":[21],"others.":[23],"Wavelet":[24],"packet":[25],"transform":[26],"(WPT)":[27],"one":[29],"most":[32],"commonly":[33],"used":[34],"noise":[35,72],"reduction":[36,73],"methods,":[37],"but":[38],"usage":[40],"threshold":[42],"can":[43],"significantly":[44],"lead":[45],"informative":[48],"content":[49],"loss":[50],"target":[52],"signals,":[53],"especially":[54],"at":[55,103,111],"high":[56,112],"frequency":[57],"or":[58],"low":[59,104,115],"signal-to-noise":[60],"ratio":[61],"(SNR).":[62],"To":[63],"address":[64],"above":[65],"issues,":[66],"this":[67],"paper":[68],"proposes":[69],"a":[70],"new":[71],"method":[74,96],"based":[75],"on":[76],"WPT,":[77],"supported":[78],"Fuzzy":[80],"C-Means":[81],"clustering":[82],"(FCM)":[83],"k-nearest":[85],"neighbors":[86],"(KNN)":[87],"algorithms.":[88],"The":[89],"experiment":[90],"results":[91],"show":[92],"that":[93],"proposed":[95],"has":[97],"less":[98],"performance":[99],"fluctuation":[100],"than":[101],"WPT":[102,108],"frequencies,":[105],"outperforms":[107],"FCM":[110],"frequencies":[113],"SNR.":[116]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}