{"id":"https://openalex.org/W2999065616","doi":"https://doi.org/10.1109/access.2020.2967411","title":"Mahalanobis-Taguchi System for Symbolic Interval Data Based on Kernel Mahalanobis Distance","display_name":"Mahalanobis-Taguchi System for Symbolic Interval Data Based on Kernel Mahalanobis Distance","publication_year":2020,"publication_date":"2020-01-01","ids":{"openalex":"https://openalex.org/W2999065616","doi":"https://doi.org/10.1109/access.2020.2967411","mag":"2999065616"},"language":"en","primary_location":{"id":"doi:10.1109/access.2020.2967411","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2020.2967411","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8948470/08962011.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://ieeexplore.ieee.org/ielx7/6287639/8948470/08962011.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5033234010","display_name":"Zhipeng Chang","orcid":"https://orcid.org/0000-0003-1157-4133"},"institutions":[{"id":"https://openalex.org/I92178344","display_name":"Anhui University of Technology","ror":"https://ror.org/02qdtrq21","country_code":"CN","type":"education","lineage":["https://openalex.org/I92178344"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Zhipeng Chang","raw_affiliation_strings":["School of Business, Anhui University of Technology, Ma\u2019anshan, China","School of Business, Anhui University of Technology, Ma'anshan, China"],"raw_orcid":"https://orcid.org/0000-0003-1157-4133","affiliations":[{"raw_affiliation_string":"School of Business, Anhui University of Technology, Ma\u2019anshan, China","institution_ids":["https://openalex.org/I92178344"]},{"raw_affiliation_string":"School of Business, Anhui University of Technology, Ma'anshan, China","institution_ids":["https://openalex.org/I92178344"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5083450269","display_name":"Wenhe Chen","orcid":"https://orcid.org/0000-0003-2236-7076"},"institutions":[{"id":"https://openalex.org/I92178344","display_name":"Anhui University of Technology","ror":"https://ror.org/02qdtrq21","country_code":"CN","type":"education","lineage":["https://openalex.org/I92178344"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wenhe Chen","raw_affiliation_strings":["School of Business, Anhui University of Technology, Ma\u2019anshan, China","School of Business, Anhui University of Technology, Ma'anshan, China"],"raw_orcid":"https://orcid.org/0000-0003-2236-7076","affiliations":[{"raw_affiliation_string":"School of Business, Anhui University of Technology, Ma\u2019anshan, China","institution_ids":["https://openalex.org/I92178344"]},{"raw_affiliation_string":"School of Business, Anhui University of Technology, Ma'anshan, China","institution_ids":["https://openalex.org/I92178344"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5091054173","display_name":"Yuping Gu","orcid":"https://orcid.org/0000-0002-1728-1748"},"institutions":[{"id":"https://openalex.org/I188935350","display_name":"Anhui University of Finance and Economics","ror":"https://ror.org/0152zzg30","country_code":"CN","type":"education","lineage":["https://openalex.org/I188935350"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuping Gu","raw_affiliation_strings":["School of Management Science and Engineering, Anhui University of Finance and Economics, Bengbu, China"],"raw_orcid":"https://orcid.org/0000-0002-1728-1748","affiliations":[{"raw_affiliation_string":"School of Management Science and Engineering, Anhui University of Finance and Economics, Bengbu, China","institution_ids":["https://openalex.org/I188935350"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5011070279","display_name":"Haoyue Xu","orcid":"https://orcid.org/0000-0002-6757-5437"},"institutions":[{"id":"https://openalex.org/I92178344","display_name":"Anhui University of Technology","ror":"https://ror.org/02qdtrq21","country_code":"CN","type":"education","lineage":["https://openalex.org/I92178344"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Haoyue Xu","raw_affiliation_strings":["School of Business, Anhui University of Technology, Ma\u2019anshan, China","School of Business, Anhui University of Technology, Ma'anshan, China"],"raw_orcid":"https://orcid.org/0000-0002-6757-5437","affiliations":[{"raw_affiliation_string":"School of Business, Anhui University of Technology, Ma\u2019anshan, China","institution_ids":["https://openalex.org/I92178344"]},{"raw_affiliation_string":"School of Business, Anhui University of Technology, Ma'anshan, China","institution_ids":["https://openalex.org/I92178344"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5033234010"],"corresponding_institution_ids":["https://openalex.org/I92178344"],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":1.4879,"has_fulltext":true,"cited_by_count":11,"citation_normalized_percentile":{"value":0.81377378,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":"8","issue":null,"first_page":"20428","last_page":"20438"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10876","display_name":"Fault Detection and Control Systems","score":0.9771999716758728,"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":0.9771999716758728,"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/T11798","display_name":"Optimal Experimental Design Methods","score":0.9750999808311462,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T10320","display_name":"Neural Networks and Applications","score":0.9735000133514404,"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/mahalanobis-distance","display_name":"Mahalanobis distance","score":0.9486383199691772},{"id":"https://openalex.org/keywords/interval","display_name":"Interval (graph theory)","score":0.6007376909255981},{"id":"https://openalex.org/keywords/kernel","display_name":"Kernel (algebra)","score":0.5968760848045349},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5442841053009033},{"id":"https://openalex.org/keywords/symbolic-data-analysis","display_name":"Symbolic data analysis","score":0.5040861368179321},{"id":"https://openalex.org/keywords/dimension","display_name":"Dimension (graph theory)","score":0.501835823059082},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.49616679549217224},{"id":"https://openalex.org/keywords/taguchi-methods","display_name":"Taguchi methods","score":0.4879605174064636},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4785471558570862},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4223676025867462},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3852590322494507},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3590342402458191},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.2915734648704529},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.12307095527648926},{"id":"https://openalex.org/keywords/discrete-mathematics","display_name":"Discrete mathematics","score":0.0666283667087555}],"concepts":[{"id":"https://openalex.org/C1921717","wikidata":"https://www.wikidata.org/wiki/Q1334846","display_name":"Mahalanobis distance","level":2,"score":0.9486383199691772},{"id":"https://openalex.org/C2778067643","wikidata":"https://www.wikidata.org/wiki/Q166507","display_name":"Interval (graph theory)","level":2,"score":0.6007376909255981},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.5968760848045349},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5442841053009033},{"id":"https://openalex.org/C65620979","wikidata":"https://www.wikidata.org/wiki/Q7661176","display_name":"Symbolic data analysis","level":2,"score":0.5040861368179321},{"id":"https://openalex.org/C33676613","wikidata":"https://www.wikidata.org/wiki/Q13415176","display_name":"Dimension (graph theory)","level":2,"score":0.501835823059082},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.49616679549217224},{"id":"https://openalex.org/C83469408","wikidata":"https://www.wikidata.org/wiki/Q2036525","display_name":"Taguchi methods","level":2,"score":0.4879605174064636},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4785471558570862},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4223676025867462},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3852590322494507},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3590342402458191},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2915734648704529},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.12307095527648926},{"id":"https://openalex.org/C118615104","wikidata":"https://www.wikidata.org/wiki/Q121416","display_name":"Discrete mathematics","level":1,"score":0.0666283667087555},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2020.2967411","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2020.2967411","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8948470/08962011.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:74659654cb764d9a8adfbfc4115a5c15","is_oa":true,"landing_page_url":"https://doaj.org/article/74659654cb764d9a8adfbfc4115a5c15","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":"IEEE Access, Vol 8, Pp 20428-20438 (2020)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2020.2967411","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2020.2967411","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8948470/08962011.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G4458541701","display_name":null,"funder_award_id":"71673001","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G864508159","display_name":null,"funder_award_id":"gxyqZD2017040","funder_id":"https://openalex.org/F4320335002","funder_display_name":"Provincial Foundation for Excellent Young Talents of Colleges and Universities of Anhui Province"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320335002","display_name":"Provincial Foundation for Excellent Young Talents of Colleges and Universities of Anhui Province","ror":"https://ror.org/012m7k033"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2999065616.pdf","grobid_xml":"https://content.openalex.org/works/W2999065616.grobid-xml"},"referenced_works_count":43,"referenced_works":["https://openalex.org/W85350352","https://openalex.org/W565220493","https://openalex.org/W617456691","https://openalex.org/W980627162","https://openalex.org/W1540596182","https://openalex.org/W1549853718","https://openalex.org/W1663973292","https://openalex.org/W1778605331","https://openalex.org/W1973235744","https://openalex.org/W1978477206","https://openalex.org/W1994974007","https://openalex.org/W2007961939","https://openalex.org/W2028590934","https://openalex.org/W2038745796","https://openalex.org/W2074972084","https://openalex.org/W2125877832","https://openalex.org/W2152575748","https://openalex.org/W2154299908","https://openalex.org/W2165136605","https://openalex.org/W2336768730","https://openalex.org/W2570027862","https://openalex.org/W2611356217","https://openalex.org/W2738552792","https://openalex.org/W2767996841","https://openalex.org/W2768705038","https://openalex.org/W2771476119","https://openalex.org/W2895550934","https://openalex.org/W2896068576","https://openalex.org/W2908513159","https://openalex.org/W2946508744","https://openalex.org/W2950487361","https://openalex.org/W2958796907","https://openalex.org/W2963874858","https://openalex.org/W2967844267","https://openalex.org/W2970770192","https://openalex.org/W2971294566","https://openalex.org/W3144619878","https://openalex.org/W4206678871","https://openalex.org/W4212863985","https://openalex.org/W6632267817","https://openalex.org/W6638067389","https://openalex.org/W6702960241","https://openalex.org/W6737144532"],"related_works":["https://openalex.org/W4382795578","https://openalex.org/W2355463328","https://openalex.org/W2402648945","https://openalex.org/W2141801573","https://openalex.org/W1431147547","https://openalex.org/W2055761197","https://openalex.org/W939486154","https://openalex.org/W3006927476","https://openalex.org/W2249605127","https://openalex.org/W2367484911"],"abstract_inverted_index":{"Mahalanobis-Taguchi":[0],"System":[1],"(MTS),":[2],"as":[3,63,65],"a":[4,10,15,36,133,154],"pattern":[5],"recognition":[6],"method":[7,117,131],"by":[8],"constructing":[9],"continuous":[11],"measurement":[12],"scale,":[13],"has":[14,34,132,153],"very":[16],"good":[17],"performance":[18,136],"on":[19,121,140,142,151],"classification":[20,135],"and":[21,69,101,112,146],"feature":[22],"selection":[23],"for":[24],"real-valued":[25],"data.":[26,87],"However,":[27,148],"the":[28,40,90],"record":[29],"of":[30],"symbolic":[31,85,97,106],"interval":[32,86,98,107,122],"data":[33,99,108],"become":[35],"common":[37],"practice":[38],"with":[39,95,104,118],"recent":[41],"advances":[42],"in":[43],"database":[44],"technologies.":[45],"Kernel":[46],"methods":[47],"not":[48],"only":[49],"are":[50,110],"powerful":[51],"statistical":[52],"nonlinear":[53],"learning":[54],"methods,":[55],"but":[56],"also":[57],"can":[58],"be":[59],"defined":[60],"over":[61],"objects":[62],"diverse":[64],"graphs,":[66],"sets,":[67],"strings,":[68],"text":[70],"documents.":[71],"In":[72],"this":[73],"paper,":[74],"we":[75,113],"derive":[76],"kernel":[77],"Mahalanobis":[78,123],"distance":[79,124],"(KMD)":[80],"to":[81,84],"extend":[82],"MTS":[83,119,138,149],"To":[88],"evaluate":[89],"proposed":[91],"method,":[92],"four":[93],"experiments":[94,103],"synthetic":[96],"sets":[100,109],"seven":[102],"real":[105],"performed":[111],"have":[114],"compared":[115],"our":[116,130,160],"based":[120,139,150],"(IMD).":[125],"The":[126],"experimental":[127],"results":[128],"show":[129],"better":[134],"than":[137,159],"IMD":[141,152],"Accuracy,":[143],"Specificity,":[144],"Sensitivity,":[145],"G-means.":[147],"stronger":[155],"dimension":[156],"reduction":[157],"rate":[158],"method.":[161]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":4}],"updated_date":"2026-05-06T08:25:59.206177","created_date":"2025-10-10T00:00:00"}
