{"id":"https://openalex.org/W2810672180","doi":"https://doi.org/10.1109/fskd.2017.8393063","title":"A method for principal components selection based on stochastic matrix","display_name":"A method for principal components selection based on stochastic matrix","publication_year":2017,"publication_date":"2017-07-01","ids":{"openalex":"https://openalex.org/W2810672180","doi":"https://doi.org/10.1109/fskd.2017.8393063","mag":"2810672180"},"language":"en","primary_location":{"id":"doi:10.1109/fskd.2017.8393063","is_oa":false,"landing_page_url":"https://doi.org/10.1109/fskd.2017.8393063","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/A5077862135","display_name":"Yangwu Zhang","orcid":"https://orcid.org/0000-0002-6922-4390"},"institutions":[{"id":"https://openalex.org/I204553293","display_name":"China University of Petroleum, Beijing","ror":"https://ror.org/041qf4r12","country_code":"CN","type":"education","lineage":["https://openalex.org/I204553293"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yangwu Zhang","raw_affiliation_strings":["College of Geophysics and Information Engineering, China University of Petroleum-Beijing, Beijing, China"],"affiliations":[{"raw_affiliation_string":"College of Geophysics and Information Engineering, China University of Petroleum-Beijing, Beijing, China","institution_ids":["https://openalex.org/I204553293"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102844195","display_name":"Guohe Li","orcid":"https://orcid.org/0009-0008-9982-4478"},"institutions":[{"id":"https://openalex.org/I204553293","display_name":"China University of Petroleum, Beijing","ror":"https://ror.org/041qf4r12","country_code":"CN","type":"education","lineage":["https://openalex.org/I204553293"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Guohe Li","raw_affiliation_strings":["Beijing Key Lab of Data Mining for Petroleum Data, China University of Petroleum-Beijing, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Beijing Key Lab of Data Mining for Petroleum Data, China University of Petroleum-Beijing, Beijing, China","institution_ids":["https://openalex.org/I204553293"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100695800","display_name":"Limei Wang","orcid":"https://orcid.org/0000-0001-9757-4569"},"institutions":[{"id":"https://openalex.org/I177955009","display_name":"China University of Political Science and Law","ror":"https://ror.org/00e49gy82","country_code":"CN","type":"education","lineage":["https://openalex.org/I177955009"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Limei Wang","raw_affiliation_strings":["Department of Science and Technology Teaching, China University of Political Science and Law, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Department of Science and Technology Teaching, China University of Political Science and Law, Beijing, China","institution_ids":["https://openalex.org/I177955009"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5058178865","display_name":"Heng Zong","orcid":null},"institutions":[{"id":"https://openalex.org/I177955009","display_name":"China University of Political Science and Law","ror":"https://ror.org/00e49gy82","country_code":"CN","type":"education","lineage":["https://openalex.org/I177955009"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Heng Zong","raw_affiliation_strings":["Department of Science and Technology Teaching, China University of Political Science and Law, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Department of Science and Technology Teaching, China University of Political Science and Law, Beijing, China","institution_ids":["https://openalex.org/I177955009"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5081864317","display_name":"Jingming Zhao","orcid":"https://orcid.org/0000-0002-1019-1029"},"institutions":[{"id":"https://openalex.org/I177955009","display_name":"China University of Political Science and Law","ror":"https://ror.org/00e49gy82","country_code":"CN","type":"education","lineage":["https://openalex.org/I177955009"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jingming Zhao","raw_affiliation_strings":["Department of Science and Technology Teaching, China University of Political Science and Law, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Department of Science and Technology Teaching, China University of Political Science and Law, Beijing, China","institution_ids":["https://openalex.org/I177955009"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5077862135"],"corresponding_institution_ids":["https://openalex.org/I204553293"],"apc_list":null,"apc_paid":null,"fwci":0.2271,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.60056599,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"51","issue":null,"first_page":"1927","last_page":"1933"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11063","display_name":"Rough Sets and Fuzzy Logic","score":0.9940999746322632,"subfield":{"id":"https://openalex.org/subfields/1703","display_name":"Computational Theory and Mathematics"},"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/T11063","display_name":"Rough Sets and Fuzzy Logic","score":0.9940999746322632,"subfield":{"id":"https://openalex.org/subfields/1703","display_name":"Computational Theory and Mathematics"},"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/T11550","display_name":"Text and Document Classification Technologies","score":0.958299994468689,"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/T10538","display_name":"Data Mining Algorithms and Applications","score":0.9261000156402588,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/principal-component-analysis","display_name":"Principal component analysis","score":0.9116044044494629},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.58250492811203},{"id":"https://openalex.org/keywords/maximization","display_name":"Maximization","score":0.5083217024803162},{"id":"https://openalex.org/keywords/selection","display_name":"Selection (genetic algorithm)","score":0.4936922490596771},{"id":"https://openalex.org/keywords/covariance-matrix","display_name":"Covariance matrix","score":0.4870813190937042},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4778549373149872},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.47190409898757935},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.46478673815727234},{"id":"https://openalex.org/keywords/matrix","display_name":"Matrix (chemical analysis)","score":0.4538693130016327},{"id":"https://openalex.org/keywords/random-variable","display_name":"Random variable","score":0.4160471558570862},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.31421905755996704},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.30921658873558044},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.29264938831329346}],"concepts":[{"id":"https://openalex.org/C27438332","wikidata":"https://www.wikidata.org/wiki/Q2873","display_name":"Principal component analysis","level":2,"score":0.9116044044494629},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.58250492811203},{"id":"https://openalex.org/C2776330181","wikidata":"https://www.wikidata.org/wiki/Q18358244","display_name":"Maximization","level":2,"score":0.5083217024803162},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.4936922490596771},{"id":"https://openalex.org/C185142706","wikidata":"https://www.wikidata.org/wiki/Q1134404","display_name":"Covariance matrix","level":2,"score":0.4870813190937042},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4778549373149872},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.47190409898757935},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.46478673815727234},{"id":"https://openalex.org/C106487976","wikidata":"https://www.wikidata.org/wiki/Q685816","display_name":"Matrix (chemical analysis)","level":2,"score":0.4538693130016327},{"id":"https://openalex.org/C122123141","wikidata":"https://www.wikidata.org/wiki/Q176623","display_name":"Random variable","level":2,"score":0.4160471558570862},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.31421905755996704},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.30921658873558044},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.29264938831329346},{"id":"https://openalex.org/C159985019","wikidata":"https://www.wikidata.org/wiki/Q181790","display_name":"Composite material","level":1,"score":0.0},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/fskd.2017.8393063","is_oa":false,"landing_page_url":"https://doi.org/10.1109/fskd.2017.8393063","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":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":19,"referenced_works":["https://openalex.org/W1555148682","https://openalex.org/W1563232040","https://openalex.org/W1848453437","https://openalex.org/W1956559956","https://openalex.org/W1965555084","https://openalex.org/W1982530130","https://openalex.org/W1989962885","https://openalex.org/W2031248101","https://openalex.org/W2067092078","https://openalex.org/W2105842272","https://openalex.org/W2113620787","https://openalex.org/W2165612380","https://openalex.org/W2251567929","https://openalex.org/W2322917384","https://openalex.org/W2325227998","https://openalex.org/W2516723902","https://openalex.org/W2520488855","https://openalex.org/W4292023222","https://openalex.org/W6675783020"],"related_works":["https://openalex.org/W1975632186","https://openalex.org/W3027745756","https://openalex.org/W3205213561","https://openalex.org/W2531880140","https://openalex.org/W2126145365","https://openalex.org/W2036609560","https://openalex.org/W346861917","https://openalex.org/W3024018414","https://openalex.org/W1542592062","https://openalex.org/W4380081032"],"abstract_inverted_index":{"Principal":[0],"component":[1,23],"analysis":[2],"(PCA)":[3],"is":[4],"a":[5,55,73],"feature":[6],"extraction":[7],"method":[8,74,97],"of":[9,29,49,58,64,75,84,98],"mapping":[10],"the":[11,20,27,47,61,68,81,96,110,117,123],"original":[12],"characteristic":[13],"term":[14],"space":[15],"with":[16],"high-dimensional":[17],"sparsity":[18],"into":[19],"low-dimensional":[21],"principal":[22,36,65,76,85,99,111],"space,":[24],"by":[25],"utilizing":[26],"principle":[28],"variance":[30],"maximization.":[31],"In":[32],"random":[33,41,50,104],"matrix":[34,105],"theory,":[35],"components":[37,66,77,86,100],"are":[38,46,54],"treated":[39],"as":[40],"variables,":[42],"and":[43],"data":[44,59],"samples":[45],"observations":[48],"vectors.":[51],"When":[52],"there":[53],"large":[56],"amount":[57],"samples,":[60],"observed":[62],"values":[63],"obey":[67],"normal":[69],"distribution.":[70],"We":[71],"proposed":[72],"selection":[78,101],"based":[79,102],"on":[80,91,103],"differential":[82],"distribution":[83],"in":[87],"different":[88],"classes.":[89],"Experiment":[90],"text":[92],"classification":[93,118],"indicated":[94],"that":[95],"theory":[106],"can":[107],"effectively":[108],"determine":[109],"components.":[112],"This":[113],"not":[114],"only":[115],"improves":[116],"performance,":[119],"but":[120],"also":[121],"reduces":[122],"computational":[124],"cost.":[125]},"counts_by_year":[{"year":2022,"cited_by_count":1},{"year":2018,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
