{"id":"https://openalex.org/W2749453371","doi":"https://doi.org/10.1109/tfuzz.2017.2741444","title":"Learning Large-Scale Fuzzy Cognitive Maps Based on Compressed Sensing and Application in Reconstructing Gene Regulatory Networks","display_name":"Learning Large-Scale Fuzzy Cognitive Maps Based on Compressed Sensing and Application in Reconstructing Gene Regulatory Networks","publication_year":2017,"publication_date":"2017-08-17","ids":{"openalex":"https://openalex.org/W2749453371","doi":"https://doi.org/10.1109/tfuzz.2017.2741444","mag":"2749453371"},"language":"en","primary_location":{"id":"doi:10.1109/tfuzz.2017.2741444","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tfuzz.2017.2741444","pdf_url":null,"source":{"id":"https://openalex.org/S134177497","display_name":"IEEE Transactions on Fuzzy Systems","issn_l":"1063-6706","issn":["1063-6706","1941-0034"],"is_oa":false,"is_in_doaj":false,"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":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Fuzzy Systems","raw_type":"journal-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/A5037706636","display_name":"Kai Wu","orcid":"https://orcid.org/0000-0002-1852-6364"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Kai Wu","raw_affiliation_strings":["Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education, Xidian University, Xi'an, China"],"raw_orcid":"https://orcid.org/0000-0002-1852-6364","affiliations":[{"raw_affiliation_string":"Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education, Xidian University, Xi'an, China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100375038","display_name":"Jing Liu","orcid":"https://orcid.org/0000-0002-6834-5350"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jing Liu","raw_affiliation_strings":["Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education, Xidian University, Xi'an, China"],"raw_orcid":"https://orcid.org/0000-0002-6834-5350","affiliations":[{"raw_affiliation_string":"Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education, Xidian University, Xi'an, China","institution_ids":["https://openalex.org/I149594827"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I149594827"],"apc_list":null,"apc_paid":null,"fwci":4.7851,"has_fulltext":false,"cited_by_count":54,"citation_normalized_percentile":{"value":0.96021954,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":"25","issue":"6","first_page":"1546","last_page":"1560"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12805","display_name":"Cognitive Science and Mapping","score":0.9998000264167786,"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/T12805","display_name":"Cognitive Science and Mapping","score":0.9998000264167786,"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/fuzzy-cognitive-map","display_name":"Fuzzy cognitive map","score":0.8393344879150391},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.6812885403633118},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6087716817855835},{"id":"https://openalex.org/keywords/compressed-sensing","display_name":"Compressed sensing","score":0.5959866046905518},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.580558717250824},{"id":"https://openalex.org/keywords/scale","display_name":"Scale (ratio)","score":0.5729976892471313},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4823172092437744},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.42697620391845703},{"id":"https://openalex.org/keywords/fuzzy-logic","display_name":"Fuzzy logic","score":0.36652928590774536},{"id":"https://openalex.org/keywords/fuzzy-control-system","display_name":"Fuzzy control system","score":0.17524194717407227},{"id":"https://openalex.org/keywords/adaptive-neuro-fuzzy-inference-system","display_name":"Adaptive neuro fuzzy inference system","score":0.0718303918838501}],"concepts":[{"id":"https://openalex.org/C5041914","wikidata":"https://www.wikidata.org/wiki/Q5511107","display_name":"Fuzzy cognitive map","level":5,"score":0.8393344879150391},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.6812885403633118},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6087716817855835},{"id":"https://openalex.org/C124851039","wikidata":"https://www.wikidata.org/wiki/Q2665459","display_name":"Compressed sensing","level":2,"score":0.5959866046905518},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.580558717250824},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.5729976892471313},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4823172092437744},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.42697620391845703},{"id":"https://openalex.org/C58166","wikidata":"https://www.wikidata.org/wiki/Q224821","display_name":"Fuzzy logic","level":2,"score":0.36652928590774536},{"id":"https://openalex.org/C195975749","wikidata":"https://www.wikidata.org/wiki/Q1475705","display_name":"Fuzzy control system","level":3,"score":0.17524194717407227},{"id":"https://openalex.org/C186108316","wikidata":"https://www.wikidata.org/wiki/Q352530","display_name":"Adaptive neuro fuzzy inference system","level":4,"score":0.0718303918838501},{"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/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tfuzz.2017.2741444","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tfuzz.2017.2741444","pdf_url":null,"source":{"id":"https://openalex.org/S134177497","display_name":"IEEE Transactions on Fuzzy Systems","issn_l":"1063-6706","issn":["1063-6706","1941-0034"],"is_oa":false,"is_in_doaj":false,"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":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Fuzzy Systems","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":63,"referenced_works":["https://openalex.org/W227275893","https://openalex.org/W1459085915","https://openalex.org/W1578549529","https://openalex.org/W1967034721","https://openalex.org/W1975702385","https://openalex.org/W1977575836","https://openalex.org/W1986688807","https://openalex.org/W1986931325","https://openalex.org/W2010871295","https://openalex.org/W2012026701","https://openalex.org/W2015705737","https://openalex.org/W2023348596","https://openalex.org/W2024461600","https://openalex.org/W2024826298","https://openalex.org/W2027266048","https://openalex.org/W2028781966","https://openalex.org/W2031535420","https://openalex.org/W2034669994","https://openalex.org/W2047755165","https://openalex.org/W2050847486","https://openalex.org/W2066031679","https://openalex.org/W2081232506","https://openalex.org/W2086750561","https://openalex.org/W2089082497","https://openalex.org/W2089085970","https://openalex.org/W2092394555","https://openalex.org/W2092744745","https://openalex.org/W2095224843","https://openalex.org/W2095639638","https://openalex.org/W2098701811","https://openalex.org/W2104266187","https://openalex.org/W2114362965","https://openalex.org/W2119667497","https://openalex.org/W2120991191","https://openalex.org/W2121657501","https://openalex.org/W2122879929","https://openalex.org/W2135046866","https://openalex.org/W2135185946","https://openalex.org/W2137947700","https://openalex.org/W2145096794","https://openalex.org/W2148605346","https://openalex.org/W2157121418","https://openalex.org/W2158284104","https://openalex.org/W2159803222","https://openalex.org/W2164452299","https://openalex.org/W2245364275","https://openalex.org/W2283131038","https://openalex.org/W2296616510","https://openalex.org/W2306180594","https://openalex.org/W2312599005","https://openalex.org/W2316564661","https://openalex.org/W2520865593","https://openalex.org/W2560897075","https://openalex.org/W2562985317","https://openalex.org/W2566248507","https://openalex.org/W2612413108","https://openalex.org/W2803670972","https://openalex.org/W3187784670","https://openalex.org/W4236019906","https://openalex.org/W4238744307","https://openalex.org/W4250589301","https://openalex.org/W4250955649","https://openalex.org/W6608954586"],"related_works":["https://openalex.org/W2378211422","https://openalex.org/W2063798559","https://openalex.org/W2158224665","https://openalex.org/W2343440291","https://openalex.org/W4321353415","https://openalex.org/W2745001401","https://openalex.org/W2991207020","https://openalex.org/W2130974462","https://openalex.org/W2379589510","https://openalex.org/W2028665553"],"abstract_inverted_index":{"Learning":[0],"large-scale":[1,30,53,189],"sparse":[2,54,73,85,135,190],"fuzzy":[3],"cognitive":[4],"maps":[5],"(FCMs)":[6],"from":[7,125],"observed":[8],"data":[9,105],"automatically":[10],"without":[11],"any":[12],"prior":[13],"knowledge":[14],"remains":[15],"an":[16],"outstanding":[17],"problem.":[18],"Most":[19],"existing":[20],"methods":[21],"are":[22,169],"slow":[23],"and":[24,109,111,140,161,167],"have":[25,144],"difficulty":[26],"in":[27,180],"dealing":[28],"with":[29,59,106,137,192],"FCMs,":[31,55,63],"because":[32],"of":[33,62,66,79,129],"the":[34,60,64,84,89,96,162],"large":[35],"searching":[36],"space.":[37],"We":[38],"develop":[39],"a":[40,47,126,185],"framework":[41],"based":[42],"on":[43],"compressed":[44],"sensing":[45],"(CS),":[46],"convex":[48],"optimization":[49],"method,":[50],"to":[51,81,91,101,148,155],"learn":[52,93,102,134],"called":[56],"CS-FCM.":[57],"Combining":[58],"sparsity":[61],"task":[65],"learning":[67,124,188],"FCMs":[68,136,191],"is":[69,99,152],"first":[70],"decomposed":[71],"into":[72],"signal":[74],"reconstruction":[75],"problems.":[76],"The":[77,114,171],"ability":[78],"CS":[80],"exactly":[82,92],"recover":[83],"signals":[86],"provides":[87],"CS-FCM":[88,98,118,131,151,175,183],"probability":[90],"FCMs.":[94],"In":[95],"experiments,":[97],"applied":[100,154],"both":[103],"synthetic":[104],"varying":[107],"sizes":[108],"densities":[110],"real-life":[112],"data.":[113,130],"results":[115,172],"show":[116,173],"that":[117,174],"obtains":[119,177],"good":[120],"performance":[121],"by":[122],"just":[123],"small":[127],"amount":[128],"can":[132],"effectively":[133],"1000":[138],"nodes":[139],"even":[141],"more,":[142],"which":[143],"one":[145],"million":[146],"weights":[147],"be":[149],"determined.":[150],"also":[153,176],"reconstruct":[156],"gene":[157],"regulatory":[158],"networks":[159],"(GRNs),":[160],"well-known":[163],"benchmark":[164],"datasets":[165],"DREAM3":[166],"DREAM4":[168],"tested.":[170],"high":[178,193],"accuracy":[179],"reconstructing":[181],"GRNs.":[182],"establishes":[184],"paradigm":[186],"for":[187],"accuracy.":[194]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":6},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":8},{"year":2021,"cited_by_count":7},{"year":2020,"cited_by_count":10},{"year":2019,"cited_by_count":10},{"year":2018,"cited_by_count":4}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}