{"id":"https://openalex.org/W1500824394","doi":"https://doi.org/10.1109/ijcnn.2005.1555962","title":"Symbolic rule extraction with a scaled conjugate gradient version of CLARION","display_name":"Symbolic rule extraction with a scaled conjugate gradient version of CLARION","publication_year":2006,"publication_date":"2006-01-05","ids":{"openalex":"https://openalex.org/W1500824394","doi":"https://doi.org/10.1109/ijcnn.2005.1555962","mag":"1500824394"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn.2005.1555962","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2005.1555962","pdf_url":null,"source":{"id":"https://openalex.org/S4363609022","display_name":"Proceedings. 2005 IEEE International Joint Conference on Neural Networks, 2005.","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":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings. 2005 IEEE International Joint Conference on Neural Networks, 2005.","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"http://doi.org/10.1109/IJCNN.2005.1555962","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5085187431","display_name":"T. Falas","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"T. Falas","raw_affiliation_strings":["School of Computer Science and Engineering, Cypress Semiconductors, Inc., Nicosia, Cyprus"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, Cypress Semiconductors, Inc., Nicosia, Cyprus","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5108612969","display_name":"Andreas Stafylopatis","orcid":null},"institutions":[{"id":"https://openalex.org/I174458059","display_name":"National Technical University of Athens","ror":"https://ror.org/03cx6bg69","country_code":"GR","type":"education","lineage":["https://openalex.org/I174458059"]}],"countries":["GR"],"is_corresponding":false,"raw_author_name":"A. Stafylopatis","raw_affiliation_strings":["School of Electrical and Computer Engineering, National and Technical University of Athens, Athens, Greece"],"affiliations":[{"raw_affiliation_string":"School of Electrical and Computer Engineering, National and Technical University of Athens, Athens, Greece","institution_ids":["https://openalex.org/I174458059"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5085187431"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.4211,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.54699695,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":95},"biblio":{"volume":"2","issue":null,"first_page":"845","last_page":"848"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10320","display_name":"Neural Networks and Applications","score":0.9998999834060669,"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/T10320","display_name":"Neural Networks and Applications","score":0.9998999834060669,"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/T10820","display_name":"Fuzzy Logic and Control Systems","score":0.994700014591217,"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/T11975","display_name":"Evolutionary Algorithms and Applications","score":0.967199981212616,"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/clarion","display_name":"CLARION","score":0.8353734016418457},{"id":"https://openalex.org/keywords/conjugate-gradient-method","display_name":"Conjugate gradient method","score":0.7872418165206909},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7823137044906616},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.6159517765045166},{"id":"https://openalex.org/keywords/originality","display_name":"Originality","score":0.5491533279418945},{"id":"https://openalex.org/keywords/line","display_name":"Line (geometry)","score":0.4985189437866211},{"id":"https://openalex.org/keywords/layer","display_name":"Layer (electronics)","score":0.4733300805091858},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4651307463645935},{"id":"https://openalex.org/keywords/hybrid-system","display_name":"Hybrid system","score":0.45829448103904724},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3998258411884308},{"id":"https://openalex.org/keywords/computer-engineering","display_name":"Computer engineering","score":0.33785009384155273},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.27032652497291565},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.11969581246376038}],"concepts":[{"id":"https://openalex.org/C84857602","wikidata":"https://www.wikidata.org/wiki/Q5012668","display_name":"CLARION","level":2,"score":0.8353734016418457},{"id":"https://openalex.org/C81184566","wikidata":"https://www.wikidata.org/wiki/Q1191895","display_name":"Conjugate gradient method","level":2,"score":0.7872418165206909},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7823137044906616},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.6159517765045166},{"id":"https://openalex.org/C2776950860","wikidata":"https://www.wikidata.org/wiki/Q2914681","display_name":"Originality","level":3,"score":0.5491533279418945},{"id":"https://openalex.org/C198352243","wikidata":"https://www.wikidata.org/wiki/Q37105","display_name":"Line (geometry)","level":2,"score":0.4985189437866211},{"id":"https://openalex.org/C2779227376","wikidata":"https://www.wikidata.org/wiki/Q6505497","display_name":"Layer (electronics)","level":2,"score":0.4733300805091858},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4651307463645935},{"id":"https://openalex.org/C50897621","wikidata":"https://www.wikidata.org/wiki/Q2665508","display_name":"Hybrid system","level":2,"score":0.45829448103904724},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3998258411884308},{"id":"https://openalex.org/C113775141","wikidata":"https://www.wikidata.org/wiki/Q428691","display_name":"Computer engineering","level":1,"score":0.33785009384155273},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.27032652497291565},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.11969581246376038},{"id":"https://openalex.org/C178790620","wikidata":"https://www.wikidata.org/wiki/Q11351","display_name":"Organic chemistry","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C11012388","wikidata":"https://www.wikidata.org/wiki/Q170658","display_name":"Creativity","level":2,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/ijcnn.2005.1555962","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2005.1555962","pdf_url":null,"source":{"id":"https://openalex.org/S4363609022","display_name":"Proceedings. 2005 IEEE International Joint Conference on Neural Networks, 2005.","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":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings. 2005 IEEE International Joint Conference on Neural Networks, 2005.","raw_type":"proceedings-article"},{"id":"pmh:oai:dspace.lib.ntua.gr:123456789/31479","is_oa":true,"landing_page_url":"http://doi.org/10.1109/IJCNN.2005.1555962","pdf_url":null,"source":{"id":"https://openalex.org/S4377196837","display_name":"DSpace - NTUA (National Technical University of Athens)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I174458059","host_organization_name":"National Technical University of Athens","host_organization_lineage":["https://openalex.org/I174458059"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Proceedings of the International Joint Conference on Neural Networks","raw_type":"info:eu-repo/semantics/conferenceObject"}],"best_oa_location":{"id":"pmh:oai:dspace.lib.ntua.gr:123456789/31479","is_oa":true,"landing_page_url":"http://doi.org/10.1109/IJCNN.2005.1555962","pdf_url":null,"source":{"id":"https://openalex.org/S4377196837","display_name":"DSpace - NTUA (National Technical University of Athens)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I174458059","host_organization_name":"National Technical University of Athens","host_organization_lineage":["https://openalex.org/I174458059"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Proceedings of the International Joint Conference on Neural Networks","raw_type":"info:eu-repo/semantics/conferenceObject"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":18,"referenced_works":["https://openalex.org/W32403112","https://openalex.org/W1525594942","https://openalex.org/W1900101064","https://openalex.org/W2016879831","https://openalex.org/W2051812123","https://openalex.org/W2096867547","https://openalex.org/W2100677568","https://openalex.org/W2104893957","https://openalex.org/W2113102527","https://openalex.org/W2126625980","https://openalex.org/W2154642048","https://openalex.org/W2155530592","https://openalex.org/W2766736793","https://openalex.org/W3011120880","https://openalex.org/W3041202696","https://openalex.org/W4214717370","https://openalex.org/W6631311747","https://openalex.org/W6682610290"],"related_works":["https://openalex.org/W121987298","https://openalex.org/W4241730252","https://openalex.org/W2593155302","https://openalex.org/W2041415459","https://openalex.org/W2072812638","https://openalex.org/W3126095231","https://openalex.org/W2283936668","https://openalex.org/W4234111389","https://openalex.org/W2569862494","https://openalex.org/W1982843346"],"abstract_inverted_index":{"This":[0,142],"paper":[1,143],"presents":[2],"a":[3,17,24,39,44,60,78,90,110],"hybrid":[4,111],"intelligent":[5],"system":[6,41,132,150],"made":[7],"up":[8],"of":[9,83,94,101,119,129],"two":[10,68],"modules.":[11],"The":[12,35,67,92],"bottom":[13,55],"sub-symbolic":[14],"module":[15,37,56],"is":[16,38,114,151],"multi-layer":[18],"feed-forward":[19],"neural":[20,45],"network":[21,46],"trained":[22],"by":[23],"modified":[25],"Q-learning":[26],"methodology":[27],"that":[28,116,156],"employs":[29],"the":[30,54,64,84,99,102,117,127,130,145,149],"scaled":[31,104],"conjugate":[32,105],"gradient":[33],"algorithm.":[34],"top":[36],"symbolic":[40],"(implemented":[42],"with":[43],"built":[47],"on-line)":[48],"where":[49],"rules":[50],"are":[51],"extracted":[52],"from":[53],"during":[57],"training,":[58],"in":[59,73,88,98,108,126],"fashion":[61],"similar":[62],"to":[63,76],"CLARION":[65],"system.":[66,112],"modules":[69,85],"augment":[70],"each":[71],"other":[72],"an":[74],"effort":[75],"obtain":[77],"better":[79],"performance":[80,128],"than":[81],"both":[82],"acting":[86],"alone":[87],"solving":[89],"problem.":[91],"originality":[93],"this":[95,120],"work":[96],"lies":[97],"use":[100,118],"advanced":[103],"learning":[106],"algorithm":[107,121],"such":[109],"It":[113],"expected":[115],"would":[122],"provide":[123],"significant":[124],"improvements":[125],"overall":[131],"and":[133],"also":[134],"make":[135],"it":[136],"less":[137],"dependent":[138],"on":[139],"user-selected":[140],"parameters.":[141],"emphasises":[144],"implementation":[146],"details,":[147],"since":[148],"currently":[152],"under":[153],"development,":[154],"rather":[155],"concrete":[157],"experimental":[158],"results.":[159]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2012,"cited_by_count":1}],"updated_date":"2026-03-20T23:20:44.827607","created_date":"2025-10-10T00:00:00"}
