{"id":"https://openalex.org/W2129993950","doi":"https://doi.org/10.1109/icsmc.2004.1401103","title":"Evolution and interpretation of MTM-NNTrees","display_name":"Evolution and interpretation of MTM-NNTrees","publication_year":2005,"publication_date":"2005-03-31","ids":{"openalex":"https://openalex.org/W2129993950","doi":"https://doi.org/10.1109/icsmc.2004.1401103","mag":"2129993950"},"language":"en","primary_location":{"id":"doi:10.1109/icsmc.2004.1401103","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icsmc.2004.1401103","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2004 IEEE International Conference on Systems, Man and Cybernetics (IEEE Cat. No.04CH37583)","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/A5069452869","display_name":"Qiangfu Zhao","orcid":"https://orcid.org/0000-0003-3101-749X"},"institutions":[{"id":"https://openalex.org/I141591182","display_name":"University of Aizu","ror":"https://ror.org/02pg0e883","country_code":"JP","type":"education","lineage":["https://openalex.org/I141591182"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Qiangfu Zhao","raw_affiliation_strings":["University of Aizu, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Aizu, Japan","institution_ids":["https://openalex.org/I141591182"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103372695","display_name":"Chun Lu","orcid":null},"institutions":[{"id":"https://openalex.org/I76569877","display_name":"Southeast University","ror":"https://ror.org/04ct4d772","country_code":"CN","type":"education","lineage":["https://openalex.org/I76569877"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chun Lu","raw_affiliation_strings":["South-East University, Nanjing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"South-East University, Nanjing, China","institution_ids":["https://openalex.org/I76569877"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5108517807","display_name":"Wenjiand Pei","orcid":null},"institutions":[{"id":"https://openalex.org/I76569877","display_name":"Southeast University","ror":"https://ror.org/04ct4d772","country_code":"CN","type":"education","lineage":["https://openalex.org/I76569877"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wenjiand Pei","raw_affiliation_strings":["South-East University, Nanjing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"South-East University, Nanjing, China","institution_ids":["https://openalex.org/I76569877"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5113938150","display_name":"Zhenya He","orcid":null},"institutions":[{"id":"https://openalex.org/I76569877","display_name":"Southeast University","ror":"https://ror.org/04ct4d772","country_code":"CN","type":"education","lineage":["https://openalex.org/I76569877"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhenya He","raw_affiliation_strings":["South-East University, Nanjing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"South-East University, Nanjing, China","institution_ids":["https://openalex.org/I76569877"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.7394,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.71840767,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"6","issue":null,"first_page":"5702","last_page":"5707"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10320","display_name":"Neural Networks and Applications","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/T10320","display_name":"Neural Networks and Applications","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"}},{"id":"https://openalex.org/T11063","display_name":"Rough Sets and Fuzzy Logic","score":0.9937999844551086,"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/T10057","display_name":"Face and Expression Recognition","score":0.9918000102043152,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7560639381408691},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6949419379234314},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.6016614437103271},{"id":"https://openalex.org/keywords/interpretation","display_name":"Interpretation (philosophy)","score":0.5417277812957764},{"id":"https://openalex.org/keywords/tree","display_name":"Tree (set theory)","score":0.5194084644317627},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.505355179309845},{"id":"https://openalex.org/keywords/node","display_name":"Node (physics)","score":0.5012667179107666},{"id":"https://openalex.org/keywords/decision-tree","display_name":"Decision tree","score":0.48582908511161804},{"id":"https://openalex.org/keywords/perceptron","display_name":"Perceptron","score":0.43986764550209045},{"id":"https://openalex.org/keywords/tree-structure","display_name":"Tree structure","score":0.41502827405929565},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.22070425748825073},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.12264710664749146},{"id":"https://openalex.org/keywords/binary-tree","display_name":"Binary tree","score":0.09704115986824036},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.06596946716308594}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7560639381408691},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6949419379234314},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.6016614437103271},{"id":"https://openalex.org/C527412718","wikidata":"https://www.wikidata.org/wiki/Q855395","display_name":"Interpretation (philosophy)","level":2,"score":0.5417277812957764},{"id":"https://openalex.org/C113174947","wikidata":"https://www.wikidata.org/wiki/Q2859736","display_name":"Tree (set theory)","level":2,"score":0.5194084644317627},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.505355179309845},{"id":"https://openalex.org/C62611344","wikidata":"https://www.wikidata.org/wiki/Q1062658","display_name":"Node (physics)","level":2,"score":0.5012667179107666},{"id":"https://openalex.org/C84525736","wikidata":"https://www.wikidata.org/wiki/Q831366","display_name":"Decision tree","level":2,"score":0.48582908511161804},{"id":"https://openalex.org/C60908668","wikidata":"https://www.wikidata.org/wiki/Q690207","display_name":"Perceptron","level":3,"score":0.43986764550209045},{"id":"https://openalex.org/C163797641","wikidata":"https://www.wikidata.org/wiki/Q2067937","display_name":"Tree structure","level":3,"score":0.41502827405929565},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.22070425748825073},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.12264710664749146},{"id":"https://openalex.org/C197855036","wikidata":"https://www.wikidata.org/wiki/Q380172","display_name":"Binary tree","level":2,"score":0.09704115986824036},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.06596946716308594},{"id":"https://openalex.org/C66938386","wikidata":"https://www.wikidata.org/wiki/Q633538","display_name":"Structural engineering","level":1,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icsmc.2004.1401103","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icsmc.2004.1401103","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2004 IEEE International Conference on Systems, Man and Cybernetics (IEEE Cat. No.04CH37583)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/16","display_name":"Peace, Justice and strong institutions","score":0.5899999737739563}],"awards":[],"funders":[{"id":"https://openalex.org/F4320334764","display_name":"Japan Society for the Promotion of Science","ror":"https://ror.org/00hhkn466"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":16,"referenced_works":["https://openalex.org/W1510445422","https://openalex.org/W1539678260","https://openalex.org/W1593227966","https://openalex.org/W1857290210","https://openalex.org/W2088203270","https://openalex.org/W2125055259","https://openalex.org/W2142260217","https://openalex.org/W2145470394","https://openalex.org/W2155092378","https://openalex.org/W2158599326","https://openalex.org/W2532845490","https://openalex.org/W2541218906","https://openalex.org/W6635572812","https://openalex.org/W6639077117","https://openalex.org/W6672596321","https://openalex.org/W6729149155"],"related_works":["https://openalex.org/W1985727224","https://openalex.org/W2376211578","https://openalex.org/W2093885745","https://openalex.org/W2351266481","https://openalex.org/W2132547887","https://openalex.org/W2071459461","https://openalex.org/W2516987005","https://openalex.org/W2907786475","https://openalex.org/W2963447120","https://openalex.org/W4289082820"],"abstract_inverted_index":{"Neural":[0],"network":[1,26],"tree":[2,16],"(NNTree)":[3],"is":[4,52,70,76,111],"a":[5,14,100,107,118,131],"hybrid":[6],"learning":[7,64],"model":[8,60],"with":[9],"the":[10,45,78,157],"overall":[11],"structure":[12],"being":[13,22],"decision":[15],"(DT)":[17],"and":[18,65,134,152],"each":[19,50,114,125],"non-terminal":[20],"node":[21],"an":[23,58,74,135,146],"expert":[24],"neural":[25],"(ENN).":[27],"So":[28],"far":[29],"we":[30,98,144],"have":[31],"shown":[32],"through":[33,154],"experiments":[34,155],"that":[35,71,156],"NNTrees":[36,55,104],"are":[37,159],"not":[38,84],"only":[39],"learnable,":[40],"but":[41],"also":[42],"interpretable":[43],"if":[44,73],"number":[46],"of":[47,103,117],"inputs":[48],"for":[49,61,113,149],"ENN":[51,115],"limited.":[53],"Therefore,":[54],"might":[56],"be":[57,85,128,138],"efficient":[59],"unifying":[62],"both":[63],"understanding.":[66],"One":[67],"important":[68],"problem":[69],"even":[72],"NNTree":[75],"interpretable,":[77],"rules":[79],"extracted":[80],"from":[81],"it":[82],"may":[83,89],"understandable":[86],"because":[87],"they":[88],"contain":[90],"too":[91],"many":[92],"details.":[93],"To":[94],"solve":[95],"this":[96,123,142],"problem,":[97],"propose":[99],"new":[101],"type":[102],"in":[105],"which":[106],"multi-template":[108],"matcher":[109],"(MTM)":[110],"used":[112,129],"instead":[116],"multilayer":[119],"perceptron":[120],"(MLP).":[121],"In":[122,141],"model,":[124],"template":[126],"can":[127,137],"as":[130,160,162],"previous":[132],"case,":[133],"MTM-NNTree":[136],"understood":[139],"straightforwardly.":[140],"paper,":[143],"provide":[145],"evolutionary":[147],"algorithm":[148],"designing":[150],"MTM-NNTrees,":[151],"show":[153],"MTM-NNTrees":[158],"powerful":[161],"MLP-NNTrees.":[163]},"counts_by_year":[],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
