{"id":"https://openalex.org/W2137170240","doi":"https://doi.org/10.1109/icsmc.2007.4413837","title":"Comparison between real-time learning capabilities of the IDS method and Radial Basis Function Networks","display_name":"Comparison between real-time learning capabilities of the IDS method and Radial Basis Function Networks","publication_year":2007,"publication_date":"2007-10-01","ids":{"openalex":"https://openalex.org/W2137170240","doi":"https://doi.org/10.1109/icsmc.2007.4413837","mag":"2137170240"},"language":"en","primary_location":{"id":"doi:10.1109/icsmc.2007.4413837","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icsmc.2007.4413837","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2007 IEEE International Conference on Systems, Man and Cybernetics","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/A5058869794","display_name":"Masayuki Murakami","orcid":"https://orcid.org/0000-0003-1649-196X"},"institutions":[{"id":"https://openalex.org/I20529979","display_name":"University of Electro-Communications","ror":"https://ror.org/02x73b849","country_code":"JP","type":"education","lineage":["https://openalex.org/I20529979"]}],"countries":["JP"],"is_corresponding":true,"raw_author_name":"Masayuki Murakami","raw_affiliation_strings":["Department of Systems Engineering, University of Electro-Communications, Chofu, Tokyo, Japan","Univ. of Electro-Commun., Tokyo"],"affiliations":[{"raw_affiliation_string":"Department of Systems Engineering, University of Electro-Communications, Chofu, Tokyo, Japan","institution_ids":["https://openalex.org/I20529979"]},{"raw_affiliation_string":"Univ. of Electro-Commun., Tokyo","institution_ids":["https://openalex.org/I20529979"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5109076270","display_name":"Nakaji Honda","orcid":null},"institutions":[{"id":"https://openalex.org/I20529979","display_name":"University of Electro-Communications","ror":"https://ror.org/02x73b849","country_code":"JP","type":"education","lineage":["https://openalex.org/I20529979"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Nakaji Honda","raw_affiliation_strings":["Department of Systems Engineering, University of Electro-Communications, Chofu, Tokyo, Japan","Univ. of Electro-Commun., Tokyo"],"affiliations":[{"raw_affiliation_string":"Department of Systems Engineering, University of Electro-Communications, Chofu, Tokyo, Japan","institution_ids":["https://openalex.org/I20529979"]},{"raw_affiliation_string":"Univ. of Electro-Commun., Tokyo","institution_ids":["https://openalex.org/I20529979"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5058869794"],"corresponding_institution_ids":["https://openalex.org/I20529979"],"apc_list":null,"apc_paid":null,"fwci":0.4693,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.76201263,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"3","issue":null,"first_page":"1262","last_page":"1267"},"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/T12676","display_name":"Machine Learning and ELM","score":0.9937999844551086,"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/T10057","display_name":"Face and Expression Recognition","score":0.9842000007629395,"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/radial-basis-function","display_name":"Radial basis function","score":0.7700297236442566},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7613090872764587},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.7512897849082947},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6551227569580078},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.6050034761428833},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5801734328269958},{"id":"https://openalex.org/keywords/convergence","display_name":"Convergence (economics)","score":0.5686289072036743},{"id":"https://openalex.org/keywords/function","display_name":"Function (biology)","score":0.4966948628425598}],"concepts":[{"id":"https://openalex.org/C98856871","wikidata":"https://www.wikidata.org/wiki/Q1588488","display_name":"Radial basis function","level":3,"score":0.7700297236442566},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7613090872764587},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.7512897849082947},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6551227569580078},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.6050034761428833},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5801734328269958},{"id":"https://openalex.org/C2777303404","wikidata":"https://www.wikidata.org/wiki/Q759757","display_name":"Convergence (economics)","level":2,"score":0.5686289072036743},{"id":"https://openalex.org/C14036430","wikidata":"https://www.wikidata.org/wiki/Q3736076","display_name":"Function (biology)","level":2,"score":0.4966948628425598},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0},{"id":"https://openalex.org/C50522688","wikidata":"https://www.wikidata.org/wiki/Q189833","display_name":"Economic growth","level":1,"score":0.0},{"id":"https://openalex.org/C78458016","wikidata":"https://www.wikidata.org/wiki/Q840400","display_name":"Evolutionary biology","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icsmc.2007.4413837","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icsmc.2007.4413837","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2007 IEEE International Conference on Systems, Man and Cybernetics","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":16,"referenced_works":["https://openalex.org/W19156176","https://openalex.org/W1986915529","https://openalex.org/W2095701484","https://openalex.org/W2097038759","https://openalex.org/W2097175829","https://openalex.org/W2099005356","https://openalex.org/W2099244771","https://openalex.org/W2107115494","https://openalex.org/W2110158084","https://openalex.org/W2111284535","https://openalex.org/W2114160202","https://openalex.org/W2122785831","https://openalex.org/W2171277043","https://openalex.org/W2310376671","https://openalex.org/W2993421702","https://openalex.org/W6698282354"],"related_works":["https://openalex.org/W2378211422","https://openalex.org/W4321353415","https://openalex.org/W2745001401","https://openalex.org/W2130974462","https://openalex.org/W2028665553","https://openalex.org/W2086519370","https://openalex.org/W4246352526","https://openalex.org/W2121910908","https://openalex.org/W915438175","https://openalex.org/W2393731464"],"abstract_inverted_index":{"The":[0],"ink":[1],"drop":[2],"spread":[3],"(IDS)":[4],"method":[5,69,87],"is":[6],"a":[7,27,83],"modeling":[8],"technique":[9],"developed":[10],"by":[11,54],"algorithmically":[12],"mimicking":[13],"the":[14,18,35,39,55,62,67,75,85,96,100,115,119],"information-handling":[15],"processes":[16],"of":[17,38,57,66,72,77,95,102,118],"human":[19],"brain,":[20],"and":[21,90,99],"it":[22],"has":[23],"been":[24],"proposed":[25],"as":[26,82],"new":[28],"soft":[29],"computing":[30],"paradigm.":[31],"This":[32,59,106],"study":[33,60,107],"investigates":[34],"real-time":[36,63,116],"performance":[37,117],"IDS":[40,68,86,120],"method.":[41,121],"Radial":[42],"basis":[43],"function":[44],"networks":[45,50],"(RBFNs)":[46],"are":[47,52],"artificial":[48],"neural":[49],"that":[51,71],"characterized":[53],"speed":[56],"learning.":[58],"compares":[61],"learning":[64,97],"capability":[65],"with":[70],"RBFNs.":[73],"In":[74],"approximation":[76],"five":[78],"different":[79],"functions":[80],"used":[81],"benchmark,":[84],"exhibits":[88],"stable":[89],"fast":[91],"convergence":[92],"in":[93],"terms":[94],"time":[98],"number":[101],"training":[103],"examples":[104],"used.":[105],"also":[108],"presents":[109],"an":[110],"effective":[111],"approach":[112],"to":[113],"enhance":[114]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
