{"id":"https://openalex.org/W1600096919","doi":"https://doi.org/10.1109/ijcnn.2005.1555952","title":"A new N-parallel updating method of the Hopfield-type neural network for N-queens problem","display_name":"A new N-parallel updating method of the Hopfield-type neural network for N-queens problem","publication_year":2006,"publication_date":"2006-01-05","ids":{"openalex":"https://openalex.org/W1600096919","doi":"https://doi.org/10.1109/ijcnn.2005.1555952","mag":"1600096919"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn.2005.1555952","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2005.1555952","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":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5058126062","display_name":"Thong Le","orcid":null},"institutions":[{"id":"https://openalex.org/I119487337","display_name":"Yaskawa Electric (Japan)","ror":"https://ror.org/037qwc103","country_code":"JP","type":"company","lineage":["https://openalex.org/I119487337"]}],"countries":["JP"],"is_corresponding":true,"raw_author_name":"T.-N. Le","raw_affiliation_strings":["Yaskawa Information Systems Company Limited, Kitakyushu, Japan"],"affiliations":[{"raw_affiliation_string":"Yaskawa Information Systems Company Limited, Kitakyushu, Japan","institution_ids":["https://openalex.org/I119487337"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5042912660","display_name":"Cong\u2010Kha Pham","orcid":"https://orcid.org/0000-0001-5255-4919"},"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":"C.-K. Pham","raw_affiliation_strings":["University of Electro-Communications, Tokyo, Japan"],"affiliations":[{"raw_affiliation_string":"University of Electro-Communications, Tokyo, Japan","institution_ids":["https://openalex.org/I20529979"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5058126062"],"corresponding_institution_ids":["https://openalex.org/I119487337"],"apc_list":null,"apc_paid":null,"fwci":0.8158,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.69271198,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"2","issue":null,"first_page":"788","last_page":"791"},"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/T13579","display_name":"Image and Video Stabilization","score":0.9843000173568726,"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"}},{"id":"https://openalex.org/T11447","display_name":"Blind Source Separation Techniques","score":0.9789000153541565,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/hopfield-network","display_name":"Hopfield network","score":0.7469509840011597},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7090027928352356},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.7009502053260803},{"id":"https://openalex.org/keywords/type","display_name":"Type (biology)","score":0.4801168441772461},{"id":"https://openalex.org/keywords/types-of-artificial-neural-networks","display_name":"Types of artificial neural networks","score":0.4292127788066864},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.34156447649002075},{"id":"https://openalex.org/keywords/recurrent-neural-network","display_name":"Recurrent neural network","score":0.2979987859725952},{"id":"https://openalex.org/keywords/biology","display_name":"Biology","score":0.04926776885986328}],"concepts":[{"id":"https://openalex.org/C46421273","wikidata":"https://www.wikidata.org/wiki/Q1407668","display_name":"Hopfield network","level":3,"score":0.7469509840011597},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7090027928352356},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.7009502053260803},{"id":"https://openalex.org/C2777299769","wikidata":"https://www.wikidata.org/wiki/Q3707858","display_name":"Type (biology)","level":2,"score":0.4801168441772461},{"id":"https://openalex.org/C177973122","wikidata":"https://www.wikidata.org/wiki/Q7860946","display_name":"Types of artificial neural networks","level":4,"score":0.4292127788066864},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.34156447649002075},{"id":"https://openalex.org/C147168706","wikidata":"https://www.wikidata.org/wiki/Q1457734","display_name":"Recurrent neural network","level":3,"score":0.2979987859725952},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.04926776885986328},{"id":"https://openalex.org/C18903297","wikidata":"https://www.wikidata.org/wiki/Q7150","display_name":"Ecology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ijcnn.2005.1555952","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2005.1555952","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"}],"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/W1507402377","https://openalex.org/W1989122938","https://openalex.org/W2013446962","https://openalex.org/W2055010035","https://openalex.org/W2069559839","https://openalex.org/W2121890596","https://openalex.org/W2158009048","https://openalex.org/W2902040463","https://openalex.org/W3080781218","https://openalex.org/W3192793709","https://openalex.org/W4233200259","https://openalex.org/W4235434177","https://openalex.org/W4245926088","https://openalex.org/W6630507708","https://openalex.org/W6757100947","https://openalex.org/W6781846430"],"related_works":["https://openalex.org/W2735720847","https://openalex.org/W2148784397","https://openalex.org/W2610359609","https://openalex.org/W1583137156","https://openalex.org/W2124776483","https://openalex.org/W2387061801","https://openalex.org/W1521456446","https://openalex.org/W2440925417","https://openalex.org/W2367122357","https://openalex.org/W1497095139"],"abstract_inverted_index":{"In":[0,67],"the":[1,7,78,96,108,116],"previous":[2,117],"N-parallel":[3,74],"updating":[4,75],"methods":[5],"of":[6,26,52,57,77,107],"Hopfield-type":[8,79],"neural":[9,80],"network":[10,81],"for":[11,82,91],"N-queens":[12,83],"problem,":[13,84],"N/spl":[14],"times/N":[15],"neurons":[16,28,93],"have":[17],"been":[18,100],"grouped":[19],"into":[20],"N":[21,27,92],"groups.":[22],"Each":[23],"group":[24,98],"composed":[25,94],"which":[29],"are":[30],"located":[31],"in":[32,39,54,85,95],"a":[33,40,62,72,87,103,112],"same":[34,41,97],"horizontal":[35],"line":[36],"(column)":[37],"or":[38],"diagonal":[42],"line.":[43],"However,":[44],"these":[45],"method":[46,76,90,110],"did":[47],"not":[48],"give":[49],"convergence":[50,64],"results":[51,106],"100%":[53],"all":[55],"size":[56],"N.":[58],"Also,":[59],"they":[60],"required":[61],"large":[63],"time":[65],"steps.":[66],"our":[68],"work,":[69],"we":[70],"propose":[71],"new":[73,88],"which,":[86],"grouping":[89],"has":[99],"adopted.":[101],"As":[102],"result,":[104],"simulation":[105],"proposed":[109],"show":[111],"best":[113],"performance":[114],"than":[115],"generally.":[118]},"counts_by_year":[{"year":2022,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
