{"id":"https://openalex.org/W4402351908","doi":"https://doi.org/10.1109/ijcnn60899.2024.10650945","title":"Designing Network Topologies of Multiple Reservoir Echo State Networks: A Genetic Algorithm Based Approach","display_name":"Designing Network Topologies of Multiple Reservoir Echo State Networks: A Genetic Algorithm Based Approach","publication_year":2024,"publication_date":"2024-06-30","ids":{"openalex":"https://openalex.org/W4402351908","doi":"https://doi.org/10.1109/ijcnn60899.2024.10650945"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn60899.2024.10650945","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn60899.2024.10650945","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 International Joint Conference on Neural Networks (IJCNN)","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/A5069278632","display_name":"Ziqiang Li","orcid":"https://orcid.org/0000-0002-7208-9003"},"institutions":[{"id":"https://openalex.org/I74801974","display_name":"The University of Tokyo","ror":"https://ror.org/057zh3y96","country_code":"JP","type":"education","lineage":["https://openalex.org/I74801974"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Ziqiang Li","raw_affiliation_strings":["The University of Tokyo,International Research Center for Neurointelligence,Tokyo,Japan,113-0033"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The University of Tokyo,International Research Center for Neurointelligence,Tokyo,Japan,113-0033","institution_ids":["https://openalex.org/I74801974"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5065197780","display_name":"Kantaro Fujiwara","orcid":"https://orcid.org/0000-0001-8114-7837"},"institutions":[{"id":"https://openalex.org/I74801974","display_name":"The University of Tokyo","ror":"https://ror.org/057zh3y96","country_code":"JP","type":"education","lineage":["https://openalex.org/I74801974"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Kantaro Fujiwara","raw_affiliation_strings":["The University of Tokyo,International Research Center for Neurointelligence,Tokyo,Japan,113-0033"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The University of Tokyo,International Research Center for Neurointelligence,Tokyo,Japan,113-0033","institution_ids":["https://openalex.org/I74801974"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5025420478","display_name":"Gouhei Tanaka","orcid":"https://orcid.org/0000-0002-6223-4406"},"institutions":[{"id":"https://openalex.org/I197274945","display_name":"Nagoya Institute of Technology","ror":"https://ror.org/055yf1005","country_code":"JP","type":"education","lineage":["https://openalex.org/I197274945"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Gouhei Tanaka","raw_affiliation_strings":["Nagoya Institute of Technology,Graduate School of Engineering,Department of Computer Science,Nagoya,Japan,466-8555"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Nagoya Institute of Technology,Graduate School of Engineering,Department of Computer Science,Nagoya,Japan,466-8555","institution_ids":["https://openalex.org/I197274945"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"9"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12611","display_name":"Neural Networks and Reservoir Computing","score":1.0,"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/T12611","display_name":"Neural Networks and Reservoir Computing","score":1.0,"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/T10502","display_name":"Advanced Memory and Neural Computing","score":0.9976999759674072,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T13362","display_name":"Slime Mold and Myxomycetes Research","score":0.9861000180244446,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/network-topology","display_name":"Network topology","score":0.8311780095100403},{"id":"https://openalex.org/keywords/echo","display_name":"Echo (communications protocol)","score":0.7470463514328003},{"id":"https://openalex.org/keywords/echo-state-network","display_name":"Echo state network","score":0.6933640837669373},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6760008335113525},{"id":"https://openalex.org/keywords/reservoir-computing","display_name":"Reservoir computing","score":0.6540508270263672},{"id":"https://openalex.org/keywords/genetic-algorithm","display_name":"Genetic algorithm","score":0.5835028290748596},{"id":"https://openalex.org/keywords/state","display_name":"State (computer science)","score":0.47142714262008667},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.35254454612731934},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.2858874499797821},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.24672523140907288},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.13896721601486206},{"id":"https://openalex.org/keywords/recurrent-neural-network","display_name":"Recurrent neural network","score":0.11825203895568848},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.10057064890861511}],"concepts":[{"id":"https://openalex.org/C199845137","wikidata":"https://www.wikidata.org/wiki/Q145490","display_name":"Network topology","level":2,"score":0.8311780095100403},{"id":"https://openalex.org/C2779426996","wikidata":"https://www.wikidata.org/wiki/Q18389128","display_name":"Echo (communications protocol)","level":2,"score":0.7470463514328003},{"id":"https://openalex.org/C172025690","wikidata":"https://www.wikidata.org/wiki/Q5332763","display_name":"Echo state network","level":4,"score":0.6933640837669373},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6760008335113525},{"id":"https://openalex.org/C135796866","wikidata":"https://www.wikidata.org/wiki/Q7315328","display_name":"Reservoir computing","level":4,"score":0.6540508270263672},{"id":"https://openalex.org/C8880873","wikidata":"https://www.wikidata.org/wiki/Q187787","display_name":"Genetic algorithm","level":2,"score":0.5835028290748596},{"id":"https://openalex.org/C48103436","wikidata":"https://www.wikidata.org/wiki/Q599031","display_name":"State (computer science)","level":2,"score":0.47142714262008667},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.35254454612731934},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.2858874499797821},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.24672523140907288},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.13896721601486206},{"id":"https://openalex.org/C147168706","wikidata":"https://www.wikidata.org/wiki/Q1457734","display_name":"Recurrent neural network","level":3,"score":0.11825203895568848},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.10057064890861511}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ijcnn60899.2024.10650945","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn60899.2024.10650945","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G530108296","display_name":"Mathematical Foundations of Brain-Inspired Computing Based on Diversity","funder_award_id":"23K28154","funder_id":"https://openalex.org/F4320334764","funder_display_name":"Japan Society for the Promotion of Science"}],"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":28,"referenced_works":["https://openalex.org/W55405823","https://openalex.org/W1517907695","https://openalex.org/W1579694346","https://openalex.org/W2001263627","https://openalex.org/W2011301426","https://openalex.org/W2101234009","https://openalex.org/W2118706537","https://openalex.org/W2121402967","https://openalex.org/W2132022337","https://openalex.org/W2171865010","https://openalex.org/W2177933918","https://openalex.org/W2608997467","https://openalex.org/W2781626870","https://openalex.org/W2885420314","https://openalex.org/W2928236413","https://openalex.org/W2946547492","https://openalex.org/W3038427506","https://openalex.org/W3094704314","https://openalex.org/W3140759899","https://openalex.org/W3171078540","https://openalex.org/W3196296792","https://openalex.org/W4226400506","https://openalex.org/W4295312788","https://openalex.org/W4312889804","https://openalex.org/W4317356199","https://openalex.org/W4386938263","https://openalex.org/W6697721707","https://openalex.org/W6766978945"],"related_works":["https://openalex.org/W57315087","https://openalex.org/W2010974764","https://openalex.org/W4386848428","https://openalex.org/W4205631599","https://openalex.org/W2021379535","https://openalex.org/W2020067398","https://openalex.org/W2967225774","https://openalex.org/W4292972806","https://openalex.org/W2137783571","https://openalex.org/W4390782828"],"abstract_inverted_index":{"In":[0,62],"Reservoir":[1,5],"Computing":[2],"methods,":[3],"Multiple":[4],"Echo":[6,23],"State":[7,24],"Networks":[8],"(MRESNs)":[9],"with":[10,123],"multiple":[11],"reservoir":[12,99],"encoders":[13],"can":[14],"have":[15,36,134],"better":[16,135],"computational":[17,73,136],"abilities":[18,137],"than":[19,138],"the":[20,48,72,80,83,98,124,139],"standard":[21],"single":[22],"Network":[25],"on":[26,56,79,143],"many":[27],"time-series":[28,146],"processing":[29,60,147],"tasks.":[30],"However,":[31],"several":[32],"hand-crafted":[33],"network":[34,100,116,127],"topologies":[35,128],"been":[37],"widely":[38],"adopted":[39],"for":[40],"building":[41],"most":[42],"existing":[43],"MRESN-based":[44],"models,":[45],"which":[46],"limits":[47],"potential":[49],"of":[50,53,75,82,102],"their":[51],"performance":[52],"an":[54,76,103],"MRESN":[55,77,104,141],"a":[57,67,93,107,114],"given":[58],"temporal":[59],"task.":[61],"this":[63,89],"work,":[64],"we":[65,91],"propose":[66],"new":[68],"method":[69,95],"to":[70,96,112],"improve":[71],"ability":[74],"based":[78],"perspective":[81],"neural":[84],"architecture":[85],"search.":[86],"To":[87],"accomplish":[88],"goal,":[90],"use":[92],"binary-encoding":[94],"represent":[97],"topology":[101],"and":[105],"develop":[106],"Genetic":[108],"Algorithm":[109],"(GA)-based":[110],"approach":[111,133],"seek":[113],"desirable":[115],"topology.":[117],"Experimental":[118],"results":[119],"show":[120],"that":[121],"MRESNs":[122],"corresponding":[125],"optimal":[126],"searched":[129],"by":[130],"our":[131],"proposed":[132],"baseline":[140],"models":[142],"four":[144],"benchmark":[145],"datasets.":[148]},"counts_by_year":[{"year":2025,"cited_by_count":2}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}