{"id":"https://openalex.org/W4413319051","doi":"https://doi.org/10.1109/tnnls.2025.3596244","title":"Bidirectional Multiscale Efficient Dilated Convolutional Recurrent Neural Network Improved by Swarm Intelligence Optimization","display_name":"Bidirectional Multiscale Efficient Dilated Convolutional Recurrent Neural Network Improved by Swarm Intelligence Optimization","publication_year":2025,"publication_date":"2025-08-19","ids":{"openalex":"https://openalex.org/W4413319051","doi":"https://doi.org/10.1109/tnnls.2025.3596244","pmid":"https://pubmed.ncbi.nlm.nih.gov/40828718"},"language":"en","primary_location":{"id":"doi:10.1109/tnnls.2025.3596244","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2025.3596244","pdf_url":null,"source":{"id":"https://openalex.org/S4210175523","display_name":"IEEE Transactions on Neural Networks and Learning Systems","issn_l":"2162-237X","issn":["2162-237X","2162-2388"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Neural Networks and Learning Systems","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"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/A5022385306","display_name":"Qinwei Fan","orcid":"https://orcid.org/0000-0002-1017-3496"},"institutions":[{"id":"https://openalex.org/I37987034","display_name":"Guangzhou University","ror":"https://ror.org/05ar8rn06","country_code":"CN","type":"education","lineage":["https://openalex.org/I37987034"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qinwei Fan","raw_affiliation_strings":["School of Mathematics and Information Science, Guangzhou University, Guangzhou, China"],"raw_orcid":"https://orcid.org/0000-0002-1017-3496","affiliations":[{"raw_affiliation_string":"School of Mathematics and Information Science, Guangzhou University, Guangzhou, China","institution_ids":["https://openalex.org/I37987034"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Shuai Zhao","orcid":"https://orcid.org/0009-0005-8173-2864"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shuai Zhao","raw_affiliation_strings":["School of Mathematics and Statistics, Xidian University, Xi&#x2019;an, China"],"raw_orcid":"https://orcid.org/0009-0005-8173-2864","affiliations":[{"raw_affiliation_string":"School of Mathematics and Statistics, Xidian University, Xi&#x2019;an, China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5015925094","display_name":"Jacek M. \u017burada","orcid":"https://orcid.org/0000-0001-6622-534X"},"institutions":[{"id":"https://openalex.org/I142740786","display_name":"University of Louisville","ror":"https://ror.org/01ckdn478","country_code":"US","type":"education","lineage":["https://openalex.org/I142740786"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jacek M. Zurada","raw_affiliation_strings":["Department of Electrical and Computer Engineering, University of Louisville, Louisville, KY, USA"],"raw_orcid":"https://orcid.org/0000-0001-6622-534X","affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, University of Louisville, Louisville, KY, USA","institution_ids":["https://openalex.org/I142740786"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5074290686","display_name":"Tingwen Huang","orcid":"https://orcid.org/0000-0001-9610-846X"},"institutions":[{"id":"https://openalex.org/I180726961","display_name":"Shenzhen University","ror":"https://ror.org/01vy4gh70","country_code":"CN","type":"education","lineage":["https://openalex.org/I180726961"]},{"id":"https://openalex.org/I4210152380","display_name":"Shenzhen Technology University","ror":"https://ror.org/04qzpec27","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210152380"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tingwen Huang","raw_affiliation_strings":["Faculty of Computer Science and Control Engineering, Shenzhen University of Advanced Technology, Shenzhen, China"],"raw_orcid":"https://orcid.org/0000-0001-9610-846X","affiliations":[{"raw_affiliation_string":"Faculty of Computer Science and Control Engineering, Shenzhen University of Advanced Technology, Shenzhen, China","institution_ids":["https://openalex.org/I4210152380","https://openalex.org/I180726961"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5079389901","display_name":"Xiaolong Qin","orcid":"https://orcid.org/0000-0002-3381-8525"},"institutions":[{"id":"https://openalex.org/I163151501","display_name":"Hangzhou Normal University","ror":"https://ror.org/014v1mr15","country_code":"CN","type":"education","lineage":["https://openalex.org/I163151501"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaolong Qin","raw_affiliation_strings":["Department of Mathematics, Hangzhou Normal University, Hangzhou, China"],"raw_orcid":"https://orcid.org/0000-0002-3381-8525","affiliations":[{"raw_affiliation_string":"Department of Mathematics, Hangzhou Normal University, Hangzhou, China","institution_ids":["https://openalex.org/I163151501"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101551923","display_name":"Rui Zhang","orcid":"https://orcid.org/0000-0001-9547-2585"},"institutions":[{"id":"https://openalex.org/I37802460","display_name":"Northwest University","ror":"https://ror.org/00z3td547","country_code":"CN","type":"education","lineage":["https://openalex.org/I37802460"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Rui Zhang","raw_affiliation_strings":["Medical Big Data Research Center, Northwest University, Xi&#x2019;an, China"],"raw_orcid":"https://orcid.org/0000-0001-9547-2585","affiliations":[{"raw_affiliation_string":"Medical Big Data Research Center, Northwest University, Xi&#x2019;an, China","institution_ids":["https://openalex.org/I37802460"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":7,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.10457067,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"36","issue":"12","first_page":"20009","last_page":"20023"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10320","display_name":"Neural Networks and Applications","score":0.9104999899864197,"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":0.9104999899864197,"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/computer-science","display_name":"Computer science","score":0.6872779726982117},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6287685632705688},{"id":"https://openalex.org/keywords/swarm-intelligence","display_name":"Swarm intelligence","score":0.624786376953125},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5033618807792664},{"id":"https://openalex.org/keywords/recurrent-neural-network","display_name":"Recurrent neural network","score":0.49733760952949524},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.41712796688079834},{"id":"https://openalex.org/keywords/particle-swarm-optimization","display_name":"Particle swarm optimization","score":0.38036102056503296},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.2782135009765625}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6872779726982117},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6287685632705688},{"id":"https://openalex.org/C119487961","wikidata":"https://www.wikidata.org/wiki/Q863960","display_name":"Swarm intelligence","level":3,"score":0.624786376953125},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5033618807792664},{"id":"https://openalex.org/C147168706","wikidata":"https://www.wikidata.org/wiki/Q1457734","display_name":"Recurrent neural network","level":3,"score":0.49733760952949524},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.41712796688079834},{"id":"https://openalex.org/C85617194","wikidata":"https://www.wikidata.org/wiki/Q2072794","display_name":"Particle swarm optimization","level":2,"score":0.38036102056503296},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2782135009765625}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tnnls.2025.3596244","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2025.3596244","pdf_url":null,"source":{"id":"https://openalex.org/S4210175523","display_name":"IEEE Transactions on Neural Networks and Learning Systems","issn_l":"2162-237X","issn":["2162-237X","2162-2388"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Neural Networks and Learning Systems","raw_type":"journal-article"},{"id":"pmid:40828718","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/40828718","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE transactions on neural networks and learning systems","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1623747056","display_name":null,"funder_award_id":"12471482","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G2770850836","display_name":null,"funder_award_id":"12271117","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5606537135","display_name":null,"funder_award_id":"12031003","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G6775529807","display_name":"Rolandic\u766b\u75eb\u795e\u7ecf\u8ba1\u7b97\u6a21\u578b\u53ca\u5176\u5728\u53d1\u4f5c\u9884\u6d4b\u4e0e\u6291\u5236\u4e2d\u7684\u5e94\u7528\u7814\u7a76","funder_award_id":"12071369","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":44,"referenced_works":["https://openalex.org/W2183341477","https://openalex.org/W2604847698","https://openalex.org/W2774942496","https://openalex.org/W2962850830","https://openalex.org/W2998553334","https://openalex.org/W3121003328","https://openalex.org/W3130777809","https://openalex.org/W3133735015","https://openalex.org/W3178756396","https://openalex.org/W3198399144","https://openalex.org/W4221048209","https://openalex.org/W4292059111","https://openalex.org/W4309573071","https://openalex.org/W4320520334","https://openalex.org/W4377089044","https://openalex.org/W4382999145","https://openalex.org/W4385338584","https://openalex.org/W4385945212","https://openalex.org/W4387717436","https://openalex.org/W4388019149","https://openalex.org/W4388283607","https://openalex.org/W4388520081","https://openalex.org/W4388782207","https://openalex.org/W4389169325","https://openalex.org/W4389179403","https://openalex.org/W4389665145","https://openalex.org/W4390871606","https://openalex.org/W4391004165","https://openalex.org/W4391020334","https://openalex.org/W4391206025","https://openalex.org/W4391507190","https://openalex.org/W4392728778","https://openalex.org/W4393257647","https://openalex.org/W4399534188","https://openalex.org/W4400934186","https://openalex.org/W4402669404","https://openalex.org/W4402979470","https://openalex.org/W4405177046","https://openalex.org/W4406062401","https://openalex.org/W4406133538","https://openalex.org/W4406309539","https://openalex.org/W4406939211","https://openalex.org/W4407089331","https://openalex.org/W4407450036"],"related_works":["https://openalex.org/W4225394202","https://openalex.org/W4298287631","https://openalex.org/W2953061907","https://openalex.org/W1847088711","https://openalex.org/W3036642985","https://openalex.org/W3032952384","https://openalex.org/W3017902212","https://openalex.org/W2964335273","https://openalex.org/W2982145560","https://openalex.org/W2070977815"],"abstract_inverted_index":{"In":[0],"recent":[1],"years,":[2],"bidirectional":[3,53,131],"convolutional":[4,54,141],"recurrent":[5,133],"neural":[6],"networks":[7],"(RNNs)":[8],"have":[9],"made":[10],"significant":[11],"breakthroughs":[12],"in":[13,194],"addressing":[14],"a":[15,52,71,158,164],"wide":[16],"range":[17],"of":[18,31,105,125,147,183,190],"challenging":[19],"problems":[20],"related":[21],"to":[22,65,80,96,114],"time":[23],"series":[24],"and":[25,50,84,120,155,186],"prediction":[26,68],"applications.":[27],"However,":[28],"the":[29,32,38,58,98,103,106,122,126,130,140,145,181,184,188],"performance":[30],"models":[33],"is":[34],"highly":[35],"dependent":[36],"on":[37,57,177],"hyperparameters":[39],"chosen.":[40],"Hence,":[41],"we":[42],"propose":[43],"an":[44],"automatic":[45],"method":[46,89],"for":[47,172],"hyperparameter":[48,149,173],"optimization":[49,62,192],"apply":[51],"RNN":[55],"based":[56],"improved":[59],"swarm":[60],"intelligence":[61],"(sparrow":[63],"search)":[64],"solve":[66],"regression":[67],"problems.":[69],"Specifically,":[70],"parallel":[72,111],"multiscale":[73,112],"dilated":[74],"convolution":[75,91],"(PMDC)":[76],"module":[77],"was":[78,170],"designed":[79],"capture":[81],"both":[82],"local":[83],"global":[85],"spatial":[86],"correlations.":[87],"This":[88],"utilizes":[90],"with":[92,163],"different":[93,118],"dilation":[94],"rates":[95],"expand":[97],"receptive":[99],"field":[100],"without":[101],"increasing":[102],"complexity":[104],"model.":[107],"Meanwhile,":[108],"it":[109],"integrates":[110],"structures":[113],"extract":[115],"features":[116],"at":[117],"scales":[119],"enhance":[121],"model's":[123],"understanding":[124],"input":[127],"data.":[128],"Then,":[129],"gated":[132],"units":[134],"(BGRUs)":[135],"learn":[136],"temporal":[137],"information":[138],"from":[139],"features.":[142],"To":[143],"address":[144],"limitations":[146],"empirical":[148],"selection,":[150],"such":[151],"as":[152],"slow":[153],"training":[154],"low":[156],"efficiency,":[157],"novel":[159],"PMDC-BGRU":[160],"model":[161,196],"integrated":[162],"pretrained":[165],"sparrow":[166],"search":[167],"algorithm":[168,185],"(SSA)":[169],"proposed":[171],"optimization.":[174,198],"Finally,":[175],"experiments":[176],"multiple":[178],"datasets":[179],"verified":[180],"superiority":[182],"explained":[187],"flexibility":[189],"intelligent":[191],"algorithms":[193],"solving":[195],"parameter":[197]},"counts_by_year":[],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}
