{"id":"https://openalex.org/W7091376402","doi":"https://doi.org/10.1109/access.2025.3621850","title":"AI-Based Mobility Prediction Using Recurrent Neural Networks and Attention Mechanisms","display_name":"AI-Based Mobility Prediction Using Recurrent Neural Networks and Attention Mechanisms","publication_year":2025,"publication_date":"2025-01-01","ids":{"openalex":"https://openalex.org/W7091376402","doi":"https://doi.org/10.1109/access.2025.3621850"},"language":"en","primary_location":{"id":"doi:10.1109/access.2025.3621850","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2025.3621850","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1109/access.2025.3621850","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Mohammad Al-Hattab","orcid":"https://orcid.org/0000-0001-8359-7428"},"institutions":[{"id":"https://openalex.org/I161913731","display_name":"Al Ain University","ror":"https://ror.org/023abrt21","country_code":"AE","type":"education","lineage":["https://openalex.org/I161913731"]}],"countries":["AE"],"is_corresponding":false,"raw_author_name":"Mohammad Al-Hattab","raw_affiliation_strings":["College of Engineering, Al Ain University, Al Ain, United Arab Emirates"],"raw_orcid":"https://orcid.org/0000-0001-8359-7428","affiliations":[{"raw_affiliation_string":"College of Engineering, Al Ain University, Al Ain, United Arab Emirates","institution_ids":["https://openalex.org/I161913731"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Ayman Odeh","orcid":"https://orcid.org/0000-0002-3892-6488"},"institutions":[{"id":"https://openalex.org/I161913731","display_name":"Al Ain University","ror":"https://ror.org/023abrt21","country_code":"AE","type":"education","lineage":["https://openalex.org/I161913731"]}],"countries":["AE"],"is_corresponding":false,"raw_author_name":"Ayman Odeh","raw_affiliation_strings":["College of Engineering, Al Ain University, Al Ain, United Arab Emirates"],"raw_orcid":"https://orcid.org/0000-0002-3892-6488","affiliations":[{"raw_affiliation_string":"College of Engineering, Al Ain University, Al Ain, United Arab Emirates","institution_ids":["https://openalex.org/I161913731"]}]},{"author_position":"last","author":{"id":null,"display_name":"Maen Takruri","orcid":"https://orcid.org/0000-0001-9785-3920"},"institutions":[{"id":"https://openalex.org/I2803079837","display_name":"American University of the Middle East","ror":"https://ror.org/02gqgne03","country_code":"KW","type":"education","lineage":["https://openalex.org/I2803079837"]}],"countries":["KW"],"is_corresponding":false,"raw_author_name":"Maen Takruri","raw_affiliation_strings":["College of Engineering and Technology, American University of the Middle East, Egaila, Kuwait"],"raw_orcid":"https://orcid.org/0000-0001-9785-3920","affiliations":[{"raw_affiliation_string":"College of Engineering and Technology, American University of the Middle East, Egaila, Kuwait","institution_ids":["https://openalex.org/I2803079837"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":0.6148,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.73885499,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":97},"biblio":{"volume":"13","issue":null,"first_page":"179686","last_page":"179695"},"is_retracted":false,"is_paratext":false,"is_xpac":true,"primary_topic":{"id":"https://openalex.org/T11344","display_name":"Traffic Prediction and Management Techniques","score":0.9164999723434448,"subfield":{"id":"https://openalex.org/subfields/2215","display_name":"Building and Construction"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11344","display_name":"Traffic Prediction and Management Techniques","score":0.9164999723434448,"subfield":{"id":"https://openalex.org/subfields/2215","display_name":"Building and Construction"},"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/T11980","display_name":"Human Mobility and Location-Based Analysis","score":0.04600000008940697,"subfield":{"id":"https://openalex.org/subfields/3313","display_name":"Transportation"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T11942","display_name":"Transportation and Mobility Innovations","score":0.0066999997943639755,"subfield":{"id":"https://openalex.org/subfields/2203","display_name":"Automotive 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/recurrent-neural-network","display_name":"Recurrent neural network","score":0.715399980545044},{"id":"https://openalex.org/keywords/public-transport","display_name":"Public transport","score":0.5149999856948853},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.46790000796318054},{"id":"https://openalex.org/keywords/layer","display_name":"Layer (electronics)","score":0.41929998993873596},{"id":"https://openalex.org/keywords/intelligent-transportation-system","display_name":"Intelligent transportation system","score":0.3727000057697296},{"id":"https://openalex.org/keywords/data-modeling","display_name":"Data modeling","score":0.3693999946117401},{"id":"https://openalex.org/keywords/mobility-model","display_name":"Mobility model","score":0.3255000114440918}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8134999871253967},{"id":"https://openalex.org/C147168706","wikidata":"https://www.wikidata.org/wiki/Q1457734","display_name":"Recurrent neural network","level":3,"score":0.715399980545044},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5195000171661377},{"id":"https://openalex.org/C539828613","wikidata":"https://www.wikidata.org/wiki/Q178512","display_name":"Public transport","level":2,"score":0.5149999856948853},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.46790000796318054},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.44620001316070557},{"id":"https://openalex.org/C2779227376","wikidata":"https://www.wikidata.org/wiki/Q6505497","display_name":"Layer (electronics)","level":2,"score":0.41929998993873596},{"id":"https://openalex.org/C47796450","wikidata":"https://www.wikidata.org/wiki/Q508378","display_name":"Intelligent transportation system","level":2,"score":0.3727000057697296},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.3693999946117401},{"id":"https://openalex.org/C191485582","wikidata":"https://www.wikidata.org/wiki/Q6887309","display_name":"Mobility model","level":2,"score":0.3255000114440918},{"id":"https://openalex.org/C2778068325","wikidata":"https://www.wikidata.org/wiki/Q19892785","display_name":"Individual mobility","level":2,"score":0.31869998574256897},{"id":"https://openalex.org/C133488467","wikidata":"https://www.wikidata.org/wiki/Q6673524","display_name":"Long short term memory","level":4,"score":0.3183000087738037},{"id":"https://openalex.org/C2985695025","wikidata":"https://www.wikidata.org/wiki/Q4323994","display_name":"Road traffic","level":2,"score":0.311599999666214},{"id":"https://openalex.org/C45804977","wikidata":"https://www.wikidata.org/wiki/Q7239673","display_name":"Predictive modelling","level":2,"score":0.2775999903678894},{"id":"https://openalex.org/C2781361454","wikidata":"https://www.wikidata.org/wiki/Q7170607","display_name":"Personal mobility","level":2,"score":0.2721000015735626},{"id":"https://openalex.org/C114289077","wikidata":"https://www.wikidata.org/wiki/Q3284399","display_name":"Statistical model","level":2,"score":0.27090001106262207},{"id":"https://openalex.org/C52970973","wikidata":"https://www.wikidata.org/wiki/Q2497134","display_name":"Adaptive system","level":2,"score":0.263700008392334},{"id":"https://openalex.org/C79487989","wikidata":"https://www.wikidata.org/wiki/Q934680","display_name":"Vehicle dynamics","level":2,"score":0.2515000104904175}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2025.3621850","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2025.3621850","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:801122328bb14ea1b83544d90251b9a9","is_oa":true,"landing_page_url":"https://doaj.org/article/801122328bb14ea1b83544d90251b9a9","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","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":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 13, Pp 179686-179695 (2025)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2025.3621850","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2025.3621850","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[{"display_name":"Sustainable cities and communities","score":0.815536379814148,"id":"https://metadata.un.org/sdg/11"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Accurate":[0],"mobility":[1,80,111,151],"prediction":[2,90],"plays":[3],"a":[4,23],"pivotal":[5],"role":[6],"in":[7,87,129],"optimizing":[8],"transportation":[9],"systems,":[10],"supporting":[11],"urban":[12,150],"planning,":[13],"and":[14,44,76,108,138,147],"alleviating":[15],"traffic":[16,136],"congestion.":[17],"In":[18,92],"this":[19],"work,":[20],"we":[21],"present":[22],"novel":[24],"artificial":[25],"intelligence-based":[26],"approach":[27],"for":[28,126],"short-term":[29],"public":[30],"transport":[31,105,142],"demand":[32],"prediction,":[33],"utilizing":[34],"Recurrent":[35],"Neural":[36],"Networks":[37],"equipped":[38],"with":[39],"Long":[40],"Short-Term":[41],"Memory":[42],"units":[43],"attention":[45,61,116],"mechanisms.":[46],"This":[47],"hybrid":[48],"framework":[49],"is":[50,74],"designed":[51],"to":[52,64,103],"effectively":[53],"model":[54,96,123],"complex":[55],"temporal":[56],"dependencies":[57],"by":[58],"leveraging":[59],"the":[60,95,114,122],"mechanism\u2019s":[62],"capacity":[63],"highlight":[65],"informative":[66],"patterns":[67],"across":[68,140],"varying":[69],"time":[70],"scales.":[71],"Our":[72],"method":[73],"trained":[75],"validated":[77],"using":[78],"real-world":[79,127],"datasets,":[81],"consistently":[82],"outperforming":[83],"traditional":[84],"statistical":[85],"models":[86],"terms":[88],"of":[89],"accuracy.":[91],"our":[93],"experiments,":[94],"achieved":[97],"96.8%":[98],"accuracy,":[99],"demonstrating":[100],"its":[101],"potential":[102],"enhance":[104],"system":[106],"responsiveness":[107],"support":[109],"personalized":[110],"services.":[112],"Furthermore,":[113],"integrated":[115],"layer":[117],"provides":[118],"valuable":[119],"interpretability,":[120],"making":[121],"particularly":[124],"suitable":[125],"deployments":[128],"areas":[130],"such":[131],"as":[132],"dynamic":[133],"fleet":[134],"management,":[135],"monitoring,":[137],"integration":[139],"multimodal":[141],"networks,":[143],"thereby":[144],"promoting":[145],"smarter":[146],"more":[148],"adaptive":[149],"solutions.":[152]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-16T00:00:00"}