{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,30]],"date-time":"2026-06-30T16:02:27Z","timestamp":1782835347547,"version":"3.54.5"},"reference-count":50,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"22","license":[{"start":{"date-parts":[[2025,11,15]],"date-time":"2025-11-15T00:00:00Z","timestamp":1763164800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2025,11,15]],"date-time":"2025-11-15T00:00:00Z","timestamp":1763164800000},"content-version":"am","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2025,11,15]],"date-time":"2025-11-15T00:00:00Z","timestamp":1763164800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2025,11,15]],"date-time":"2025-11-15T00:00:00Z","timestamp":1763164800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"name":"NSF","award":["CNS-2319342"],"award-info":[{"award-number":["CNS-2319342"]}]},{"name":"NSF","award":["CNS-2319343"],"award-info":[{"award-number":["CNS-2319343"]}]},{"name":"Wireless Engineering Research and Education Center at Auburn University"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Internet Things J."],"published-print":{"date-parts":[[2025,11,15]]},"DOI":"10.1109\/jiot.2025.3604332","type":"journal-article","created":{"date-parts":[[2025,8,29]],"date-time":"2025-08-29T17:43:25Z","timestamp":1756489405000},"page":"48262-48276","source":"Crossref","is-referenced-by-count":4,"title":["FDALLM+: A Functional Data Analysis-Driven Large-Language Model Framework for Network Traffic Prediction"],"prefix":"10.1109","volume":"12","author":[{"ORCID":"https:\/\/orcid.org\/0009-0003-1894-136X","authenticated-orcid":false,"given":"Yujie","family":"Sun","sequence":"first","affiliation":[{"name":"Department of Electrical and Computer Engineering, Auburn University, Auburn, AL, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4759-8674","authenticated-orcid":false,"given":"Xuyu","family":"Wang","sequence":"additional","affiliation":[{"name":"Knight Foundation School of Computing and Information Sciences, Florida International University, Miami, FL, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6454-3210","authenticated-orcid":false,"given":"Guanqun","family":"Cao","sequence":"additional","affiliation":[{"name":"Department of Statistics and Probability, Michigan State University, East Lansing, MI, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7052-0007","authenticated-orcid":false,"given":"Shiwen","family":"Mao","sequence":"additional","affiliation":[{"name":"Department of Electrical and Computer Engineering, Auburn University, Auburn, AL, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1007\/s12544-015-0170-8"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/ICACCI.2017.8126198"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/comst.2025.3526606"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/mnet.2024.3470774"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/COMST.2024.3503680"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/MWC.005.2400019"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2024.findings-emnlp.201"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1145\/3719207"},{"key":"ref9","article-title":"Tiny time mixers (TTMs): Fast pre-trained models for enhanced zero\/few-shot forecasting of multivariate time series","author":"Ekambaram","year":"2024","journal-title":"arXiv:2401.03955"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/ICDEW61823.2024.00022"},{"key":"ref11","article-title":"Wav2Prompt: End-to-end speech prompt generation and tuning for LLM in zero and few-shot learning","author":"Deng","year":"2024","journal-title":"arXiv:2406.00522"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1093\/jamia\/ocae090"},{"key":"ref13","article-title":"Time-LLM: Time series forecasting by reprogramming large language models","author":"Jin","year":"2024","journal-title":"arXiv:2310.01728"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1145\/3589334.3645434"},{"key":"ref15","volume-title":"GPT-4 Technical Report","year":"2024"},{"key":"ref16","article-title":"Large language models are zero-shot time series forecasters","author":"Gruver","year":"2024","journal-title":"arXiv:2310.07820"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/tkde.2023.3342137"},{"key":"ref18","article-title":"TEMPO: Prompt-based generative pre-trained transformer for time series forecasting","author":"Cao","year":"2023","journal-title":"arXiv:2310.04948"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2024.findings-acl.466"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1146\/annurev-statistics-041715-033624"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1002\/wics.1638"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/ICC51166.2024.10623122"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1109\/ICC52391.2025.11161166"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1109\/ISCAS.2001.921273"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1109\/IVS.2011.5940418"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1631\/FITEE.1500381"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.3390\/s20030603"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1080\/03081060.2019.1622250"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1016\/j.future.2019.12.013"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.3390\/a17090398"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1109\/PIMRC.2018.8581000"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2022.108199"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1109\/TITS.2016.2643005"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1002\/bimj.202300363"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1002\/wics.70001"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1109\/TITS.2017.2706143"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1109\/MDM61037.2024.00025"},{"key":"ref38","article-title":"Strada-LLM: Graph LLM for traffic prediction","author":"Moghadas","year":"2024","journal-title":"arXiv:2410.20856"},{"key":"ref39","article-title":"TPLLM: A traffic prediction framework based on pretrained large language models","author":"Ren","year":"2024","journal-title":"arXiv:2403.02221"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1109\/TIV.2024.3418522"},{"key":"ref41","first-page":"309","article-title":"LLMs in short answer scoring: Limitations and promise of zero-shot and few-shot approaches","volume-title":"Proc. Workshop Innov. Use NLP Educ. Appl. (BEA)","author":"Chamieh"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1109\/COMST.2006.253272"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1145\/3701716.3717744"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2023.bionlp-1.7"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.1016\/j.commtr.2024.100150"},{"key":"ref46","doi-asserted-by":"crossref","DOI":"10.2139\/ssrn.4805901","volume-title":"Towards responsible and reliable traffic flow prediction with large language models.","author":"Guo","year":"2024"},{"key":"ref47","article-title":"Enhancing traffic prediction with textual data using large language models","author":"Huang","year":"2024","journal-title":"arXiv:2405.06719"},{"key":"ref48","first-page":"39135","article-title":"S2IP-LLM: Semantic space informed prompt learning with LLM for time series forecasting","volume-title":"Proc. ICML","author":"Pan"},{"key":"ref49","doi-asserted-by":"publisher","DOI":"10.1038\/sdata.2015.55"},{"key":"ref50","article-title":"Gemini: A family of highly capable multimodal models","author":"Anil","year":"2023","journal-title":"arXiv:2312.11805"}],"container-title":["IEEE Internet of Things Journal"],"original-title":[],"link":[{"URL":"https:\/\/ieeexplore.ieee.org\/ielam\/6488907\/11231115\/11145078-aam.pdf","content-type":"application\/pdf","content-version":"am","intended-application":"syndication"},{"URL":"http:\/\/xplorestaging.ieee.org\/ielx8\/6488907\/11231115\/11145078.pdf?arnumber=11145078","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,11,7]],"date-time":"2025-11-07T18:13:09Z","timestamp":1762539189000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/11145078\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,11,15]]},"references-count":50,"journal-issue":{"issue":"22"},"URL":"https:\/\/doi.org\/10.1109\/jiot.2025.3604332","relation":{},"ISSN":["2327-4662","2372-2541"],"issn-type":[{"value":"2327-4662","type":"electronic"},{"value":"2372-2541","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,11,15]]}}}