{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,30]],"date-time":"2026-10-30T01:05:31Z","timestamp":1793322331759,"version":"4.5.0"},"reference-count":70,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2026,11,1]],"date-time":"2026-11-01T00:00:00Z","timestamp":1793491200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2026,11,1]],"date-time":"2026-11-01T00:00:00Z","timestamp":1793491200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2026,11,1]],"date-time":"2026-11-01T00:00:00Z","timestamp":1793491200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-017"},{"start":{"date-parts":[[2026,11,1]],"date-time":"2026-11-01T00:00:00Z","timestamp":1793491200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"},{"start":{"date-parts":[[2026,11,1]],"date-time":"2026-11-01T00:00:00Z","timestamp":1793491200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-012"},{"start":{"date-parts":[[2026,11,1]],"date-time":"2026-11-01T00:00:00Z","timestamp":1793491200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2026,11,1]],"date-time":"2026-11-01T00:00:00Z","timestamp":1793491200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-004"}],"funder":[{"DOI":"10.13039\/501100012245","name":"Science and Technology Planning Project of Guangdong Province","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100012245","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Expert Systems with Applications"],"published-print":{"date-parts":[[2026,11]]},"DOI":"10.1016\/j.eswa.2026.132913","type":"journal-article","created":{"date-parts":[[2026,5,23]],"date-time":"2026-05-23T15:44:01Z","timestamp":1779551041000},"page":"132913","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":2,"special_numbering":"C","title":["Non-stationary diffusion for trajectory generation incorporating turning choice behavior and geographic attention U-Net"],"prefix":"10.1016","volume":"329","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-2213-1971","authenticated-orcid":false,"given":"Kunxiang","family":"Deng","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3278-0924","authenticated-orcid":false,"given":"Dongran","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0002-9917-1565","authenticated-orcid":false,"given":"Xinhao","family":"Liang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0000-0766-9012","authenticated-orcid":false,"given":"Keyu","family":"Hao","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3062-4140","authenticated-orcid":false,"given":"Jun","family":"Li","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"78","reference":[{"issue":"1","key":"10.1016\/j.eswa.2026.132913_bib0001","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/S0968-090X(00)00002-4","article-title":"Investigating the learning effects of route guidance and traffic advisories on route choice behavior","volume":"9","author":"Adler","year":"2001","journal-title":"Transportation Research Part C: Emerging Technologies"},{"issue":"1\/2","key":"10.1016\/j.eswa.2026.132913_bib0002","doi-asserted-by":"crossref","first-page":"181","DOI":"10.2307\/2333823","article-title":"A change in level of a non-stationary time series","volume":"52","author":"Box","year":"1965","journal-title":"Biometrika"},{"key":"10.1016\/j.eswa.2026.132913_bib0003","doi-asserted-by":"crossref","first-page":"332","DOI":"10.1016\/j.neucom.2020.03.120","article-title":"Trajvae: A variational autoencoder model for trajectory generation","volume":"428","author":"Chen","year":"2021","journal-title":"Neurocomputing"},{"issue":"10","key":"10.1016\/j.eswa.2026.132913_bib0004","doi-asserted-by":"crossref","first-page":"1053","DOI":"10.1080\/0740817X.2014.999180","article-title":"Time series forecasting for nonlinear and non-stationary processes: A review and comparative study","volume":"47","author":"Cheng","year":"2015","journal-title":"Iie Transactions"},{"key":"10.1016\/j.eswa.2026.132913_bib0005","doi-asserted-by":"crossref","DOI":"10.1016\/j.aei.2025.103798","article-title":"MetaGNSDformer: Meta-learning enhanced gated non-stationary informer with frequency-aware attention for point-interval remaining useful life prediction of lithium-ion batteries","volume":"69","author":"Cheng","year":"2026","journal-title":"Advanced Engineering Informatics"},{"key":"10.1016\/j.eswa.2026.132913_bib0006","doi-asserted-by":"crossref","DOI":"10.1016\/j.trc.2021.103091","article-title":"TrajGAIL: Generating urban vehicle trajectories using generative adversarial imitation learning","volume":"128","author":"Choi","year":"2021","journal-title":"Transportation Research Part C: Emerging Technologies"},{"key":"10.1016\/j.eswa.2026.132913_bib0007","series-title":"Proceedings of the 31st ACM SIGKDD conference on knowledge discovery and data mining v. 2","first-page":"463","article-title":"Marionette: Fine-grained conditional generative modeling of spatiotemporal human trajectory data beyond imitation","author":"Deng","year":"2025"},{"key":"10.1016\/j.eswa.2026.132913_bib0008","doi-asserted-by":"crossref","DOI":"10.1016\/j.aei.2025.104063","article-title":"Enhancing trajectory imputation distributional consistency via spatio-temporal conditional diffusion approach","volume":"69","author":"Deng","year":"2026","journal-title":"Advanced Engineering Informatics"},{"key":"10.1016\/j.eswa.2026.132913_bib0009","doi-asserted-by":"crossref","DOI":"10.1016\/j.asoc.2025.113618","article-title":"Glformer: Global-local spatio-temporal graph fusion transformer network for traffic flow prediction","volume":"183","author":"Deng","year":"2025","journal-title":"Applied Soft Computing"},{"key":"10.1016\/j.eswa.2026.132913_bib0010","first-page":"8780","article-title":"Diffusion models beat GANs on image synthesis","volume":"34","author":"Dhariwal","year":"2021","journal-title":"Advances in Neural Information Processing Systems"},{"key":"10.1016\/j.eswa.2026.132913_bib0011","series-title":"Proceedings of the 30th ACM international conference on information & knowledge management","first-page":"402","article-title":"Adarnn: Adaptive learning and forecasting of time series","author":"Du","year":"2021"},{"issue":"5","key":"10.1016\/j.eswa.2026.132913_bib0012","doi-asserted-by":"crossref","first-page":"771","DOI":"10.1109\/JPROC.2004.826605","article-title":"Computational intelligence methods for rule-based data understanding","volume":"92","author":"Duch","year":"2004","journal-title":"Proceedings of the IEEE"},{"key":"10.1016\/j.eswa.2026.132913_bib0013","series-title":"Proceedings of the first workshop on measurement, privacy, and mobility","first-page":"1","article-title":"Next place prediction using mobility Markov chains","author":"Gambs","year":"2012"},{"key":"10.1016\/j.eswa.2026.132913_bib0014","series-title":"Proceedings of the 22nd ACM SIGKDD international conference on knowledge discovery and data mining","first-page":"855","article-title":"node2vec: Scalable feature learning for networks","author":"Grover","year":"2016"},{"key":"10.1016\/j.eswa.2026.132913_bib0015","doi-asserted-by":"crossref","DOI":"10.1016\/j.aei.2024.102742","article-title":"A behavioral conditional diffusion probabilistic model for human motion modeling in multi-action mixed human-robot collaboration","volume":"62","author":"Gui","year":"2024","journal-title":"Advanced Engineering Informatics"},{"key":"10.1016\/j.eswa.2026.132913_bib0016","doi-asserted-by":"crossref","DOI":"10.1016\/j.aei.2024.102805","article-title":"Technological life-cycle analysis of ultra-precision machining technology: Forecasting perspective directions and tracking the critical transitions with evolution","volume":"62","author":"Guo","year":"2024","journal-title":"Advanced Engineering Informatics"},{"key":"10.1016\/j.eswa.2026.132913_bib0017","series-title":"Classification and regression diffusion models and tree-based extensions","author":"Han","year":"2024"},{"key":"10.1016\/j.eswa.2026.132913_bib0018","doi-asserted-by":"crossref","first-page":"18100","DOI":"10.52202\/068431-1316","article-title":"Card: Classification and regression diffusion models","volume":"35","author":"Han","year":"2022","journal-title":"Advances in Neural Information Processing Systems"},{"key":"10.1016\/j.eswa.2026.132913_bib0019","first-page":"6840","article-title":"Denoising diffusion probabilistic models","volume":"33","author":"Ho","year":"2020","journal-title":"Advances in Neural Information Processing Systems"},{"key":"10.1016\/j.eswa.2026.132913_bib0020","doi-asserted-by":"crossref","DOI":"10.1016\/j.aei.2024.102866","article-title":"Massive-scale construction dataset synthesis through stable diffusion for machine learning training","volume":"62","author":"Hong","year":"2024","journal-title":"Advanced Engineering Informatics"},{"key":"10.1016\/j.eswa.2026.132913_bib0021","doi-asserted-by":"crossref","DOI":"10.1016\/j.knosys.2025.113848","article-title":"Dtiu: A self-supervised grid-enhanced diffusion model for trajectory imputation in unconstrained scenarios","volume":"325","author":"Hu","year":"2025","journal-title":"Knowledge-Based Systems"},{"issue":"6","key":"10.1016\/j.eswa.2026.132913_bib0022","doi-asserted-by":"crossref","first-page":"4409","DOI":"10.1109\/TPAMI.2025.3541625","article-title":"Diffusion model-based image editing: A survey","volume":"47","author":"Huang","year":"2025","journal-title":"IEEE Transactions on Pattern Analysis and Machine Intelligence"},{"key":"10.1016\/j.eswa.2026.132913_bib0023","series-title":"Proceedings of the AAAI conference on artificial intelligence","first-page":"4374","article-title":"Continuous trajectory generation based on two-stage GAN","volume":"vol. 37","author":"Jiang","year":"2023"},{"key":"10.1016\/j.eswa.2026.132913_bib0024","series-title":"Companion proceedings of the ACM on web conference 2025","first-page":"2847","article-title":"TrajLLM: A modular LLM-enhanced agent-based framework for realistic human trajectory simulation","author":"Ju","year":"2025"},{"key":"10.1016\/j.eswa.2026.132913_bib0025","doi-asserted-by":"crossref","first-page":"439","DOI":"10.1016\/j.neucom.2004.04.002","article-title":"Artificial neural networks for non-stationary time series","volume":"61","author":"Kim","year":"2004","journal-title":"Neurocomputing"},{"key":"10.1016\/j.eswa.2026.132913_bib0026","series-title":"European conference on computer vision","first-page":"201","article-title":"Activity forecasting","author":"Kitani","year":"2012"},{"key":"10.1016\/j.eswa.2026.132913_bib0027","first-page":"1","article-title":"Generalized sliced Wasserstein distances","volume":"32","author":"Kolouri","year":"2019","journal-title":"Advances in Neural Information Processing Systems"},{"key":"10.1016\/j.eswa.2026.132913_bib0028","doi-asserted-by":"crossref","DOI":"10.1016\/j.asoc.2024.111690","article-title":"Traffic trajectory generation via conditional generative adversarial networks for transportation metaverse","volume":"160","author":"Kong","year":"2024","journal-title":"Applied Soft Computing"},{"key":"10.1016\/j.eswa.2026.132913_bib0029","doi-asserted-by":"crossref","DOI":"10.1016\/j.aei.2024.102969","article-title":"Deep meta-learning approach for regional parking occupancy prediction considering heterogeneous and real-time information","volume":"64","author":"Kuang","year":"2025","journal-title":"Advanced Engineering Informatics"},{"key":"10.1016\/j.eswa.2026.132913_bib0030","series-title":"Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition","first-page":"2221","article-title":"Muse-vae: Multi-scale vae for environment-aware long term trajectory prediction","author":"Lee","year":"2022"},{"issue":"6","key":"10.1016\/j.eswa.2026.132913_bib0031","doi-asserted-by":"crossref","first-page":"72","DOI":"10.1109\/MSP.2024.3445871","article-title":"Diffusion models for audio restoration: A review [special issue on model-based and data-driven audio signal processing]","volume":"41","author":"Lemercier","year":"2025","journal-title":"IEEE Signal Processing Magazine"},{"key":"10.1016\/j.eswa.2026.132913_bib0032","series-title":"Journal of South China Normal University (Natural Science Edition)\/Huanan Shifan Daxue Xuebao (Ziran Kexue Ban)","article-title":"Predicting optimal route based on link-to-link transition probability","volume":"54","author":"Li","year":"2022"},{"key":"10.1016\/j.eswa.2026.132913_bib0033","series-title":"IEEE International Conference on Robotics and Automation (ICRA)","first-page":"16841","article-title":"Crossway diffusion: Improving diffusion-based visuomotor policy via self-supervised learning","author":"Li","year":"2024"},{"key":"10.1016\/j.eswa.2026.132913_bib0034","series-title":"The twelfth international conference on learning representations","article-title":"Transformer-modulated diffusion models for probabilistic multivariate time series forecasting","author":"Li","year":"2024"},{"key":"10.1016\/j.eswa.2026.132913_bib0035","doi-asserted-by":"crossref","first-page":"23009","DOI":"10.52202\/068431-1672","article-title":"Generative time series forecasting with diffusion, denoise, and disentanglement","volume":"35","author":"Li","year":"2022","journal-title":"Advances in Neural Information Processing Systems"},{"issue":"9","key":"10.1016\/j.eswa.2026.132913_bib0036","doi-asserted-by":"crossref","first-page":"14470","DOI":"10.1109\/TITS.2021.3129588","article-title":"Nettraj: A network-based vehicle trajectory prediction model with directional representation and spatiotemporal attention mechanisms","volume":"23","author":"Liang","year":"2021","journal-title":"IEEE Transactions on Intelligent Transportation Systems"},{"key":"10.1016\/j.eswa.2026.132913_bib0037","unstructured":"Liu, L., Ren, Y., Lin, Z., & Zhao, Z. (2022a). Pseudo numerical methods for diffusion models on manifolds. arXiv preprint arXiv: 2202.09778."},{"key":"10.1016\/j.eswa.2026.132913_bib0038","series-title":"Proceedings of the AAAI conference on artificial intelligence","article-title":"Predicting the next location: A recurrent model with spatial and temporal contexts","volume":"vol. 30","author":"Liu","year":"2016"},{"issue":"1","key":"10.1016\/j.eswa.2026.132913_bib0039","doi-asserted-by":"crossref","first-page":"257","DOI":"10.1109\/TMC.2025.3591183","article-title":"Spatio-temporal diffusion model for cellular traffic generation","volume":"25","author":"Liu","year":"2025","journal-title":"IEEE Transactions on Mobile Computing"},{"key":"10.1016\/j.eswa.2026.132913_bib0040","doi-asserted-by":"crossref","first-page":"9881","DOI":"10.52202\/068431-0718","article-title":"Non-stationary transformers: Exploring the stationarity in time series forecasting","volume":"35","author":"Liu","year":"2022","journal-title":"Advances in Neural Information Processing Systems"},{"key":"10.1016\/j.eswa.2026.132913_bib0041","doi-asserted-by":"crossref","first-page":"5775","DOI":"10.52202\/068431-0418","article-title":"Dpm-solver: A fast ode solver for diffusion probabilistic model sampling in around 10 steps","volume":"35","author":"Lu","year":"2022","journal-title":"Advances in Neural Information Processing Systems"},{"key":"10.1016\/j.eswa.2026.132913_bib0042","unstructured":"Luo, C. (2022). Understanding diffusion models: A unified perspective. arXiv preprint arXiv: 2208.11970."},{"key":"10.1016\/j.eswa.2026.132913_bib0043","series-title":"Proceedings of the SIGSPATIAL ACM GIS 2008 international workshop on security and privacy in GIS and LBS","first-page":"52","article-title":"Towards trajectory anonymization: A generalization-based approach","author":"Nergiz","year":"2008"},{"key":"10.1016\/j.eswa.2026.132913_bib0044","series-title":"Proceedings of the 17th ACM SIGSPATIAL international conference on advances in geographic information systems","first-page":"336","article-title":"Hidden Markov map matching through noise and sparseness","author":"Newson","year":"2009"},{"key":"10.1016\/j.eswa.2026.132913_bib0045","series-title":"International conference on machine learning","first-page":"8162","article-title":"Improved denoising diffusion probabilistic models","author":"Nichol","year":"2021"},{"issue":"12","key":"10.1016\/j.eswa.2026.132913_bib0046","doi-asserted-by":"crossref","first-page":"21526","DOI":"10.1109\/TITS.2025.3613178","article-title":"Diffusion models for intelligent transportation systems: A survey","volume":"26","author":"Peng","year":"2025","journal-title":"IEEE Transactions on Intelligent Transportation Systems"},{"key":"10.1016\/j.eswa.2026.132913_sbref0047","series-title":"Proceedings of the 38th international conference on machine learning","first-page":"8857","article-title":"Autoregressive denoising diffusion models for multivariate probabilistic time series forecasting","volume":"vol. 139","author":"Rasul","year":"2021"},{"key":"10.1016\/j.eswa.2026.132913_bib0048","first-page":"1","article-title":"Non-stationary dynamic bayesian networks","volume":"21","author":"Robinson","year":"2008","journal-title":"Advances in Neural Information Processing Systems"},{"key":"10.1016\/j.eswa.2026.132913_bib0049","series-title":"International conference on machine learning","first-page":"2256","article-title":"Deep unsupervised learning using nonequilibrium thermodynamics","author":"Sohl-Dickstein","year":"2015"},{"key":"10.1016\/j.eswa.2026.132913_bib0050","unstructured":"Song, J., Meng, C., & Ermon, S. (2020). Denoising diffusion implicit models. arXiv preprint arXiv: 2010.02502."},{"key":"10.1016\/j.eswa.2026.132913_bib0051","first-page":"24804","article-title":"CSDI: Conditional score-based diffusion models for probabilistic time series imputation","volume":"34","author":"Tashiro","year":"2021","journal-title":"Advances in Neural Information Processing Systems"},{"issue":"8","key":"10.1016\/j.eswa.2026.132913_bib0052","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/3721479","article-title":"Attacks and defenses for generative diffusion models: A comprehensive survey","volume":"57","author":"Truong","year":"2025","journal-title":"ACM Computing Surveys"},{"key":"10.1016\/j.eswa.2026.132913_bib0053","series-title":"Optimal transport: Old and new","first-page":"93","article-title":"The Wasserstein distances","author":"Villani","year":"2009"},{"issue":"9","key":"10.1016\/j.eswa.2026.132913_bib0054","first-page":"1","article-title":"Trajectory grid diffusion for multimodal trajectory prediction in autonomous vehicles","volume":"18","author":"Wang","year":"2024","journal-title":"IEEE Transactions on Intelligent Vehicles"},{"issue":"12","key":"10.1016\/j.eswa.2026.132913_bib0055","doi-asserted-by":"crossref","first-page":"5910","DOI":"10.1109\/TKDE.2021.3068479","article-title":"Personalized route recommendation with neural network enhanced search algorithm","volume":"34","author":"Wang","year":"2021","journal-title":"IEEE Transactions on Knowledge and Data Engineering"},{"key":"10.1016\/j.eswa.2026.132913_bib0056","series-title":"Proceedings of the ACM web conference 2024","first-page":"3509","article-title":"Cola: Cross-city mobility transformer for human trajectory simulation","author":"Wang","year":"2024"},{"issue":"12","key":"10.1016\/j.eswa.2026.132913_bib0057","doi-asserted-by":"crossref","first-page":"7940","DOI":"10.1109\/TKDE.2024.3460051","article-title":"Diff-RNTraj: A structure-aware diffusion model for road network-constrained trajectory generation","volume":"36","author":"Wei","year":"2024","journal-title":"IEEE Transactions on Knowledge and Data Engineering"},{"key":"10.1016\/j.eswa.2026.132913_bib0058","doi-asserted-by":"crossref","first-page":"39","DOI":"10.1016\/j.ins.2015.02.024","article-title":"Learning similarity with cosine similarity ensemble","volume":"307","author":"Xia","year":"2015","journal-title":"Information Sciences"},{"issue":"2","key":"10.1016\/j.eswa.2026.132913_bib0059","doi-asserted-by":"crossref","first-page":"1733","DOI":"10.1109\/TCSS.2023.3235923","article-title":"TrajSGAN: A semantic-guiding adversarial network for urban trajectory generation","volume":"11","author":"Xiong","year":"2023","journal-title":"IEEE Transactions on Computational Social Systems"},{"key":"10.1016\/j.eswa.2026.132913_bib0060","series-title":"Proceedings of the 2025\u202fSIAM international conference on data mining (SDM)","first-page":"538","article-title":"AutoSTDiff: Autoregressive spatio-temporal denoising diffusion model for asynchronous trajectory generation","author":"Xu","year":"2025"},{"key":"10.1016\/j.eswa.2026.132913_bib0061","series-title":"Proceedings of the AAAI conference on artificial intelligence","article-title":"SeqGAN: Sequence generative adversarial nets with policy gradient","volume":"vol. 31","author":"Yu","year":"2017"},{"issue":"1","key":"10.1016\/j.eswa.2026.132913_bib0062","doi-asserted-by":"crossref","first-page":"116","DOI":"10.1109\/TPAMI.2024.3461721","article-title":"Efficient diffusion model for image restoration by residual shifting","volume":"47","author":"Yue","year":"2024","journal-title":"IEEE Transactions on Pattern Analysis and Machine Intelligence"},{"issue":"3","key":"10.1016\/j.eswa.2026.132913_bib0063","doi-asserted-by":"crossref","first-page":"520","DOI":"10.1109\/TNN.2003.810603","article-title":"Trajectory generation and modulation using dynamic neural networks","volume":"14","author":"Zegers","year":"2003","journal-title":"IEEE Transactions on Neural Networks"},{"key":"10.1016\/j.eswa.2026.132913_bib0064","unstructured":"Zeng, Y., Cao, J., Li, Z., Chen, Y., Ren, T., Li, Z., Xiang, D., Wu, X., Gao, S., & Yu, T. (2025). TreeDiff: AST-guided code generation with diffusion LLMs. arXiv preprint arXiv: 2508.01473."},{"key":"10.1016\/j.eswa.2026.132913_bib0065","doi-asserted-by":"crossref","unstructured":"Zhang, L., Zhao, L., & Pfoser, D. (2022a). Factorized deep generative models for end-to-end trajectory generation with spatiotemporal validity constraints. In Proceedings of the 30th international conference on advances in geographic information systems (pp. 1\u201312).","DOI":"10.1145\/3557915.3560994"},{"issue":"12","key":"10.1016\/j.eswa.2026.132913_bib0066","doi-asserted-by":"crossref","first-page":"24474","DOI":"10.1109\/TITS.2022.3202185","article-title":"Trajgen: Generating realistic and diverse trajectories with reactive and feasible agent behaviors for autonomous driving","volume":"23","author":"Zhang","year":"2022","journal-title":"IEEE Transactions on Intelligent Transportation Systems"},{"key":"10.1016\/j.eswa.2026.132913_bib0067","doi-asserted-by":"crossref","DOI":"10.1016\/j.aei.2024.102966","article-title":"Research on multi-stage topology optimization method based on latent diffusion model","volume":"63","author":"Zhang","year":"2025","journal-title":"Advanced Engineering Informatics"},{"key":"10.1016\/j.eswa.2026.132913_bib0068","doi-asserted-by":"crossref","first-page":"22961","DOI":"10.52202\/075280-0995","article-title":"SynMob: Creating high-fidelity synthetic GPS trajectory dataset for urban mobility analysis","volume":"36","author":"Zhu","year":"2023","journal-title":"Advances in Neural Information Processing Systems"},{"key":"10.1016\/j.eswa.2026.132913_bib0069","doi-asserted-by":"crossref","first-page":"65168","DOI":"10.52202\/075280-2843","article-title":"DiffTraj: Generating GPS trajectory with diffusion probabilistic model","volume":"36","author":"Zhu","year":"2023","journal-title":"Advances in Neural Information Processing Systems"},{"key":"10.1016\/j.eswa.2026.132913_bib0070","series-title":"Proceedings of the 30th ACM SIGKDD conference on knowledge discovery and data mining","first-page":"4676","article-title":"ControlTraj: Controllable trajectory generation with topology-constrained diffusion model","author":"Zhu","year":"2024"}],"container-title":["Expert Systems with Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0957417426018257?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0957417426018257?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,9,6]],"date-time":"2026-09-06T08:58:24Z","timestamp":1788685104000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S0957417426018257"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,11]]},"references-count":70,"alternative-id":["S0957417426018257"],"URL":"https:\/\/doi.org\/10.1016\/j.eswa.2026.132913","relation":{},"ISSN":["0957-4174"],"issn-type":[{"value":"0957-4174","type":"print"}],"subject":[],"published":{"date-parts":[[2026,11]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"Non-stationary diffusion for trajectory generation incorporating turning choice behavior and geographic attention U-Net","name":"articletitle","label":"Article Title"},{"value":"Expert Systems with Applications","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.eswa.2026.132913","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2026 Elsevier Ltd. All rights are reserved, including those for text and data mining, AI training, and similar technologies.","name":"copyright","label":"Copyright"}],"article-number":"132913"}}