{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,28]],"date-time":"2026-03-28T07:11:46Z","timestamp":1774681906339,"version":"3.50.1"},"publisher-location":"Singapore","reference-count":25,"publisher":"Springer Nature Singapore","isbn-type":[{"value":"9789819698905","type":"print"},{"value":"9789819698912","type":"electronic"}],"license":[{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2025]]},"DOI":"10.1007\/978-981-96-9891-2_26","type":"book-chapter","created":{"date-parts":[[2025,7,25]],"date-time":"2025-07-25T05:45:30Z","timestamp":1753422330000},"page":"304-316","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Spatial-Temporal Traffic Prediction Based on Multi-Scale Time Difference"],"prefix":"10.1007","author":[{"given":"Yongli","family":"Hu","sequence":"first","affiliation":[]},{"given":"Qi","family":"Zuo","sequence":"additional","affiliation":[]},{"given":"Kan","family":"Guo","sequence":"additional","affiliation":[]},{"given":"Zhongfan","family":"Sun","sequence":"additional","affiliation":[]},{"given":"Tingzheng","family":"Jia","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2025,7,26]]},"reference":[{"issue":"10","key":"26_CR1","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1007\/s11432-015-5397-4","volume":"58","author":"C Yin","year":"2015","unstructured":"Yin, C., Xiong, Z., Chen, H., Wang, J., Cooper, D., David, B.: A literature survey on smart cities. Sci. China Inf. Sci. 58(10), 1\u201318 (2015)","journal-title":"Sci. China Inf. Sci."},{"issue":"9","key":"26_CR2","doi-asserted-by":"publisher","first-page":"3848","DOI":"10.1109\/TITS.2019.2935152","volume":"21","author":"L Zhao","year":"2019","unstructured":"Zhao, L., et al.: T-GCN: a temporal graph convolutional network for traffic prediction. IEEE Trans. Intell. Transp. Syst. 21(9), 3848\u20133858 (2019)","journal-title":"IEEE Trans. Intell. Transp. Syst."},{"issue":"7","key":"26_CR3","doi-asserted-by":"publisher","first-page":"485","DOI":"10.3390\/ijgi10070485","volume":"10","author":"J Bai","year":"2021","unstructured":"Bai, J., et al.: A3T-GCN: attention temporal graph convolutional network for traffic forecasting. ISPRS Int. J. Geo Inf. 10(7), 485 (2021)","journal-title":"ISPRS Int. J. Geo Inf."},{"issue":"11","key":"26_CR4","doi-asserted-by":"publisher","first-page":"20681","DOI":"10.1109\/TITS.2022.3173689","volume":"23","author":"J Huang","year":"2022","unstructured":"Huang, J., Luo, K., Cao, L., Wen, Y., Zhong, S.: Learning multiaspect traffic couplings by multirelational graph attention networks for traffic prediction. IEEE Trans. Intell. Transp. Syst. 23(11), 20681\u201320695 (2022)","journal-title":"IEEE Trans. Intell. Transp. Syst."},{"key":"26_CR5","doi-asserted-by":"crossref","unstructured":"Jiang, J., Han, C., Zhao, W.X., Wang, J.: PDFormer: propagation delay-aware dynamic long-range transformer for traffic flow prediction. In: Proceedings of the AAAI Conference on Artificial Intelligence, vol. 37, pp. 4365\u20134373 (2023)","DOI":"10.1609\/aaai.v37i4.25556"},{"issue":"1","key":"26_CR6","doi-asserted-by":"publisher","first-page":"65","DOI":"10.1007\/s13042-022-01689-2","volume":"15","author":"J Xia","year":"2024","unstructured":"Xia, J., Wang, S., Wang, X., Xia, M., Xie, K., Cao, J.: Multi-view Bayesian spatio-temporal graph neural networks for reliable traffic flow prediction. Int. J. Mach. Learn. Cybern. 15(1), 65\u201378 (2024)","journal-title":"Int. J. Mach. Learn. Cybern."},{"key":"26_CR7","doi-asserted-by":"crossref","unstructured":"Wang, Y., et al.: Fully-connected spatial-temporal graph for multivariate time-series data. In: Proceedings of the AAAI Conference on Artificial Intelligence, vol. 38, pp.15715\u201315724 (2024)","DOI":"10.1609\/aaai.v38i14.29500"},{"key":"26_CR8","doi-asserted-by":"crossref","unstructured":"Du, S., Xu, Z., Lv, J.: An EMD-and GRU-based hybrid network traffic prediction model with data reconstruction. In: 2021 IEEE International Conference on Communications Workshops (ICC Workshops), pp. 1\u20137. IEEE (2021)","DOI":"10.1109\/ICCWorkshops50388.2021.9473822"},{"key":"26_CR9","doi-asserted-by":"crossref","unstructured":"Lu, H., Yang, F.: A network traffic prediction model based on wavelet transformation and LSTM network. In: 2018 IEEE 9th International Conference on Software Engineering and Service Science (ICSESS), pp. 1\u20134. IEEE (2018)","DOI":"10.1109\/ICSESS.2018.8663884"},{"key":"26_CR10","doi-asserted-by":"crossref","unstructured":"Hochreiter, S.: Long Short-term Memory. Neural Computation MIT-Press (1997)","DOI":"10.1162\/neco.1997.9.8.1735"},{"issue":"1","key":"26_CR11","doi-asserted-by":"publisher","first-page":"156","DOI":"10.1111\/j.1467-6419.2010.00637.x","volume":"25","author":"D Qin","year":"2011","unstructured":"Qin, D.: Rise of VAR modelling approach. J. Econ. Surv. 25(1), 156\u2013174 (2011)","journal-title":"J. Econ. Surv."},{"key":"26_CR12","unstructured":"Drucker, H., Burges, C.J., Kaufman, L., Smola, A., Vapnik, V.: Support vector regression machines. Advances in neural information processing systems 9 (1996)"},{"key":"26_CR13","doi-asserted-by":"crossref","unstructured":"Seo, Y., Defferrard, M., Vandergheynst, P., Bresson, X.: Structured sequence modeling with graph convolutional recurrent networks. In: Neural information processing: 25th International Conference, ICONIP 2018, Siem Reap, Cambodia, December 13\u201316, 2018, proceedings, part I 25, pp. 362\u2013373. Springer (2018)","DOI":"10.1007\/978-3-030-04167-0_33"},{"key":"26_CR14","doi-asserted-by":"crossref","unstructured":"Yu, B., Yin, H., Zhu, Z.: Spatio-temporal graph convolutional networks: a deep learning framework for traffic forecasting. arXiv preprint arXiv:1709.04875 (2017)","DOI":"10.24963\/ijcai.2018\/505"},{"key":"26_CR15","unstructured":"Li, Y., Yu, R., Shahabi, C., Liu, Y.: Diffusion convolutional recurrent neural network: data-driven traffic forecasting. arXiv preprint arXiv:1707.01926 (2017)"},{"issue":"2","key":"26_CR16","doi-asserted-by":"publisher","first-page":"1138","DOI":"10.1109\/TITS.2019.2963722","volume":"22","author":"K Guo","year":"2020","unstructured":"Guo, K., et al.: Optimized graph convolution recurrent neural network for traffic prediction. IEEE Trans. Intell. Transp. Syst. 22(2), 1138\u20131149 (2020)","journal-title":"IEEE Trans. Intell. Transp. Syst."},{"key":"26_CR17","doi-asserted-by":"crossref","unstructured":"Wu, Z., Pan, S., Long, G., Jiang, J., Zhang, C.: Graph wavenet for deep spatial-temporal graph modeling. arXiv preprint arXiv:1906.00121 (2019)","DOI":"10.24963\/ijcai.2019\/264"},{"key":"26_CR18","doi-asserted-by":"crossref","unstructured":"Guo, S., Lin, Y., Feng, N., Song, C., Wan, H.: Attention based spatial-temporal graph convolutional networks for traffic flow forecasting. In: Proceedings of the AAAI Conference on Artificial Intelligence, vol. 33, pp. 922\u2013929 (2019)","DOI":"10.1609\/aaai.v33i01.3301922"},{"issue":"2","key":"26_CR19","doi-asserted-by":"publisher","first-page":"1009","DOI":"10.1109\/TITS.2020.3019497","volume":"23","author":"K Guo","year":"2020","unstructured":"Guo, K., Hu, Y., Qian, Z., Sun, Y., Gao, J., Yin, B.: Dynamic graph convolution network for traffic forecasting based on latent network of Laplace matrix estimation. IEEE Trans. Intell. Transp. Syst. 23(2), 1009\u20131018 (2020)","journal-title":"IEEE Trans. Intell. Transp. Syst."},{"key":"26_CR20","doi-asserted-by":"crossref","unstructured":"Song, C., Lin, Y., Guo, S., Wan, H.: Spatial-temporal synchronous graph convolutional networks: a new framework for spatial-temporal network data forecasting. In: Proceedings of the AAAI Conference on Artificial Intelligence, vol. 34, pp. 914\u2013921 (2020)","DOI":"10.1609\/aaai.v34i01.5438"},{"key":"26_CR21","doi-asserted-by":"crossref","unstructured":"Chen, W., Chen, L., Xie, Y., Cao, W., Gao, Y., Feng, X.: Multi-range attentive bicomponent graph convolutional network for traffic forecasting. In: Proceedings of the AAAI Conference on Artificial Intelligence, vol. 34, pp. 3529\u20133536 (2020)","DOI":"10.1609\/aaai.v34i04.5758"},{"key":"26_CR22","doi-asserted-by":"crossref","unstructured":"Li, M., Zhu, Z.: Spatial-temporal fusion graph neural networks for traffic flow forecasting. In: Proceedings of the AAAI Conference on Artificial Intelligence, vol. 35, pp. 4189\u20134196 (2021)","DOI":"10.1609\/aaai.v35i5.16542"},{"issue":"12","key":"26_CR23","doi-asserted-by":"publisher","first-page":"23680","DOI":"10.1109\/TITS.2022.3208943","volume":"23","author":"Y Sun","year":"2022","unstructured":"Sun, Y., et al.: Dual dynamic spatial-temporal graph convolution network for traffic prediction. IEEE Trans. Intell. Transp. Syst. 23(12), 23680\u201323693 (2022)","journal-title":"IEEE Trans. Intell. Transp. Syst."},{"issue":"9","key":"26_CR24","doi-asserted-by":"publisher","first-page":"1835","DOI":"10.1049\/itr2.12378","volume":"17","author":"Y Hu","year":"2023","unstructured":"Hu, Y., Peng, T., Guo, K., Sun, Y., Gao, J., Yin, B.: Graph transformer based dynamic multiple graph convolution networks for traffic flow forecasting. IET Intel. Transport Syst. 17(9), 1835\u20131845 (2023)","journal-title":"IET Intel. Transport Syst."},{"key":"26_CR25","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2024.128249","volume":"602","author":"K Guo","year":"2024","unstructured":"Guo, K., et al.: Contrastive optimized graph convolution network for traffic forecasting. Neurocomputing 602, 128249 (2024)","journal-title":"Neurocomputing"}],"container-title":["Lecture Notes in Computer Science","Advanced Intelligent Computing Technology and Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-981-96-9891-2_26","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,3,28]],"date-time":"2026-03-28T06:06:35Z","timestamp":1774677995000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-981-96-9891-2_26"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025]]},"ISBN":["9789819698905","9789819698912"],"references-count":25,"URL":"https:\/\/doi.org\/10.1007\/978-981-96-9891-2_26","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025]]},"assertion":[{"value":"26 July 2025","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"The authors have no competing interests to declare that relevant to the content of this article.","order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Disclosure of Interests."}},{"value":"ICIC","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Intelligent Computing","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Ningbo","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"China","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2025","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"26 July 2025","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"29 July 2025","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"21","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"icic2025","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/www.ic-icc.cn\/icg\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}