{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,26]],"date-time":"2025-03-26T03:50:40Z","timestamp":1742961040288,"version":"3.40.3"},"publisher-location":"Cham","reference-count":21,"publisher":"Springer Nature Switzerland","isbn-type":[{"type":"print","value":"9783031714634"},{"type":"electronic","value":"9783031714641"}],"license":[{"start":{"date-parts":[[2024,11,13]],"date-time":"2024-11-13T00:00:00Z","timestamp":1731456000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2024,11,13]],"date-time":"2024-11-13T00:00:00Z","timestamp":1731456000000},"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\/978-3-031-71464-1_22","type":"book-chapter","created":{"date-parts":[[2024,11,12]],"date-time":"2024-11-12T17:50:49Z","timestamp":1731433849000},"page":"261-272","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Mobile Crowdsourcing Task Assignment Algorithm Based on\u00a0ConvNeXt and\u00a0GRU"],"prefix":"10.1007","author":[{"given":"Zequn","family":"Fan","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Qingxian","family":"Pan","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zhaolong","family":"Gao","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Peng","family":"Luan","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Kai","family":"Wei","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jinru","family":"Li","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2024,11,13]]},"reference":[{"key":"22_CR1","doi-asserted-by":"publisher","first-page":"1120","DOI":"10.1007\/s11036-018-1105-0","volume":"24","author":"A Ben Said","year":"2019","unstructured":"Ben Said, A., Erradi, A., Neiat, A.G., Bouguettaya, A.: A deep learning spatiotemporal prediction framework for mobile crowdsourced services. Mob. Networks Appl. 24, 1120\u20131133 (2019)","journal-title":"Mob. Networks Appl."},{"issue":"8","key":"22_CR2","doi-asserted-by":"publisher","first-page":"2576","DOI":"10.1109\/TMC.2020.2987881","volume":"20","author":"Z Cai","year":"2020","unstructured":"Cai, Z., Duan, Z., Li, W.: Exploiting multi-dimensional task diversity in distributed auctions for mobile crowdsensing. IEEE Trans. Mob. Comput. 20(8), 2576\u20132591 (2020)","journal-title":"IEEE Trans. Mob. Comput."},{"unstructured":"Chung, J., Gulcehre, C., Cho, K., Bengio, Y.: Empirical evaluation of gated recurrent neural networks on sequence modeling. arXiv preprint arXiv:1412.3555 (2014)","key":"22_CR3"},{"key":"22_CR4","doi-asserted-by":"publisher","first-page":"269","DOI":"10.1016\/j.neucom.2019.12.118","volume":"388","author":"S Du","year":"2020","unstructured":"Du, S., Li, T., Yang, Y., Horng, S.J.: Multivariate time series forecasting via attention-based encoder-decoder framework. Neurocomputing 388, 269\u2013279 (2020)","journal-title":"Neurocomputing"},{"issue":"8","key":"22_CR5","doi-asserted-by":"publisher","first-page":"651","DOI":"10.1016\/j.patrec.2009.09.011","volume":"31","author":"AK Jain","year":"2010","unstructured":"Jain, A.K.: Data clustering: 50 years beyond k-means. Pattern Recogn. Lett. 31(8), 651\u2013666 (2010)","journal-title":"Pattern Recogn. Lett."},{"issue":"3","key":"22_CR6","doi-asserted-by":"publisher","first-page":"264","DOI":"10.1145\/331499.331504","volume":"31","author":"AK Jain","year":"1999","unstructured":"Jain, A.K., Murty, M.N., Flynn, P.J.: Data clustering: a review. ACM Comput. Surv. (CSUR) 31(3), 264\u2013323 (1999)","journal-title":"ACM Comput. Surv. (CSUR)"},{"doi-asserted-by":"crossref","unstructured":"Kumar, V., Patra, S.K.: Feature engineering for machine learning and deep learning assisted wireless communication. In: Metaheuristics in machine learning: theory and applications, pp. 77\u201395. Springer (2021)","key":"22_CR7","DOI":"10.1007\/978-3-030-70542-8_4"},{"issue":"3","key":"22_CR8","doi-asserted-by":"publisher","first-page":"1370","DOI":"10.1109\/TSTE.2019.2926147","volume":"11","author":"C Li","year":"2019","unstructured":"Li, C., Tang, G., Xue, X., Saeed, A., Hu, X.: Short-term wind speed interval prediction based on ensemble gru model. IEEE Trans. Sustainable energy 11(3), 1370\u20131380 (2019)","journal-title":"IEEE Trans. Sustainable energy"},{"issue":"1","key":"22_CR9","doi-asserted-by":"publisher","first-page":"993","DOI":"10.1109\/TVT.2021.3050339","volume":"70","author":"Y Lin","year":"2021","unstructured":"Lin, Y., Cai, Z., Wang, X., Hao, F., Wang, L., Sai, A.M.V.V.: Multi-round incentive mechanism for cold start-enabled mobile crowdsensing. IEEE Trans. Veh. Technol. 70(1), 993\u20131007 (2021)","journal-title":"IEEE Trans. Veh. Technol."},{"issue":"3","key":"22_CR10","doi-asserted-by":"publisher","first-page":"512","DOI":"10.1080\/00045608.2015.1018773","volume":"105","author":"Y Liu","year":"2015","unstructured":"Liu, Y., et al.: Social sensing: a new approach to understanding our socioeconomic environments. Ann. Assoc. Am. Geogr. 105(3), 512\u2013530 (2015)","journal-title":"Ann. Assoc. Am. Geogr."},{"doi-asserted-by":"crossref","unstructured":"Liu, Z., et al.: Swin transformer: hierarchical vision transformer using shifted windows. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision, pp. 10012\u201310022 (2021)","key":"22_CR11","DOI":"10.1109\/ICCV48922.2021.00986"},{"doi-asserted-by":"crossref","unstructured":"Liu, Z., Mao, H., Wu, C.Y., Feichtenhofer, C., Darrell, T., Xie, S.: A convnet for the 2020s. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 11976\u201311986 (2022)","key":"22_CR12","DOI":"10.1109\/CVPR52688.2022.01167"},{"unstructured":"Loshchilov, I., Hutter, F.: Decoupled weight decay regularization. arXiv preprint arXiv:1711.05101 (2017)","key":"22_CR13"},{"key":"22_CR14","doi-asserted-by":"publisher","DOI":"10.1016\/j.chaos.2020.110212","volume":"140","author":"F Shahid","year":"2020","unstructured":"Shahid, F., Zameer, A., Muneeb, M.: Predictions for covid-19 with deep learning models of lstm, gru and bi-lstm. Chaos, Solitons Fractals 140, 110212 (2020)","journal-title":"Chaos, Solitons Fractals"},{"unstructured":"Wang, Z., Oates, T.: Imaging time-series to improve classification and imputation. arXiv preprint arXiv:1506.00327 (2015)","key":"22_CR15"},{"issue":"3","key":"22_CR16","doi-asserted-by":"publisher","first-page":"928","DOI":"10.1109\/TCAD.2022.3188960","volume":"42","author":"X Wei","year":"2022","unstructured":"Wei, X., Sun, B., Cui, J., Qiu, M.: Location-and-preference joint prediction for task assignment in spatial crowdsourcing. IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. 42(3), 928\u2013941 (2022)","journal-title":"IEEE Trans. Comput. Aided Des. Integr. Circuits Syst."},{"doi-asserted-by":"crossref","unstructured":"Zhang, R., Xie, Z., Yu, D., Liang, W., Cheng, X.: Digital twin-assisted federated learning service provisioning over mobile edge networks. IEEE Trans. Comput. (2023)","key":"22_CR17","DOI":"10.1109\/TC.2023.3337317"},{"doi-asserted-by":"crossref","unstructured":"Zhao, Y., Zheng, K., Cui, Y., Su, H., Zhu, F., Zhou, X.: Predictive task assignment in spatial crowdsourcing: a data-driven approach. In: 2020 IEEE 36th International Conference on Data Engineering (ICDE), pp. 13\u201324. IEEE (2020)","key":"22_CR18","DOI":"10.1109\/ICDE48307.2020.00009"},{"issue":"2","key":"22_CR19","doi-asserted-by":"publisher","first-page":"82","DOI":"10.1109\/MWC.004.2200381","volume":"30","author":"X Zhou","year":"2023","unstructured":"Zhou, X., et al.: Decentralized p2p federated learning for privacy-preserving and resilient mobile robotic systems. IEEE Wirel. Commun. 30(2), 82\u201389 (2023)","journal-title":"IEEE Wirel. Commun."},{"issue":"4","key":"22_CR20","doi-asserted-by":"publisher","first-page":"3295","DOI":"10.1109\/JIOT.2022.3179231","volume":"10","author":"X Zhou","year":"2022","unstructured":"Zhou, X., et al.: Edge-enabled two-stage scheduling based on deep reinforcement learning for internet of everything. IEEE Internet Things J. 10(4), 3295\u20133304 (2022)","journal-title":"IEEE Internet Things J."},{"issue":"6","key":"22_CR21","doi-asserted-by":"publisher","first-page":"4196","DOI":"10.1109\/TII.2019.2941735","volume":"16","author":"S Zhu","year":"2019","unstructured":"Zhu, S., Cai, Z., Hu, H., Li, Y., Li, W.: zkcrowd: a hybrid blockchain-based crowdsourcing platform. IEEE Trans. Industr. Inf. 16(6), 4196\u20134205 (2019)","journal-title":"IEEE Trans. Industr. Inf."}],"container-title":["Lecture Notes in Computer Science","Wireless Artificial Intelligent Computing Systems and Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-71464-1_22","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,11,12]],"date-time":"2024-11-12T18:05:11Z","timestamp":1731434711000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-71464-1_22"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,11,13]]},"ISBN":["9783031714634","9783031714641"],"references-count":21,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-71464-1_22","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2024,11,13]]},"assertion":[{"value":"13 November 2024","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"WASA","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Wireless Artificial Intelligent Computing Systems and Applications","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Qingdao","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":"2024","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"21 June 2024","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"23 June 2024","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"18","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"wasa2024","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/wasa-conference.org\/WASA2024\/index.html","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}