{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,27]],"date-time":"2025-03-27T21:43:12Z","timestamp":1743111792937,"version":"3.40.3"},"publisher-location":"Cham","reference-count":17,"publisher":"Springer Nature Switzerland","isbn-type":[{"type":"print","value":"9783031180491"},{"type":"electronic","value":"9783031180507"}],"license":[{"start":{"date-parts":[[2022,10,12]],"date-time":"2022-10-12T00:00:00Z","timestamp":1665532800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2022,10,12]],"date-time":"2022-10-12T00:00:00Z","timestamp":1665532800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2023]]},"DOI":"10.1007\/978-3-031-18050-7_5","type":"book-chapter","created":{"date-parts":[[2022,10,11]],"date-time":"2022-10-11T19:02:55Z","timestamp":1665514975000},"page":"41-50","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["A SO2 Pollution Concentrations Prediction Approach Using Autoencoders"],"prefix":"10.1007","author":[{"given":"M. I.","family":"Rodr\u00edguez-Garc\u00eda","sequence":"first","affiliation":[]},{"given":"J.","family":"Gonz\u00e1lez-Enrique","sequence":"additional","affiliation":[]},{"given":"J. J.","family":"Ruiz-Aguilar","sequence":"additional","affiliation":[]},{"given":"I. J.","family":"Turias","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2022,10,12]]},"reference":[{"key":"5_CR1","doi-asserted-by":"publisher","first-page":"801","DOI":"10.1007\/s00477-018-01644-0","volume":"33","author":"J Gonz\u00e1lez-Enrique","year":"2019","unstructured":"Gonz\u00e1lez-Enrique, J., Turias, I.J., Ruiz-Aguilar, J.J., Moscoso-L\u00f3pez, J.A., Franco, L.: Spatial and meteorological relevance in NO2 estimations: a case study in the Bay of Algeciras (Spain). Stoch. Environ. Res. Risk Assess. 33, 801\u2013815 (2019)","journal-title":"Stoch. Environ. Res. Risk Assess."},{"key":"5_CR2","doi-asserted-by":"publisher","first-page":"1999","DOI":"10.1007\/s00477-021-01992-4","volume":"35","author":"J Gonz\u00e1lez-Enrique","year":"2021","unstructured":"Gonz\u00e1lez-Enrique, J., Ruiz-Aguilar, J.J., Moscoso-L\u00f3pez, J.A., Urda, D., Turias, I.J.: A comparison of ranking filter methods applied to the estimation of NO2 concentrations in the Bay of Algeciras (Spain). Stoch. Env. Res. Risk Assess. 35, 1999\u20132019 (2021)","journal-title":"Stoch. Env. Res. Risk Assess."},{"key":"5_CR3","series-title":"Advances in Intelligent Systems and Computing","doi-asserted-by":"publisher","first-page":"123","DOI":"10.1007\/978-3-030-57802-2_12","volume-title":"15th International Conference on Soft Computing Models in Industrial and Environmental Applications (SOCO 2020)","author":"JA Moscoso-L\u00f3pez","year":"2021","unstructured":"Moscoso-L\u00f3pez, J.A., Urda, D., Gonz\u00e1lez-Enrique, J., Ruiz-Aguilar, J.J., Turias, I.J.: Hourly air quality index (AQI) forecasting using machine learning methods. In: Herrero, \u00c1., Cambra, C., Urda, D., Sedano, J., Quinti\u00e1n, H., Corchado, E. (eds.) SOCO 2020. AISC, vol. 1268, pp. 123\u2013132. Springer, Cham (2021). https:\/\/doi.org\/10.1007\/978-3-030-57802-2_12"},{"key":"5_CR4","doi-asserted-by":"crossref","unstructured":"Rodr\u00edguez-Garc\u00eda, M.I., Gonz\u00e1lez-Enrique, J., Moscoso-L\u00f3pez, J.A., Ruiz-Aguilar, J.J., Rodr\u00edguez-L\u00f3pez, J., Turias, I.J.: Comparison of maritime transport influence of SO2 levels in Algeciras and Alcornocales Park (Spain). In: XIV Conference on Transport Engineering, CIT2021, vol. 58, pp. 2352\u20131465 (2021)","DOI":"10.1016\/j.trpro.2021.11.078"},{"issue":"3","key":"5_CR5","first-page":"58","volume":"1","author":"Y Akin","year":"2018","unstructured":"Akin, Y., Cansu, Z., Oktay, H.: Air pollution modelling with deep learning: a review. Int. J. Environ. Pollut. Environ. Model. 1(3), 58\u201362 (2018)","journal-title":"Int. J. Environ. Pollut. Environ. Model."},{"key":"5_CR6","doi-asserted-by":"publisher","first-page":"22048","DOI":"10.1007\/s11356-016-7812-9","volume":"23","author":"X Li","year":"2016","unstructured":"Li, X., Peng, L., Hu, Y., Shao, J., Chi, T.: Deep learning architecture for air quality predictions. Environ. Sci. Pollut. Res. 23, 22048\u201322417 (2016)","journal-title":"Environ. Sci. Pollut. Res."},{"key":"5_CR7","doi-asserted-by":"crossref","unstructured":"Bo Zhang, B., Zhang, H., Zhao, G., Lian, J.: Constructing a PM2.5 concentration prediction model by combining autoencoder with Bi-LSTM neural networks. Environ. Model. Softw. 124 (2020)","DOI":"10.1016\/j.envsoft.2019.104600"},{"key":"5_CR8","doi-asserted-by":"publisher","first-page":"399","DOI":"10.1007\/s40726-020-00159-z","volume":"6","author":"Q Liao","year":"2020","unstructured":"Liao, Q., Zhu, M., Wu, L., Pan, X., Tang, X., Wang, Z.: Deep learning for air quality forecasts: a review. Curr. Pollut. Rep. 6, 399\u2013499 (2020)","journal-title":"Curr. Pollut. Rep."},{"issue":"6","key":"5_CR9","doi-asserted-by":"publisher","first-page":"3269","DOI":"10.3390\/su14063269","volume":"14","author":"AG Mengara","year":"2022","unstructured":"Mengara, A.G., Park, E., Jang, J., Yoo, Y.: Attention-based distributed deep learning model for air quality forecasting. Sustainability 14(6), 3269 (2022)","journal-title":"Sustainability"},{"issue":"7553","key":"5_CR10","doi-asserted-by":"publisher","first-page":"436","DOI":"10.1038\/nature14539","volume":"521","author":"Y LeCun","year":"2015","unstructured":"LeCun, Y., Bengio, Y., Hinton, G.: Deep learning. Nature 521(7553), 436\u2013444 (2015)","journal-title":"Nature"},{"issue":"1","key":"5_CR11","doi-asserted-by":"publisher","first-page":"71","DOI":"10.3390\/atmos13010071","volume":"13","author":"B Baldorj","year":"2022","unstructured":"Baldorj, B., Tsagaan, M., Sereeter, L., Bulkhbai, A.: Embedded generative air pollution model with variational autoencoder and environmental factor effect in Ulaanbaatar city. Atmosphere 13(1), 71 (2022)","journal-title":"Atmosphere"},{"key":"5_CR12","doi-asserted-by":"crossref","unstructured":"Xayasouk, T., Lee, H.: Air pollution prediction system using deep learning. WIT Trans. Ecol. Environ. 230 (2018)","DOI":"10.2495\/AIR180071"},{"key":"5_CR13","doi-asserted-by":"publisher","first-page":"533","DOI":"10.1038\/323533a0","volume":"323","author":"DE Rumelhart","year":"1986","unstructured":"Rumelhart, D.E., Hinton, G.E., Williams, R.J.: Learning representations by back-propagating errors. Nature 323, 533\u2013536 (1986)","journal-title":"Nature"},{"key":"5_CR14","doi-asserted-by":"publisher","first-page":"136","DOI":"10.1016\/j.neunet.2012.04.011","volume":"33","author":"P Baldi","year":"2012","unstructured":"Baldi, P., Lu, Z.: Complex-valued autoencoders. Neural Netw. 33, 136\u2013147 (2012)","journal-title":"Neural Netw."},{"key":"5_CR15","unstructured":"Makhzani, A., Frey, B.: k-Sparse autoencoders. In: 2nd International Conference on Learning Representations, ICLR 2014 \u2013 Conference Track Proceedings (2014)"},{"key":"5_CR16","first-page":"455","volume-title":"Artificial Neural Network Models","author":"P Tino","year":"2015","unstructured":"Tino, P., Benuskova, L., Sperduti, A.: Artificial Neural Network Models, pp. 455\u2013471. Springer Handbook of Computational Intelligence (2015)"},{"issue":"6973","key":"5_CR17","doi-asserted-by":"publisher","first-page":"170","DOI":"10.1136\/bmj.310.6973.170","volume":"310","author":"JM Bland","year":"1995","unstructured":"Bland, J.M., Altman, D.G.: Multiple significance tests: the Bonferroni method. BMJ 310(6973), 170 (1995)","journal-title":"BMJ"}],"container-title":["Lecture Notes in Networks and Systems","17th International Conference on Soft Computing Models in Industrial and Environmental Applications (SOCO 2022)"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-18050-7_5","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,10,11]],"date-time":"2022-10-11T19:03:28Z","timestamp":1665515008000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-18050-7_5"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,10,12]]},"ISBN":["9783031180491","9783031180507"],"references-count":17,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-18050-7_5","relation":{},"ISSN":["2367-3370","2367-3389"],"issn-type":[{"type":"print","value":"2367-3370"},{"type":"electronic","value":"2367-3389"}],"subject":[],"published":{"date-parts":[[2022,10,12]]},"assertion":[{"value":"12 October 2022","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"SOCO","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Workshop on Soft Computing Models in Industrial and Environmental Applications","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Bilbao","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Spain","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2022","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"5 September 2022","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"7 September 2022","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"17","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"socomoin2022","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/2022.sococonference.eu\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}