{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,15]],"date-time":"2026-04-15T23:57:21Z","timestamp":1776297441248,"version":"3.50.1"},"publisher-location":"Cham","reference-count":28,"publisher":"Springer Nature Switzerland","isbn-type":[{"value":"9783032193421","type":"print"},{"value":"9783032193438","type":"electronic"}],"license":[{"start":{"date-parts":[[2026,1,1]],"date-time":"2026-01-01T00:00:00Z","timestamp":1767225600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2026,1,1]],"date-time":"2026-01-01T00:00:00Z","timestamp":1767225600000},"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":[[2026]]},"DOI":"10.1007\/978-3-032-19343-8_11","type":"book-chapter","created":{"date-parts":[[2026,4,15]],"date-time":"2026-04-15T23:19:08Z","timestamp":1776295148000},"page":"170-186","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["A Comparative Analysis of\u00a0Prediction Intervals for\u00a0Forecasting in\u00a0the\u00a0Recycling Sector"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0009-0004-0694-590X","authenticated-orcid":false,"given":"Jakob","family":"Becker","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1005-9351","authenticated-orcid":false,"given":"Andrea","family":"Bommert","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6023-8921","authenticated-orcid":false,"given":"Jakob","family":"Rehof","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0976-7190","authenticated-orcid":false,"given":"Markus","family":"Pauly","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2026,4,1]]},"reference":[{"key":"11_CR1","doi-asserted-by":"crossref","unstructured":"Abdeljaber, A., Al Smadi, S., Abu Talib, M., Abdallah, M.: Comparative analysis of machine learning and conventional methods for waste generation forecasting. Cleaner Eng. Technol. 27 (2025)","DOI":"10.1016\/j.clet.2025.100992"},{"issue":"1","key":"11_CR2","doi-asserted-by":"publisher","first-page":"300","DOI":"10.32614\/RJ-2022-012","volume":"14","author":"C Alakus","year":"2022","unstructured":"Alakus, C., Larocque, D., Labbe, A.: RFpredInterval: an R package for prediction intervals with random forests and boosted forests. R J. 14(1), 300\u2013320 (2022)","journal-title":"R J."},{"key":"11_CR3","doi-asserted-by":"crossref","unstructured":"Alhathlaul, N., et al.: Assessing waste management using machine learning forecasting for sustainable development goal driven. Sustainability 17(19) (2025)","DOI":"10.3390\/su17198654"},{"issue":"2","key":"11_CR4","doi-asserted-by":"publisher","first-page":"1148","DOI":"10.1214\/18-AOS1709","volume":"47","author":"S Athey","year":"2019","unstructured":"Athey, S., Tibshirani, J., Wager, S.: Generalized random forests. Ann. Stat. 47(2), 1148\u20131178 (2019)","journal-title":"Ann. Stat."},{"key":"11_CR5","unstructured":"Auto\u2013Etymology & Meaning of the Prefix. https:\/\/www.etymonline.com\/word\/auto-. Accessed 19 Sept 2025"},{"key":"11_CR6","unstructured":"Becker, J., Kempkes, P., Mielke, K., Fendel, A., Bommert, A., Pauly, M.: Forecasting plastic waste fractions: a recycling perspective. In: Proceedings of the Conference on Production Systems and Logistics: CPSL 2025, pp. 494\u2013508. publish-Ing. Offenburg (2025)"},{"key":"11_CR7","doi-asserted-by":"publisher","first-page":"5","DOI":"10.1023\/A:1010933404324","volume":"45","author":"L Breiman","year":"2001","unstructured":"Breiman, L.: Random forest. Mach. Learn. 45, 5\u201332 (2001)","journal-title":"Mach. Learn."},{"key":"11_CR8","volume-title":"Classification and Regression Trees","author":"L Breiman","year":"1984","unstructured":"Breiman, L., Friedman, F., Olshen, R.A., Stone, C.J.: Classification and Regression Trees, 1st edn. Chapman and Hall\/CRC, New York (1984)","edition":"1"},{"key":"11_CR9","doi-asserted-by":"crossref","unstructured":"Dooley, S., Khurana, G.S., Mohapatra, C., Naidu, S., White, C.: ForecastPFN: synthetically-trained zero-shot forecasting. In: Proceedings of the Conference on Neural Information Processing Systems (NeurIPS) (2023)","DOI":"10.52202\/075280-0112"},{"issue":"1","key":"11_CR10","doi-asserted-by":"publisher","first-page":"233","DOI":"10.3390\/app11010233","volume":"11","author":"S Gallego-Garc\u00eda","year":"2021","unstructured":"Gallego-Garc\u00eda, S., Garc\u00eda-Garc\u00eda, M.: Predictive sales and operations planning based on a statistical treatment of demand to increase efficiency: a supply chain simulation case study. Appl. Sci. 11(1), 233 (2021)","journal-title":"Appl. Sci."},{"key":"11_CR11","unstructured":"Goal 12 | Department of Economic and Social Affairs. https:\/\/sdgs.un.org\/goals\/goal12#targets_and_indicators. Accessed 11 Sept 2025"},{"key":"11_CR12","doi-asserted-by":"publisher","first-page":"195","DOI":"10.1016\/j.ejor.2009.12.020","volume":"205","author":"P Goodwin","year":"2010","unstructured":"Goodwin, P., \u00d6nkal, D., Thomson, M.: Do forecasts expressed as prediction intervals improve production planning decisions? Eur. J. Oper. Res. 205, 195\u2013201 (2010)","journal-title":"Eur. J. Oper. Res."},{"key":"11_CR13","doi-asserted-by":"publisher","DOI":"10.1007\/978-0-387-84858-7","volume-title":"The Elements of Statistical Learning","author":"T Hastie","year":"2009","unstructured":"Hastie, T., Tibshirani, R., Friedman, J.: The Elements of Statistical Learning, 2nd edn. Springer, New York (2009)","edition":"2"},{"key":"11_CR14","unstructured":"Hollmann, N., M\u00fcller, S., Eggensperger, K., Hutter, F.: TabPFN: a transformer that solves small tabular classification problems in a second. In: Proceedings of the International Conference on Learning Representations (2023)"},{"key":"11_CR15","doi-asserted-by":"publisher","unstructured":"Hollmann, N., et al.: Accurate predictions on small data with a tabular foundation model. Nature 637, 319\u2013326 (2025). https:\/\/doi.org\/10.1038\/s41586-024-08328-6","DOI":"10.1038\/s41586-024-08328-6"},{"key":"11_CR16","unstructured":"Hyndman, R.J., Athanasopoulos, G.: Forecasting: Principles and Practice. 3rd edn. OTexts, Melbourne, Australia (2021). https:\/\/OTexts.com\/fpp3. Accessed 31 Aug 2025"},{"key":"11_CR17","doi-asserted-by":"publisher","first-page":"361","DOI":"10.1080\/00031305.1996.10473566","volume":"50","author":"RJ Hyndman","year":"1996","unstructured":"Hyndman, R.J., Fan, Y.: Sample quantiles in statistical packages. Am. Stat. 50, 361\u2013365 (1996)","journal-title":"Am. Stat."},{"issue":"35","key":"11_CR18","first-page":"983","volume":"7","author":"N Meinshausen","year":"2006","unstructured":"Meinshausen, N.: Quantile regression forests. J. Mach. Learn. Res. 7(35), 983\u2013999 (2006)","journal-title":"J. Mach. Learn. Res."},{"key":"11_CR19","doi-asserted-by":"crossref","unstructured":"Mudannayake, O., Rathnayake, D., Herath, J.D., Fernando, D.K., Fernando, M.: Exploring machine learning and deep learning approaches for multi-step forecasting in municipal solid waste generation. IEEE Access 10, 122570\u2013122585 (2022)","DOI":"10.1109\/ACCESS.2022.3221941"},{"key":"11_CR20","doi-asserted-by":"crossref","unstructured":"Opara, I.K, Silue, Y., Opara, U.L., Fawole, O.A.: Forecasting of postharvest fresh produce waste at the wholesale level using time series models. Agric. Food Secur. 14(1) (2025)","DOI":"10.1186\/s40066-025-00550-3"},{"key":"11_CR21","doi-asserted-by":"publisher","unstructured":"Oroye, O.A, Akintade, J.V., Oroye, B.E.: Waste generation forecast and prediction analysis using exponential smoothing model. In: IEEE 5th International Conference on Electro-Computing Technologies for Humanity 2024, NIGERCON, pp. 1\u20135 (2024). https:\/\/doi.org\/10.1109\/NIGERCON62786.2024.10927015","DOI":"10.1109\/NIGERCON62786.2024.10927015"},{"key":"11_CR22","unstructured":"Plastic waste and recycling in the EU: facts and figures | Topics | European Parliament. https:\/\/www.europarl.europa.eu\/topics\/en\/article\/20181212STO21610\/plastic-waste-and-recycling-in-the-eu-facts-and-figures. Accessed 10 Sept 2025"},{"key":"11_CR23","doi-asserted-by":"publisher","first-page":"49","DOI":"10.1016\/j.spl.2019.03.017","volume":"151","author":"B Ramosaj","year":"2019","unstructured":"Ramosaj, B., Pauly, M.: Consistent estimation of residual variance with random forest Out-of-Bag errors. Stat. Probab. Lett. 151, 49\u201357 (2019)","journal-title":"Stat. Probab. Lett."},{"key":"11_CR24","unstructured":"The Comprehensive R Archive Network. https:\/\/cran.r-project.org\/. Accessed 1 Oct 2025"},{"key":"11_CR25","unstructured":"The Plastic Recycling Process - Association of Plastic Recyclers (APR). https:\/\/plasticsrecycling.org\/how-recycling-works\/the-plastic-recycling-process\/. Accessed 11 Sept 2025"},{"key":"11_CR26","unstructured":"THE 17 GOALS | Sustainable Development. https:\/\/sdgs.un.org\/goals. Accessed 11 Sept 2025"},{"issue":"4","key":"11_CR27","first-page":"1","volume":"74","author":"H Zhang","year":"2019","unstructured":"Zhang, H., Zimmerman, J., Nettleton, D., Nordman, D.J.: Random forest prediction intervals. Am. Stat. 74(4), 1\u201320 (2019)","journal-title":"Am. Stat."},{"key":"11_CR28","unstructured":"41% of plastic packaging waste recycled in 2022 - News articles - Eurostat. https:\/\/ec.europa.eu\/eurostat\/web\/products-eurostat-news\/w\/ddn-20241024-3. Accessed 10 Sept 2025"}],"container-title":["Lecture Notes in Logistics","Dynamics in Logistics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-032-19343-8_11","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,4,15]],"date-time":"2026-04-15T23:19:10Z","timestamp":1776295150000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-032-19343-8_11"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026]]},"ISBN":["9783032193421","9783032193438"],"references-count":28,"URL":"https:\/\/doi.org\/10.1007\/978-3-032-19343-8_11","relation":{},"ISSN":["2194-8917","2194-8925"],"issn-type":[{"value":"2194-8917","type":"print"},{"value":"2194-8925","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026]]},"assertion":[{"value":"1 April 2026","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"The authors have no competing interests to declare that\u00a0are relevant to the content of this article.","order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Disclosure of Interests"}},{"value":"LDIC","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Dynamics in Logistics","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Bremen","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Germany","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2026","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"25 February 2026","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"27 February 2026","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"10","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"ldic2026","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/www.ldic-conference.org\/program\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}