An ARIMA and XGBoost Model Utilized for Forecasting Municipal Solid Waste Generation
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Springer Nature Switzerland
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https://link.springer.com/content/pdf/10.1007/978-3-031-43838-7_2
Reference29 articles.
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2. Ahsan, M., Alamgir, M., El-Sergany, M., Shams, S., Rowshon, M.K., Nik, N.N.: Daud, assessment of municipal solid waste management system in a developing country. Chin. J. Eng. 11, 561935 (2014). https://doi.org/10.1155/2014/561935
3. Abdel-Shafy, H.I., Mansour, M.S.: Solid waste issue: Sources, composition, disposal, recycling, and valorization. Egypt. J. Petrol. 27(4), 1275–1290 (2018). ISSN 1110–0621, https://doi.org/10.1016/j.ejpe.2018.07.003
4. Jayaraman, V., Parthasarathy, S., Lakshminarayanan, A.R., Singh, H.K.: Predicting the quantity of municipal solid waste using XGBoost model. In: 2021 Third International Conference on Inventive Research in Computing Applications (ICIRCA), Coimbatore, India, pp. 148–152 (2021). https://doi.org/10.1109/ICIRCA51532.2021.9544094
5. van Beukering, P., et al.: Analysing Urban Solid Waste in Developing Counttries: a Perspective on Bangalore (India) (1999)
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