Filter Method Feature Selection Techniques for Solid Waste Prediction Based on GRU Deep Learning Model
Author:
Publisher
Springer Nature Switzerland
Link
https://link.springer.com/content/pdf/10.1007/978-3-031-66965-1_30
Reference12 articles.
1. Municipal Solid Waste Management: https://www.gminsights.com/industry/analysis/municipal-solid-waste-management-market. Accessed 01 june 2023
2. BoranWu, D.: Detection of long-term effect in forecasting municipal solid waste using a long short-term memory neural network. J. Clean. Prod. (2020). https://doi.org/10.1016/j.jclepro.2020.125187
3. Kenneth, K., Adusei, K.T.W.N., Mahmud, T.S., Karimi, N., Lakhan, C.: Exploring the use of astronomical seasons in municipal solid waste disposal rates modeling. Sustainable Cities and Society 86, 104115 (2022). ISSN 2210-6707
4. Liu, B., Zhang, L., Wang, Q.: Demand gap analysis of municipal solid waste landfill in Beijing: Based on the municipal solid waste generation. Waste Management 134, 42–51 (2021)
5. Cubillos, M.: Multi-site household waste generation forecasting using a deep learning approach. Waste Manage. 115, 8–14 (2020)
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