LSTM-Based Forecasting for Urban Construction Waste Generation

LSTM-Based Forecasting for Urban Construction Waste Generation

Accurate forecasts of construction waste are important for recycling the waste and formulating relevant governmental policies. Deficiencies in reliable forecasting methods and historical data hinder the prediction of this waste in long- or short-term planning. To effectively forecast construction wa...

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Bibliographic Details
Main Authors: Li Huang, Ting Cai, Ya Zhu, Yuliang Zhu, Wei Wang, Kehua Sun
Format: Article
Language:English
Published: MDPI AG 2020-10-01
Series:Sustainability
Subjects:
environmental engineering
construction waste
short and long-term memory (LSTM) network
time-series forecasting
deep learning
Online Access:https://www.mdpi.com/2071-1050/12/20/8555

Internet

https://www.mdpi.com/2071-1050/12/20/8555

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