Estimating Physical Composition of Municipal Solid Waste in China by Applying Artificial Neural Network Method-Reference-Cited by-同舟云学术

Estimating Physical Composition of Municipal Solid Waste in China by Applying Artificial Neural Network Method

Published:2020-07-06 Issue:15 Volume:54 Page:9609-9617
ISSN:0013-936X
Container-title:Environmental Science & Technology
language:en
Short-container-title:Environ. Sci. Technol.

Author:

Ma Shijun¹²,Zhou Chuanbin¹²^ORCID,Chi Ce³,Liu Yijie¹,Yang Guang¹²

Affiliation:

1. State Key Laboratory of Urban and Regional Ecology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China

2. University of Chinese Academy of Sciences, Beijing 100049, China

3. High Performance Computer Research Center, Institute of Computing Technology, Chinese Academy of Sciences, Beijing 100089, China

Funder

Ministry of Science and Technology of the People's Republic of China

Youth Innovation Promotion Association of the Chinese Academy of Sciences

National Natural Science Foundation of China

Publisher

American Chemical Society (ACS)

Subject

Environmental Chemistry,General Chemistry

Link

https://pubs.acs.org/doi/pdf/10.1021/acs.est.0c01802

Reference59 articles.

1. Statistical analysis of solid waste composition data: Arithmetic mean, standard deviation and correlation coefficients

2. Estimates of solid waste disposal rates and reduction targets for landfill gas emissions

3. Case study on prediction of remaining methane potential of landfilled municipal solid waste by statistical analysis of waste composition data

4. Modeling the carbon cycle of the municipal solid waste management system for urban metabolism

5. Gasification characteristics of MSW and an ANN prediction model

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