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Forecasting ultimate resource recovery

✍ Scribed by M.Hashem Pesaran; Hossein Samiei

Book ID
113290688
Publisher
Elsevier Science
Year
1995
Tongue
English
Weight
972 KB
Volume
11
Category
Article
ISSN
0169-2070

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Global socio-economic data and solid waste composition for 28 international cities are utilized in developing regression models using multiple linear regression. The models are applied to forecast four recovery waste components: paper, metal, food and glass, which play an important role in the selec