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Forecasting medical waste generation using short and extra short datasets: Case study of Lithuania
2016
Waste Management & Research
There were 1.83 million cars and average passenger car age was 18 years in Lithuania in 2013. Increasing number of cars has an insignificant effect on car age change but it is contrary to automotive waste, both hazardous and non-hazardous, that accumulates during vehicle exploitation and after it ends. The aim of this study was to assess different mathematical modelling methods abilities to forecast non-hazardous and hazardous automotive waste generation. Artificial neural networks, multiple
doi:10.1177/0734242x16628977
pmid:26879908
fatcat:rrhgoitn55bspiw55hlxiip66a