Forecasting the transport energy demand based on PLSR method in China
By M. Zhang, Hailin Mu, Gang Li, Yadong Ning. 2009
160 citations recorded by the source corpus.
Subfields: Automotive Engineering, Environmental Engineering, Renewable Energy, Sustainability and the Environment
View Paper: https://www.semanticscholar.org/paper/27d838cbada44db5a3010ad5bccba3a6fd2a073a
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In Automotive Engineering
In Environmental Engineering
In Renewable Energy, Sustainability and the Environment
Citations in the corpus
- An empirical study of direct rebound effect for passenger transport in urban China (2012, background): “During the past decades, a fleet of various passenger transport vehicles, fuel consumption and the demand for transportation services has really experienced great growth along with households' incomeand expenditure increase (Zhang et al., 2007, 2009).”
- Application of PSO (particle swarm optimization) and GA (genetic algorithm) techniques on demand est (2010, methodology): “Zhang et al. applied partial least square regression method to estimate transport energy demand in China [11].”
- Transport energy consumption and saving in China (2014, background): “Projection for China's transport energy demand [5].”
- Future energy use and CO2 emissions of urban passenger transport in China: A travel behavior and urban form based approach (2018, background): “Energy Consumption (tonnes of oil equivalent) Zhang, Mu [24], Hu, Chang [25],Ma, Lou [26],”