An effective rolling decomposition-ensemble model for gasoline consumption forecasting
Sign Up to like & getrecommendations! Published in 2021 at "Energy"
DOI: 10.1016/j.energy.2021.119869
Abstract: Abstract In this paper, an effective rolling decomposition-ensemble model is proposed for quarterly gasoline consumption forecasting in China. In this model, three steps, data decomposition, component prediction and ensemble output, are involved. In the data… read more here.
Keywords: decomposition ensemble; decomposition; rolling decomposition; model ... See more keywords
Impact of Covid-19 outbreak on Turkish gasoline consumption
Sign Up to like & getrecommendations! Published in 2020 at "Technological Forecasting and Social Change"
DOI: 10.1016/j.techfore.2021.120637
Abstract: This paper investigates the effects of COVID-19 outbreak on Turkish gasoline market by employing daily gasoline consumption data covering 2014-2020 periods The read more here.
Keywords: turkish gasoline; covid outbreak; gasoline; outbreak turkish ... See more keywords
Asymmetric price effects on gasoline consumption: evidence and Implications
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DOI: 10.1080/13504851.2019.1610700
Abstract: ABSTRACT The increased volatility of gasoline prices in the last 10 years has renewed the interest in how gasoline demand responds to new changes. Using recent urban household survey and Metropolitan Statistical Areas (MSA) level… read more here.
Keywords: effects gasoline; gasoline prices; price; gasoline ... See more keywords
A Two-Level Model for Traffic Signal Timing and Trajectories Planning of Multiple CAVs in a Random Environment
Sign Up to like & getrecommendations! Published in 2021 at "Journal of Advanced Transportation"
DOI: 10.1155/2021/9945398
Abstract: Connected and automated vehicles (CAVs) trajectories not only provide more real-time information by vehicles to infrastructure but also can be controlled and optimized, to further save travel time and gasoline consumption. This paper proposes a… read more here.
Keywords: traffic; traffic signal; two level; time ... See more keywords