2022
DOI: 10.1007/s44196-021-00060-7
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Self-organizing Maps and Bayesian Regularized Neural Network for Analyzing Gasoline and Diesel Price Drifts

Abstract: Any nation’s growth depends on the trend of the price of fuel. The fuel price drifts have both direct and indirect impacts on a nation’s economy. Nation’s growth will be hampered due to the higher level of inflation prevailing in the oil industry. This paper proposed a method of analyzing Gasoline and Diesel Price Drifts based on Self-organizing Maps and Bayesian regularized neural networks. The US gasoline and diesel price timeline dataset is used to validate the proposed approach. In the dataset, all grades,… Show more

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Cited by 7 publications
(1 citation statement)
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“…Because of the greater degree of inflation in the oil business, a nation’s economy will be limited. The neural networks are trained using three different training algorithms: Levenberg–Marquardt, SCG and Bayesian regularisation [ 11 ]. The location of the mine pit will be the sub-groundwater level as mining depth increases.…”
Section: Related Workmentioning
confidence: 99%
“…Because of the greater degree of inflation in the oil business, a nation’s economy will be limited. The neural networks are trained using three different training algorithms: Levenberg–Marquardt, SCG and Bayesian regularisation [ 11 ]. The location of the mine pit will be the sub-groundwater level as mining depth increases.…”
Section: Related Workmentioning
confidence: 99%