Description:
As the oil demand continues to surge ahead and production continues to decline, it is believed that oil prices will continue to rise to unprecedented levels. As a reference, in 2004, the crude oil price was averaging $41 per barrel while it is above $130 in today’s market. This oil price increase is affecting the economy from both developing and developed countries. This paper investigates the possibility of using oil futures price to forecast spot price direction for short term, one day ahead using multilayer feedforward neural networks. The data was pre-processed to reflect the direction and the turning point of the price. Our approach is to create a benchmark based on lagged value of pre-processed spot price, then add pre-processed futures prices 1, 2, 3 and 4 months for maturity one by one and also altogether. For all the experiments, that include futures data as an input, the results show that on the short term, one day ahead, there is weak evidence to support futures price do hold new information on the spot price direction. This evidence is stronger for futures 1, 2 months to maturity.
Description:
As the oil demand continues to surge ahead and production continues to decline, it is believed that oil prices will continue to rise to unprecedented levels. As a reference, in 2004, the crude oil price was averaging $41 per barrel while it is above $130 in today’s market. This oil price increase is affecting the economy from both developing and developed countries. This paper investigates the possibility of using oil futures price to forecast spot price direction for short term, one day ahead using multilayer feedforward neural networks. The data was pre-processed to reflect the direction and the turning point of the price. Our approach is to create a benchmark based on lagged value of pre-processed spot price, then add pre-processed futures prices 1, 2, 3 and 4 months for maturity one by one and also altogether. For all the experiments, that include futures data as an input, the results show that on the short term, one day ahead, there is weak evidence to support futures price do hold new information on the spot price direction. This evidence is stronger for futures 1, 2 months to maturity.
Description:
In the present research work, a neural network model has been developed to predict the exhaust emissions and performance of a compression ignition engine. The significance and novelty of the work, with respect to existing literature, is the application of sensitivity analysis and an artificial neural network (ANN) simultaneously in order to predict the engine parameters. The inputs of the model were engine load (0, 25, 50, 75 and 100%), engine speed (1700, 2100, 2500 and 2900 rpm) and the percent of biodiesel fuel derived from waste cooking oil in diesel fuel (B0, B5, B10, B15 and B20). The relationship between the input parameters and engine cylinder performance and emissions can be determined by the network. The global sensitivity analysis results show that all the investigated factors are effective on the created model and cannot be ignored. In addition, it is found that the most emissions decreased while using biodiesel fuel in the compression ignition engine.
Description:
In the present research work, a neural network model has been developed to predict the exhaust emissions and performance of a compression ignition engine. The significance and novelty of the work, with respect to existing literature, is the application of sensitivity analysis and an artificial neural network (ANN) simultaneously in order to predict the engine parameters. The inputs of the model were engine load (0, 25, 50, 75 and 100%), engine speed (1700, 2100, 2500 and 2900 rpm) and the percent of biodiesel fuel derived from waste cooking oil in diesel fuel (B0, B5, B10, B15 and B20). The relationship between the input parameters and engine cylinder performance and emissions can be determined by the network. The global sensitivity analysis results show that all the investigated factors are effective on the created model and cannot be ignored. In addition, it is found that the most emissions decreased while using biodiesel fuel in the compression ignition engine.