This paper presents short-term forecasting model for crude oil prices based on three layer feedforward neural network. Careful attention was paid on finding the optimal network structure. Moreover, a number of features were tested as an inputs such as crude oil futures prices, dollar index, gold spot price, heating oil spot price and S&P 500 index. The results show that with adequate network design and appropriate selection of the training inputs, feedforward networks are capable of forecasting noisy time series with high accuracy
The global economy is assured to be very sensitive to the volatility of the oil market. The benefici...
Crude oil has an important role in the financial indicators of global markets and economies. The pri...
This paper proposes a novel approach, based on convolutional neural network (CNN) models, that forec...
This thesis examines the ability of Artificial Neural Networks (ANN) to predict crude oil spot price...
A new method based on integrating discrete wavelet transform and artificial neural networks (WANN) m...
When the literature regarding applications of neural networks is investigated, it appears that a sub...
Prediction of oil prices is an implausible task due to the multifaceted nature of oil markets. This ...
When the literature regarding applications of neural networks is investigated, it appears that a sub...
As the oil demand continues to surge ahead and production continues to decline, it is believed that ...
Crude oil is one of the most traded non-food products or commodities in the world. In Indonesia, cru...
In the long-term, crude oil prices may impact the economic stability and sustainability of many coun...
In the long-term, crude oil prices may impact the economic stability and sustainability of many coun...
In order to improve the accuracy of forecasting crude oil prices, a new crude oil price forecasting ...
This research studies the application of hybrid algorithms for predicting the prices of crude oil. B...
Crude oil has an important role in the financial indicators of global markets and economies. The pri...
The global economy is assured to be very sensitive to the volatility of the oil market. The benefici...
Crude oil has an important role in the financial indicators of global markets and economies. The pri...
This paper proposes a novel approach, based on convolutional neural network (CNN) models, that forec...
This thesis examines the ability of Artificial Neural Networks (ANN) to predict crude oil spot price...
A new method based on integrating discrete wavelet transform and artificial neural networks (WANN) m...
When the literature regarding applications of neural networks is investigated, it appears that a sub...
Prediction of oil prices is an implausible task due to the multifaceted nature of oil markets. This ...
When the literature regarding applications of neural networks is investigated, it appears that a sub...
As the oil demand continues to surge ahead and production continues to decline, it is believed that ...
Crude oil is one of the most traded non-food products or commodities in the world. In Indonesia, cru...
In the long-term, crude oil prices may impact the economic stability and sustainability of many coun...
In the long-term, crude oil prices may impact the economic stability and sustainability of many coun...
In order to improve the accuracy of forecasting crude oil prices, a new crude oil price forecasting ...
This research studies the application of hybrid algorithms for predicting the prices of crude oil. B...
Crude oil has an important role in the financial indicators of global markets and economies. The pri...
The global economy is assured to be very sensitive to the volatility of the oil market. The benefici...
Crude oil has an important role in the financial indicators of global markets and economies. The pri...
This paper proposes a novel approach, based on convolutional neural network (CNN) models, that forec...