In the oil and gas industry, energy prediction can help the distributor and customer to forecast the outgoing and incoming gas through the pipeline. It will also help to eliminate any uncertainties in gas metering for billing purposes. The objective of this paper is to develop Neural Network Model for energy consumption and analyze the performance model. This paper provides a comprehensive review on published research on the energy consumption prediction which focuses on structures and the parameters used in developing Neural Network models. This paper is then focused on the parameter selection of the neural network prediction model development for energy consumption and analysis on the result. The most reliable model that gives the most ac...
Under the supervision of Professors William Beckman, Sandford Klein, and John Mitchell; 160pp.The wo...
Machine learning (ML) methods has recently contributed very well in the advancement of the predictio...
The analysis of a time series is a problem well known to statisticians. Neural networks form the bas...
Natural gas is transported to consumers via pipelines. The outgoing gas flow along the pipelines is...
Abstract: Energy consumption has been increasing steadily due to globalization and industrialization...
Neural networks for the real world applications are increasing rapidly. Artificial Neural Network i...
The paper proposes the solution to the problem of forecasting the power load for various gas industr...
Accurate measurement of temperature, pressure and volume in a gas metering stations is an important...
International audienceThe increasing global demand for electrical energy coupled with rise in cost o...
The prediction of energy consumption is of great significance to the stability of the regional energ...
The energy management of electrical machine is significant to ensure efficient power consumption. Mi...
The tremendous rise of electrical energy demand worldwide has led to many problems related to effici...
The paper illustrates an artificial neural network (ANN) approach based on supervised neural network...
Fuel consumption are important in every vehicle. This study investigates the performance of fuel usa...
Accurate baseline energy models demand increase significantly as it lower the risk of energy savings...
Under the supervision of Professors William Beckman, Sandford Klein, and John Mitchell; 160pp.The wo...
Machine learning (ML) methods has recently contributed very well in the advancement of the predictio...
The analysis of a time series is a problem well known to statisticians. Neural networks form the bas...
Natural gas is transported to consumers via pipelines. The outgoing gas flow along the pipelines is...
Abstract: Energy consumption has been increasing steadily due to globalization and industrialization...
Neural networks for the real world applications are increasing rapidly. Artificial Neural Network i...
The paper proposes the solution to the problem of forecasting the power load for various gas industr...
Accurate measurement of temperature, pressure and volume in a gas metering stations is an important...
International audienceThe increasing global demand for electrical energy coupled with rise in cost o...
The prediction of energy consumption is of great significance to the stability of the regional energ...
The energy management of electrical machine is significant to ensure efficient power consumption. Mi...
The tremendous rise of electrical energy demand worldwide has led to many problems related to effici...
The paper illustrates an artificial neural network (ANN) approach based on supervised neural network...
Fuel consumption are important in every vehicle. This study investigates the performance of fuel usa...
Accurate baseline energy models demand increase significantly as it lower the risk of energy savings...
Under the supervision of Professors William Beckman, Sandford Klein, and John Mitchell; 160pp.The wo...
Machine learning (ML) methods has recently contributed very well in the advancement of the predictio...
The analysis of a time series is a problem well known to statisticians. Neural networks form the bas...