@article{(Open Science Index):https://publications.waset.org/pdf/12881,
	  title     = {Development of Neural Network Prediction Model of Energy Consumption},
	  author    = {Maryam Jamela Ismail and  Rosdiazli Ibrahim and  Idris Ismail},
	  country	= {},
	  institution	= {},
	  abstract     = {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 accurate
result is proposed for the prediction. The result shows that the
proposed neural network energy prediction model is able to
demonstrate an adequate performance with least Root Mean Square
Error.},
	    journal   = {International Journal of Energy and Power Engineering},
	  volume    = {5},
	  number    = {10},
	  year      = {2011},
	  pages     = {1367 - 1372},
	  ee        = {https://publications.waset.org/pdf/12881},
	  url   	= {https://publications.waset.org/vol/58},
	  bibsource = {https://publications.waset.org/},
	  issn  	= {eISSN: 1307-6892},
	  publisher = {World Academy of Science, Engineering and Technology},
	  index 	= {Open Science Index 58, 2011},
	}