@article{(Open Science Index):https://publications.waset.org/pdf/10008992,
	  title     = {Crude Oil Price Prediction Using LSTM Networks},
	  author    = {Varun Gupta and  Ankit Pandey},
	  country	= {},
	  institution	= {},
	  abstract     = {Crude oil market is an immensely complex and dynamic environment and thus the task of predicting changes in such an environment becomes challenging with regards to its accuracy. A number of approaches have been adopted to take on that challenge and machine learning has been at the core in many of them. There are plenty of examples of algorithms based on machine learning yielding satisfactory results for such type of prediction. In this paper, we have tried to predict crude oil prices using Long Short-Term Memory (LSTM) based recurrent neural networks. We have tried to experiment with different types of models using different epochs, lookbacks and other tuning methods. The results obtained are promising and presented a reasonably accurate prediction for the price of crude oil in near future.
},
	    journal   = {International Journal of Computer and Information Engineering},
	  volume    = {12},
	  number    = {3},
	  year      = {2018},
	  pages     = {226 - 230},
	  ee        = {https://publications.waset.org/pdf/10008992},
	  url   	= {https://publications.waset.org/vol/135},
	  bibsource = {https://publications.waset.org/},
	  issn  	= {eISSN: 1307-6892},
	  publisher = {World Academy of Science, Engineering and Technology},
	  index 	= {Open Science Index 135, 2018},
	}