Machine Learning Algorithms for Oil Price Prediction
J Shiva Keerthan1, Y Nagasai2, Subhani Shaik3
1J Shiva Keerthan, Information Technology, Sreenidhi Institute of Science and Technology, Hyderabad, (Telangana), India.
2Y Nagasai, Information Technology, Sreenidhi Institute of Science and Technology, Hyderabad, (Telangana), India.
3Dr.Subhani Shaik, Associate Professor, Department of IT, Sreenidhi Institute of Science and Technology, Hyderabad, (Telangana), India.
Manuscript received on 02 June 2019 | Revised Manuscript received on 10 June 2019 | Manuscript published on 30 June 2019 | PP: 958-963 | Volume-8 Issue-8, June 2019 | Retrieval Number: G5696058719/19©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Crude oil is world’s most leading fuel. Some machine learning models fits the dataset efficiently depending upon the type of datapoints provided. The main aim of this project is to find the different models that efficiently fit the datapoints and predict the price of fuel with the help of machine learning model. This project aims to compare the different supervised learning models and bring a conclusion based on the efficiency. We have used 5 supervised learning models SVR(linear,RBF,polynomial),RandomForestRegressio-n,Linear Regression, to know which gives best in terms of accuracy and performance we have tried these algorithms which are mostly adaptive to many environments. Now-a-days the oil price has been increasing in leaps and bounds due to certain reason like inflation throughout the world. This has become a major problem in India where prices of LPG (Liquified Petroleum Gas), Petroleum, Diesel have been increasing. Hence these are derived or extracted from crude oil; India gets its source of crude oil from neighbouring countries like Dubai and Saudi-Arabia. To predict the values of the petroleum and Diesel in the mere future, we have decided to use the Machine Learning algorithms and after choosing set of algorithms we have chosen the Linear Regression algorithm, which have given the most accurate results.
Keyword: Prediction, Oil Prices, Machine Learning Models.
Scope of the Article: Machine Learning.