Associate Professor, Dept. of IT, PSG college of Technology, Coimbatore, TN, India
Software Engineer, Netlink digital solution, Chennai, TN, India
Petroleum plays a vital role in the economy of our country. It is one of the important sources of the energy and act as vital raw material for a number of industries. Every economic sector in the world is dependent on crude oil, any increase or decrease in the price of crude oil has a ripple effect on the global economy. Hence accurately predicting the price petroleum become the hot issues in many countries around the world. To grasp the trend of petroleum price and reduce the negative impact of petroleum price changes. In this paper a new improved hybrid model is proposed by combining Particle Swarm Optimization (PSO) and Back Propagation (BP)-Artificial Neural Network(ANN) techniques to predict the oil price.