Indian Journal of Science and Technology

Abstract

Objective: The Crude Oil industry plays a substantial role in the Philippine economy. The researchers intended to compare models of NARX Neural Network and Multiple Linear Regression through the forecast of the Crude Oil price in the Philippines (y) and prediction of the values from October 2018 to December 2023. Methods/Statistical Analysis: The researchers observed the behaviour of the factors that impact the Crude Oil price in the Philippines (y) and with the application of Multiple Linear Regression (MLR), concluded that among the factors, the substantial predictors are Inflation Rate (x₂ ), Consumption of Crude Oil (x₅), Import of Crude Oil (x₇) and Export of Crude Oil (x₈) while – Exchange rate (x₁), Consumer price index (x₃), Domestic interest rate (x₄) and Production of Crude Oil (x₆) are not. Also, NARX Neural Network was used to predict the Crude Oil prices in the Philippines from October 2018 to December 2023. Findings: Through using the NARX Neural Network, researchers were able to come up with the predicted Crude Oil prices in the Philippines and concluded that their behaviour fluctuates. Improvement: Novelty of work is NARX Neural Network which is the best-fitted model in predicting the Crude Oil price in the Philippines. Thus, predicted values are highly precise.

Keywords: Artificial Neural Network, Crude Oil Price in the Philippines, Forecasting Accuracy, Multiple Linear -Regression, NARX Neural Network