Trade Forecasting Withai: Integrating Machine Learning, Deeplearning, and Explainabilityforcrude Oil Price Prediction
Year: 2025
Type: conference-paper
Abstract: Crude oil price prediction remains a challenging task due to volatile market conditions. Traditional models often fail to adjust, while modern AI models like LSTMcan find patterns but are hard to explain. This study combines Machine Learning (Random Forest), Deep Learning (LSTM), and explainability tools (SHAP and LIME). This study aims to develop a model that is both accurate and easy to understand. The results exhibit that the combined model of ers better accuracy and trust for decision-making.
Authors: Balasubramanian S, Natarajan M
Language: English
Field: Decision Sciences
Domain: Social Sciences
Open Access status: gold
OpenAlex ID: W4413475767