An AI-Agent-Based Trapezoidal Fuzzy Ensemble Forecasting Model for Crude Oil Price Prediction

In this study, a Al-agent-based trapezoidal fuzzy ensemble forecasting model is proposed for crude oil price prediction. In the proposed ensemble model, some single AI models are first used as predictors for crude oil price prediction. Then these single prediction results produced by the single Al-based predictors are fuzzified into some fuzzy prediction representations. Subsequently, these fuzzified representations are fused into a fuzzy consensus, i.e., aggregated fuzzy prediction. Finally, the aggregated prediction is defuzzified into a crisp value as the final prediction results. For testing purposes, two typical crude oil price prediction experiments are presented.