Junzhe Shi

Granular Framework for Construction Material Price Forecasting: Econometric and Machine-Learning Approaches

Abstract The persistent volatility of construction material prices poses significant risks to cost estimation, budgeting, and project delivery, underscoring the urgent need for granular and scalable forecasting methods. This study develops a forecasting framework that leverages t...

Mitigating overconfidence in nonlinear Kalman filters via covariance recalibration

The Kalman filter (KF) is an optimal linear state estimator for linear systems, and numerous extensions, including the extended Kalman filter (EKF), unscented Kalman filter (UKF), and cubature Kalman filter (CKF), have been developed for nonlinear systems. Although these nonlinea...