3 papers
cs.LG2025
State Estimation Using Particle Filtering in Adaptive Machine Learning Methods: Integrating Q-Learning and NEAT Algorithms with Noisy Radar Measurements
Wonjin Song, Feng Bao
Reliable state estimation is essential for autonomous systems operating in complex, noisy environments. Classical filtering approaches, such as the Kalman filter, can struggle when…
math.NA2025
Joint State-Parameter Estimation for the Reduced Fracture Model via the United Filter
Toan Huynh, Thi-Thao-Phuong Hoang, Guannan Zhang +1
In this paper, we introduce an effective United Filter method for jointly estimating the solution state and physical parameters in flow and transport problems within fractured poro…
math.NA2024
Parameter Estimation for the Reduced Fracture Model via a Direct Filter Method
Phuoc Toan Huynh, Feng Bao, Thi-Thao-Phuong Hoang
In this work, we present a numerical method that provides accurate real-time detection for the widths of the fractures in a fractured porous medium based on observational data on p…