Load angle estimation process of the operating synchronous generator on power system is defined based dynamic neural networks. In forming model choice input values and structures network explored defined. Data from recorded responses to at standard conditions malfunctioning a are used for learning network. The comparison results obtained using method load with by measurement, reveals applicabil...

Substantial advancements in markerless motion capture accuracy exist, but discrepancies persist when measuring joint angles compared to those taken with a goniometer. This study integrates machine learning techniques capture, an aim enhance this accuracy. Two artificial intelligence-based libraries—MediaPipe and LightGBM—were employed executing shoulder abduction angle estimation. The of ten he...

Abstract We propose a state estimation approach to time-varying magnetic resonance imaging utilizing priori information. In estimation, the time-dependent image reconstruction problem is modeled by separate evolution and observation models. our method, we compute estimates using Kalman filter steady-state smoother data-driven estimate for process noise covariance matrix, constructed from conven...

Abstract Accurate vehicular trajectory estimation is important for the recently developed autonomous driving systems. As accuracy of reduced with slippage that occurs during turning, we propose a method in this study to accurately estimate vehicle, focusing on slip angle estimation. Although two-wheel model used as general concept estimation, accurate parameters was difficult using conventional...