Results 81 to 90 of about 39,931 (297)
Dynamic multidimensional sensor data acquisition with adaptive Kalman filtering [PDF]
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information SciencesTraditional mobile sensing systems often experience a decline in data acquisition accuracy in dynamic environments due to the use of fixed-parameter Kalman filters, which lack adaptability to changes in motion states and sensor noise.
B. Yu
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Research on a High-Precision State-of-Charge Estimation Method Based on Forgetting Factor Recursive Least Squares and Adaptive Extended Kalman Filter Applied to LiFePO4 Battery [PDF]
, 2023 Yihui Xia +4 more
openalex +1 more source
A hidden Markov model and reinforcement learning‐based strategy for fault‐tolerant control
The Canadian Journal of Chemical Engineering, EarlyView.Abstract This study introduces a data‐driven control strategy integrating hidden Markov models (HMM) and reinforcement learning (RL) to achieve resilient, fault‐tolerant operation against persistent disturbances in nonlinear chemical processes. Called hidden Markov model and reinforcement learning (HMMRL), this strategy is evaluated in two case studies
Tamera Leitao +2 more
wiley +1 more source
An optimization approach to adaptive Kalman filtering
Automatica, 2009 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Karasalo, Maja, Hu, Xiaoming
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Bayesian inverse ensemble forecasting for COVID‐19
Canadian Journal of Statistics, EarlyView.Abstract Variations in strains of COVID‐19 have a significant impact on the rate of surges and on the accuracy of forecasts of the epidemic dynamics. The primary goal for this article is to quantify the effects of varying strains of COVID‐19 on ensemble forecasts of individual “surges.” By modelling the disease dynamics with an SIR model, we solve the ...
Kimberly Kroetch, Don Estep
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EnergiesIn this study, an improved adaptive robust unscented Kalman Filter (ARUKF) is proposed for an accurate state-of-charge (SOC) estimation of battery management system (BMS) in electric vehicles (EV). The extended Kalman Filter (EKF) algorithm is first used
Cheng Li, Gi-Woo Kim
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Investigation of the Multiple Method Adaptive Control (MMAC) method for flight control systems [PDF]
The stochastic adaptive control of the NASA F-8C digital-fly-by-wire aircraft using the multiple model adaptive control (MMAC) method is presented. The selection of the performance criteria for the lateral and the longitudinal dynamics, the design of the
Athans, M. +7 more
core +1 more source
Deep Underground Science and Engineering, EarlyView.This review synthesizes advances in predicting miners' vital signs by integrating environmental monitoring (dust, temperature, and gas) with physiological data. It highlights multi‐source data fusion techniques and early‐warning models for enhanced occupational safety in underground coal mines.
Junji Zhu +4 more
wiley +1 more source
DSGE Model Forecasting: Rational Expectations Versus Adaptive Learning
Journal of Forecasting, EarlyView.ABSTRACT This paper compares within‐sample and out‐of‐sample fit of a DSGE model with rational expectations to a model with adaptive learning. The Galí, Smets, and Wouters model is the chosen laboratory using quarterly real‐time euro area data vintages, covering 2001Q1–2019Q4.
Anders Warne
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Exact particle flow Daum-Huang filters for mobile robot localization in occupancy grid maps
Complex & Intelligent SystemsIn this paper, we present a novel localization algorithm for mobile robots navigating in complex planar environments, a critical capability for various real-world applications such as autonomous driving, robotic assistance, and industrial automation ...
Domonkos Csuzdi +3 more
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