Results 161 to 170 of about 8,393,375 (379)

Random Learning Leads to Faster Convergence in ‘Model‐Free’ ILC: With Application to MIMO Feedforward in Industrial Printing

International Journal of Adaptive Control and Signal Processing, EarlyView.
The cost as a function of the number of experiments for a non‐symmetric 21×21$$ 21\times 21 $$ system. Four approaches are shown: the proposed stochastic conjugate gradient ILC (SCGILC) method (), deterministic conjugate gradient ILC (), stochastic gradient descent ILC () and deterministic gradient descent ILC ().
Leontine Aarnoudse, Tom Oomen
wiley   +1 more source

Propagating Model Uncertainty through Filtering-based Probabilistic Numerical ODE Solvers [PDF]

arXiv
Filtering-based probabilistic numerical solvers for ordinary differential equations (ODEs), also known as ODE filters, have been established as efficient methods for quantifying numerical uncertainty in the solution of ODEs. In practical applications, however, the underlying dynamical system often contains uncertain parameters, requiring the ...
arxiv  

Performance Triggered Adaptive Model Reduction for Soil Moisture Estimation in Precision Irrigation

International Journal of Adaptive Control and Signal Processing, EarlyView.
ABSTRACT Accurate soil moisture information is essential for precise irrigation to enhance water use efficiency. Estimating soil moisture based on limited soil moisture sensors is especially critical for obtaining comprehensive soil moisture information when dealing with large‐scale agricultural fields.
Sarupa Debnath, Bernard Twum Agyeman, Soumya Ranjan Sahoo, Xunyuan Yin, Jinfeng Liu   +4 more
wiley   +1 more source

Parameter uncertainty and sensitivity in a liquid-effluent dose model [PDF]

, 1995
T. C. Hyman, D.M. Hamby
openalex   +1 more source

Bayesian regression explains how human participants handle parameter uncertainty. [PDF]

PLoS Comput Biol, 2020
Jegminat J, Jastrzębowska MA, Pachai MV, Herzog MH, Pfister JP.   +4 more
europepmc   +1 more source

Neural Network Adaptive Control With Long Short‐Term Memory

International Journal of Adaptive Control and Signal Processing, EarlyView.
ABSTRACT In this study, we propose a novel adaptive control architecture that provides dramatically better transient response performance compared to conventional adaptive control methods. This is accomplished by the synergistic employment of a traditional adaptive neural network (ANN) controller and a long short‐term memory (LSTM) network.
Emirhan Inanc, Abdullah Habboush, Yigit Gurses, Yildiray Yildiz, Anuradha M. Annaswamy   +4 more
wiley   +1 more source

Optimization in a Class of Distributed Parameter Systems under Uncertainty

, 1972
Naonori Nishida, Eiichiro TAZAKI
openalex   +2 more sources

Impacts of Parameter Uncertainty and Seasonal Variation on a Regional Model [PDF]

, 1999
Benjamin Sherman, Mark J. TenBroek
openalex   +1 more source

A Case‐Based Reasoning Approach to Model Manufacturing Constraints for Impact Extrusion

Advanced Engineering Materials, EarlyView.
A hybrid modeling approach is presented that combines constraint‐based process modeling and case‐based reasoning. The model formalizes manufacturing constraints and integrates simulation data to model complex manufacturing processes. The approach supports manufacturability analysis during product design through an adaptive modeling environment.
Kevin Herrmann, Eduard Ortlieb, Hendrik Wester, Paul Christoph Gembarski, Bernd‐Arno Behrens, Roland Lachmayer   +5 more
wiley   +1 more source

Solving the Robust Shortest Path Problem with Multimodal Transportation

Mathematics
This paper explores the challenges of finding robust shortest paths in multimodal transportation networks. With the increasing complexity and uncertainties in modern transportation systems, developing efficient and reliable routing strategies that can ...
Jinzuo Guo, Tianyu Liu, Guopeng Song, Bo Guo   +3 more
doaj   +1 more source