Results 21 to 30 of about 15,092,034 (255)

Adaptive Neural Network Control for Exoskeleton Motion Rehabilitation Robot With Disturbances and Uncertain Parameters

IEEE Access, 2023
This paper investigates the adaptive control problem for a class of Euler-Lagrangian (EL) systems with uncertain parameters and external disturbances.
Bowen Zhang, Tong Wu, Tianqi Wang
doaj   +1 more source

An Entropic Approach for Pair Trading

Entropy, 2017
In this paper, we derive the optimal boundary for pair trading. This boundary defines the points of entry into or exit from the market for a given stock pair.
Daisuke Yoshikawa
doaj   +1 more source

Model Uncertainty in the Projected Indian Summer Monsoon Precipitation Change under Low-Emission Scenarios

Atmosphere, 2021
The projected ISM precipitation changes under low-emission scenarios, Representative Concentration Pathway 2.6 (RCP2.6) and Shared Socioeconomic Pathway 1-2.6 (SSP1-2.6), are investigated by outputs from models participating in phases 5 and 6 of the ...
Shang-Min Long, Gen Li
doaj   +1 more source

Time-Varying Window Length for Correlation Forecasts

Econometrics, 2017
Forecasting correlations between stocks and commodities is important for diversification across asset classes and other risk management decisions. Correlation forecasts are affected by model uncertainty, the sources of which can include uncertainty about
Yoontae Jeon, Thomas H. McCurdy
doaj   +1 more source

Conditional Coherent and Convex Risk Measures Under Uncertainty

Mathematics
In this paper, we take a new perspective to describe the model uncertainty, and thus propose two new classes of risk measures under model uncertainty. To be precise, we use an auxiliary random variable to describe model uncertainty. By proposing new sets
Shuo Gong, Yijun Hu
doaj   +1 more source

Forecasting the Crude Oil Spot Price with Bayesian Symbolic Regression

Energies, 2022
In this study, the crude oil spot price is forecast using Bayesian symbolic regression (BSR). In particular, the initial parameters specification of BSR is analysed.
Krzysztof Drachal
doaj   +1 more source

To the brave scientists: Aren't we strong enough to stand (and profit from) uncertainty in Earth system measurement and modelling?

Geoscience Data Journal, 2022
The current handling of data in earth observation, modelling and prediction measures gives cause for critical consideration, since we all too often carelessly ignore data uncertainty.
Hendrik Paasche, Matthias Gross, Jakob Lüttgau, David S. Greenberg, Tobias Weigel   +4 more
doaj   +1 more source

Optimising Sensor Placement in Heritage Buildings: A Comparison of Model-Based and Data-Driven Approaches

Sensors
The long-term preservation of heritage structures relies on effective Structural Health Monitoring (SHM) systems, where sensor placement is key to ensuring early damage detection and guiding conservation efforts.
Estefanía Chaves, Alberto Barontini, Nuno Mendes, Víctor Compán   +3 more
doaj   +1 more source

Suitability of Mechanics-Based and Optimized Machine Learning-Based Models in the Shear Strength Prediction of Slender Beams Without Stirrups

Buildings
Accurate shear capacity estimation for reinforced concrete (RC) beams without stirrups is essential for reliable structural design. Traditional code-based methods, primarily empirical, exhibit variability in predicting shear strength for these beams ...
Abayomi B. David, Oladimeji B. Olalusi, Paul O. Awoyera, Lenganji Simwanda   +3 more
doaj   +1 more source

How to measure uncertainty in uncertainty sampling for active learning [PDF]

, 2022
Various strategies for active learning have been proposed in the machine learning literature. In uncertainty sampling, which is among the most popular approaches, the active learner sequentially queries the label of those instances for which its current ...
Hüllermeier, Eyke, Nguyen, Vu-Linh; id_orcid, Nguyen, Vu-Linh, Shaker, Mohammad Hossein   +3 more
core   +2 more sources