Results 61 to 70 of about 3,355 (214)
Time‐Delayed Spiking Reservoir Computing Enables Efficient Time Series Prediction
Advanced Intelligent Systems, EarlyView.This study proposes time‐delayed spiking reservoir computing (TDSRC) for efficient time series prediction. By concatenating time‐lagged states, TDSRC constructs an expanded readout feature vector without altering internal reservoir dynamics. This approach enables highly accurate forecasting with significantly fewer neurons, providing a resource ...
Pin Jin +3 more
wiley +1 more source
Stochastic Finite Element Method Using Polynomial Chaos Expansion
, 2011 We present a new response surface based stochastic finite element method to obtain solutions for general random uncertainty problems using the polynomial chaos expansion.
Wei Zhao, Ji Ke Liu
core +1 more source
Embracing Complexity in HRM Research: A Call for System and Process Perspectives
Human Resource Management, EarlyView.ABSTRACT Human resource management (HRM) is inherently complex. It involves systems of principles, practices, and activities operating at individual, group, organizational, and macro levels, which are interlinked through complex processes. Yet, empirical research has not kept pace with this conceptual richness.
Rebecca Hewett, Madleen Meier‐Barthold
wiley +1 more source
UNCERTAINTY QUANTIFICATION IN STOCHASTIC SYSTEMS USING POLYNOMIAL CHAOS EXPANSION
, 2010 In recent years, extensive research has been reported about a method which is called the generalized polynomial chaos expansion. In contrast to the sampling methods, e.g., Monte Carlo simulations, polynomial chaos expansion is a nonsampling method which
K. SEPAHVAND, H.-J. HARDTKE, S. MARBURG
core +1 more source
Distributional uncertainty analysis using polynomial chaos expansions [PDF]
2010 IEEE International Symposium on Computer-Aided Control System Design, 2010 A computationally efficient approach is presented that quantifies the influence of parameter uncertainties on the states and outputs of finite-time control trajectories for nonlinear systems, based on the approximate representation of the model via polynomial chaos expansion.
Zoltán K. Nagy, Richard D. Braatz
openaire +1 more source
Mathematical Methods in the Applied Sciences, EarlyView.ABSTRACT The numerical approximation of nonlinear chaotic differential systems, such as the modified stretch‐twist‐fold (STF) flow and multi‐bond chaotic attractors, presents a significant challenge due to their sensitive dependence on initial conditions and complex dynamics where analytical solutions are unattainable.
Shina Daniel Oloniiju, Anastacia Dlamini
wiley +1 more source
Surrogate modeling based on resampled polynomial chaos expansions
Reliability Engineering & System Safety, 2020 Reliability Engineering & System Safety ...
Zicheng Liu 0002 +3 more
openaire +4 more sources
Swiss Political Science Review, EarlyView.Abstract This study analyses the success of populist radical right (PRR) parties in the 2023 Swiss elections using reference group theory. While existing literature emphasizes the influence of objective and subjective group membership on electoral choice, it often overlooks voters' feelings toward groups they do not belong to and their perceptions of ...
Anke Tresch, Line Rennwald
wiley +1 more source
The Journal of Physiology, EarlyView.Abstract figure legend Graphical representation of methods. We implemented three biventricular geometric models (Zenger et al., 2020) with rule‐based myocardial fibre orientations (Bayer et al., 2018). We evaluated variability in the fibre orientation via four sets of parameter distributions to determine the role of the primary and imbrication angles ...
Lindsay C. R. Tanner +8 more
wiley +1 more source
Polynomial chaos in evaluating failure probability: A comparative study [PDF]
, 2018 summary:Recent developments in the field of stochastic mechanics and particularly regarding the stochastic finite element method allow to model uncertain behaviours for more complex engineering structures.
Kučerová, Anna +2 more
core +1 more source