Results 121 to 130 of about 129,784 (278)

Interpretable Tree‐Based Models for Predicting Short‐Term Rockburst Risk Considering Multiple Factors

Energy Science &Engineering, EarlyView.
Interpretable tree‐based models integrate microseismic, geological, and mining indicators to predict short‐term rockburst risk. SHAP analysis reveals the dominant role of energy‐related features and clarifies nonlinear factor interactions, enabling transparent and reliable early‐warning in deep coal mines.
Shuai Chen, Linming Dou, Atao Li, Wu Cai, Lei Zhang   +4 more
wiley   +1 more source

Local Polynomial Regression and Filtering for a Versatile Mesh‐Free PDE Solver

International Journal for Numerical Methods in Fluids, EarlyView.
A high‐order, mesh‐free finite difference method for solving differential equations is presented. Both derivative approximation and scheme stabilisation is carried out by parametric or non‐parametric local polynomial regression, making the resulting numerical method accurate, simple and versatile. Numerous numerical benchmark tests are investigated for
Alberto M. Gambaruto
wiley   +1 more source

Note on a Nonlinear Eigenvalue Problem

Rocky Mountain Journal of Mathematics, 1993
Consider the nonlinear eigenvalue problem \({d \over dx} (| u' |^{p-2}u')+ \lambda | u |^{p-2}u=0\). It is observed that the first positive eigenvalue \(\lambda_ p\) satisfies a conjugacy condition \(\lambda_ p^{1/p}=\lambda_ q^{1/p}\), \({1 \over p} + {1 \over q}=1\). Also the corresponding eigenfunctions are related.
openaire   +2 more sources

Comparison between the Variational Iteration Method and the Homotopy Perturbation Method for the Sturm-Liouville Differential Equation

Boundary Value Problems, 2010
We applied the variational iteration method and the homotopy perturbation method to solve Sturm-Liouville eigenvalue and boundary value problems. The main advantage of these methods is the flexibility to give approximate and exact solutions to both ...
R. Darzi, A. Neamaty
doaj   +1 more source

A Deep Learning Framework for Forecasting Medium‐Term Covariance in Multiasset Portfolios

Journal of Forecasting, EarlyView.
ABSTRACT Forecasting the covariance matrix of asset returns is central to portfolio construction, risk management, and asset pricing. However, most existing models struggle at medium‐term horizons, several weeks to months, where shifting market regimes and slower dynamics prevail.
Pedro Reis, Ana Paula Serra, João Gama
wiley   +1 more source

On a Nonlinear Elliptic Eigenvalue Problem

Journal of Differential Equations, 1995
The eigenvalue problem \(- \Delta u- \mu u= \lambda g(x, u)\) in \(D\), \(u= 0\) on \(\partial D\), with prescribed energy condition is considered. Multiplicity results are proved, based on Lyusternik-Schnirelman theory.
openaire   +2 more sources

Intraday Functional PCA Forecasting of Cryptocurrency Returns

Journal of Forecasting, EarlyView.
ABSTRACT We study the functional PCA (FPCA) forecasting method in application to functions of intraday returns on Bitcoin. We show that improved interval forecasts of future return functions are obtained when the conditional heteroscedasticity of return functions is taken into account.
Joann Jasiak, Cheng Zhong
wiley   +1 more source

Eigenvalue Problems for Systems of Nonlinear Boundary Value Problems on Time Scales

Advances in Difference Equations, 2007
Values of λ are determined for which there exist positive solutions of the system of dynamic equations, , , for , satisfying the boundary conditions, , where is a time scale. A Guo-Krasnosel'skii fixed point-theorem is applied.
Henderson J, Ntouyas SK, Benchohra M
doaj  

Forecasting With Dynamic Factor Models Estimated by Partial Least Squares

Journal of Forecasting, EarlyView.
ABSTRACT Dynamic factor models (DFMs) have found great success in nowcasting and short‐term macroeconomic forecasting when incorporating large sets of predictive information. The factor loadings are typically estimated cross‐sectionally with principal component analysis (PCA) or maximum likelihood (ML), which ignore whether the factors have predictive ...
Samuel Rauhala
wiley   +1 more source

Protective Factors Associated With Perceived Risk of Exclusion From Education and Work Among Vocational Students

Journal of Adolescence, EarlyView.
ABSTRACT Introduction Perceived risk of experiencing NEET status (Not in Education, Employment, or Training) reflects young people's sense of vulnerability in the transition from school to work. Identifying protective factors linked with lower perceived risk may help inform early prevention.
Kati Kajastus
wiley   +1 more source