Results 91 to 100 of about 16,403 (208)

Modified analytical approach for generalized quadratic and cubic logistic models with Caputo-Fabrizio fractional derivative

Alexandria Engineering Journal, 2020
In this paper, a modified reproducing kernel algorithm is proposed to solve a class of quadratic and cubic logistic equations with Caputo-Fabrizio fractional derivative in Hilbert space.
Nadir Djeddi, Shatha Hasan, Mohammed Al-Smadi, Shaher Momani   +3 more
doaj   +1 more source

Convergent Methods for Koopman Operators on Reproducing Kernel Hilbert Spaces

Data-driven spectral analysis of Koopman operators is a powerful tool for understanding numerous real-world dynamical systems, from neuronal activity to variations in sea surface temperature. The Koopman operator acts on a function space and is most commonly studied on the space of square-integrable functions.
Boullé, Nicolas, Colbrook, Matthew J., Conradie, Gustav   +2 more
openaire   +2 more sources

The theory and application of penalized methods or Reproducing Kernel Hilbert Spaces made easy

Statistics Surveys, 2012
The popular cubic smoothing spline estimate of a regression function arises as the minimizer of the penalized sum of squares $\sum_j(Y_j - μ(t_j))^2 + λ\int_a^b [μ"(t)]^2 dt$, where the data are $t_j,Y_j$, $j=1,..., n$. The minimization is taken over an infinite-dimensional function space, the space of all functions with square integrable second ...
openaire   +4 more sources

Harnessing genomic prediction in Brassica napus through a nested association mapping population

The Plant Genome, Volume 18, Issue 4, December 2025.
Abstract Genomic prediction (GP) significantly enhances genetic gain by improving selection efficiency and shortening crop breeding cycles. Using a nested association mapping population, a set of diverse scenarios were assessed to evaluate GP for important agronomic traits in Brassica napus, including plant height, days to flowering, 1000‐kernel weight,
Sampath Perumal, Erin E. Higgins, Simarjeet Sra, Yogendra Khedikar, Jessica Moore, Raju Chaudary, Teketel Haile, Chu Shin Koh, Sally Vail, Stephen J. Robinson, Kyla Horner, Brad Hope, Henry Klein‐Gebbinck, David T Herrmann, Katy Navabi, Andrew G. Sharpe, Isobel A. P. Parkin   +16 more
wiley   +1 more source

Solutions to Uncertain Volterra Integral Equations by Fitted Reproducing Kernel Hilbert Space Method

Journal of Function Spaces, 2016
We present an efficient modern strategy for solving some well-known classes of uncertain integral equations arising in engineering and physics fields. The solution methodology is based on generating an orthogonal basis upon the obtained kernel function ...
Ghaleb Gumah, Khaled Moaddy, Mohammed Al-Smadi, Ishak Hashim   +3 more
doaj   +1 more source

Numerical Solution of Delay Differential Equations via the Reproducing Kernel Hilbert Spaces Method

Asian Research Journal of Mathematics, 2020
Delay differential equations (DDEs) are generalization of the ordinary differential equation (ODEs), which is suitable for physical system that also depends on the past data. In this paper, the Reproducing Kernel Hilbert Spaces (RKHS) method is applied to approximate the solution of a general form of first, second and third order fractional DDEs (FDDEs)
Abdelhalim Ebaid, Reham K. Alshehri, Banan Maayah   +2 more
openaire   +3 more sources

Mapping novel yellow and leaf rust loci and predicting resistance in cross derived Canadian durum wheat

The Plant Genome, Volume 18, Issue 4, December 2025.
Abstract Durum wheat (Triticum turgidum ssp. durum) suffers substantial yield losses from yellow rust (Puccinia striiformis) and leaf rust (Puccinia triticina). In this study, we employed genome‐wide association studies (GWAS) to identify loci associated with rust resistance and used genomic selection (GS) to evaluate the predictive accuracy of ...
Juan Menor de Gaspar, Alejandro Domínguez Rondón, Julián García‐Abadillo, Ron Knox, Firdissa E. Bokore, Kerry Boyle, Karim Ammar, Julio Huerta‐Espino, Samia Berraies, Brad Meyer, Wentao Zhang, Richard D. Cuthbert, Fobert Pierre, Yuefeng Ruan, Julio Isidro y Sánchez   +14 more
wiley   +1 more source

Unsupervised Domain Adaptation by Mapped Correlation Alignment

IEEE Access, 2018
The goal of unsupervised domain adaptation aims to utilize labeled data from source domain to annotate the target-domain data, which has none of the labels.
Yun Zhang, Nianbin Wang, Shaobin Cai, Lei Song   +3 more
doaj   +1 more source

Robust Kernel (Cross-) Covariance Operators in Reproducing Kernel Hilbert Space toward Kernel Methods

, 2016
To the best of our knowledge, there are no general well-founded robust methods for statistical unsupervised learning. Most of the unsupervised methods explicitly or implicitly depend on the kernel covariance operator (kernel CO) or kernel cross-covariance operator (kernel CCO).
Alam, Md. Ashad, Fukumizu, Kenji, Wang, Yu-Ping   +2 more
openaire   +2 more sources

Ensemble AnalySis with Interpretable Genomic Prediction (EasiGP): Computational tool for interpreting ensembles of genomic prediction models

The Plant Genome, Volume 18, Issue 4, December 2025.
Abstract An ensemble of multiple genomic prediction models has grown in popularity due to consistent prediction performance improvements in crop breeding. However, technical tools that analyze the predictive behavior at the genome level are lacking. Here, we develop a computational tool called Ensemble AnalySis with Interpretable Genomic Prediction ...
Shunichiro Tomura, Melanie J. Wilkinson, Owen Powell, Mark Cooper   +3 more
wiley   +1 more source