Results 51 to 60 of about 1,638 (210)
Research on Precise Identification of Rock Strength Based on Bolt Drilling Parameters
Energy Science &Engineering, EarlyView.Drilling detection test platform. ABSTRACT During roadway excavation, the presence of weak interlayers and fractured rock masses significantly affects roof stability. To achieve timely and effective roadway support, it is crucial to identify and predict different rock types based on drilling signals from roof bolters.
Qiang Zhu +4 more
wiley +1 more source
BCARS Simulated Phantom Dataset for Evaluation of Processing Pipelines
Journal of Raman Spectroscopy, EarlyView.A tissue phantom, containing fingerprint Raman spectra at each pixel, is developed to evaluate Raman signal processing pipelines. The phantom is created from a BCARS image of a murine hepatic tissue. ABSTRACT Broadband coherent anti‐Stokes Raman scattering (BCARS) microscopy is a powerful label‐free biological imaging technique, but the raw signal ...
Jessica Z. Dixon +5 more
wiley +1 more source
, 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 +2 more
openaire +2 more sources
Mathematical Methods in the Applied Sciences, EarlyView.A highly accurate numerical method is given for the solution of boundary value problem of generalized Bagley‐Torvik (BgT) equation with Caputo derivative of order 0<β<2$$ 0<\beta <2 $$ by using the collocation‐shooting method (C‐SM). The collocation solution is constructed in the space Sm+1(1)$$ {S}_{m+1}^{(1)} $$ as piecewise polynomials of degree at ...
Suzan Cival Buranay +2 more
wiley +1 more source
A Discretized Tikhonov Regularization Method for a Fractional Backward Heat Conduction Problem
Abstract and Applied Analysis, 2014 We propose a numerical reconstruction method for solving a time-fractional backward heat conduction problem. Based on the idea of reproducing kernel approximation, we reconstruct the unknown initial heat distribution from a finite set of scattered ...
Zhi-Liang Deng, Xiao-Mei Yang
doaj +1 more source
INFORMATIVE ENERGY METRIC FOR SIMILARITY MEASURE IN REPRODUCING KERNEL HILBERT SPACES [PDF]
International Journal of Computational Intelligence Systems, 2012 In this paper, information energy metric (IEM) is obtained by similarity computing for high-dimensional samples in a reproducing kernel Hilbert space (RKHS).
Songhua Liu, Junying Zhang, Caiying Ding
doaj +1 more source
Magnetic Resonance in Medicine, EarlyView.ABSTRACT Purpose In multi‐shot EPI, shot‐dependent phase fluctuations can introduce ghost artifacts, undermining advantages for enhancing resolution or reducing distortion, particularly in diffusion scans. Here, a novel self‐navigation strategy based on shift‐invariant kernel extraction is proposed, enabling robust estimation of phase inconsistencies ...
Rui Tian +3 more
wiley +1 more source
Reproducing Kernel Method for Solving Nonlinear Differential-Difference Equations
Abstract and Applied Analysis, 2012 On the basis of reproducing kernel Hilbert spaces theory, an iterative algorithm for solving some nonlinear differential-difference equations (NDDEs) is presented.
Reza Mokhtari +2 more
doaj +1 more source
Boletim da Sociedade Paranaense de Matemática, 2022 The aim of this paper is to extend the application of the reproducing kernel Hilbert space method (RKHSM) to solve linear and non-linear fuzzy integro-differential equations of fractional order under Caputo's H-differentiability. The analytic and approximate solutions are given in series form in term of their parametric form in the space $W_2^2 [a,b ...
Shatha Hasan +3 more
openaire +2 more sources
Combining kernelised autoencoding and centroid prediction for dynamic multi‐objective optimisation
CAAI Transactions on Intelligence Technology, EarlyView.Abstract Evolutionary algorithms face significant challenges when dealing with dynamic multi‐objective optimisation because Pareto optimal solutions and/or Pareto optimal fronts change. The authors propose a unified paradigm, which combines the kernelised autoncoding evolutionary search and the centroid‐based prediction (denoted by KAEP), for solving ...
Zhanglu Hou +4 more
wiley +1 more source