Regression analysis for detecting epileptic seizure with different feature extracting strategies
Due to the excitability of neurons in the brain, a neurological disorder is produced known as
epilepsy. The brain activity of patients suffering from epilepsy is monitored through …
epilepsy. The brain activity of patients suffering from epilepsy is monitored through …
A fresh look at variography: measuring dependence and possible sensitivities across geophysical systems from any given data
R Sheikholeslami, S Razavi - Geophysical Research Letters, 2020 - Wiley Online Library
Sensitivity analysis in Earth and environmental systems modeling typically demands an
onerous computational cost. This issue coexists with the reliance of these algorithms on ad …
onerous computational cost. This issue coexists with the reliance of these algorithms on ad …
On the impact of prior distributions on efficiency of sparse Gaussian process regression
Gaussian process regression (GPR) is a kernel-based learning model, which unfortunately
suffers from computational intractability for irregular domain and large datasets due to the …
suffers from computational intractability for irregular domain and large datasets due to the …
Inverse problem for time-series valued computer model via scalarization
For an expensive to evaluate computer simulator, even the estimate of the overall surface
can be a challenging problem. In this paper, we focus on the estimation of the inverse …
can be a challenging problem. In this paper, we focus on the estimation of the inverse …
Hybrid APSO–spiral dynamic algorithms with application to tuning of filtered PPI controller in a wirelessHART environment
The accelerated particle swarm optimisation (APSO) is an improved variant of the PSO
algorithm that guarantees convergence through the use of only global best to update both …
algorithm that guarantees convergence through the use of only global best to update both …
[引用][C] The Design and analysis of computer experiments
TJ Santner - 2003 - Springer
Directed Gaussian process metamodeling with improved firefly algorithm (iFA) for composite manufacturing uncertainty propagation analysis
A computationally effective and physically accurate metamodeling approach is
demonstrated to analyze, under uncertainties, the spring-in angle deformation for composite …
demonstrated to analyze, under uncertainties, the spring-in angle deformation for composite …
Kriging metamodels and their designs
JPC Kleijnen, JPC Kleijnen - Design and Analysis of Simulation …, 2015 - Springer
This chapter is organized as follows. Section 5.1 introduces Kriging, which is also called
Gaussian process (GP) or spatial correlation modeling. Section 5.2 details so-called …
Gaussian process (GP) or spatial correlation modeling. Section 5.2 details so-called …
Nonlinear UGV Identification Methods via the Gaussian Process Regression Model for Control System Design
EI Trombetta, D Carminati, E Capello - Applied Sciences, 2022 - mdpi.com
In this paper, two identification methods are proposed for a ground robotic system. A
Gaussian process regression (GPR) model is presented and adopted for a system …
Gaussian process regression (GPR) model is presented and adopted for a system …
Methods to compare expensive stochastic optimization algorithms with random restarts
We consider the challenge of numerically comparing optimization algorithms that employ
random-restarts under the assumption that only limited test data is available. We develop a …
random-restarts under the assumption that only limited test data is available. We develop a …