Results 31 to 40 of about 1,248,103 (272)

Gaussian Process Time-Series Models for Structures under Operational Variability

Frontiers in Built Environment, 2017
A wide range of vibrating structures are characterized by variable structural dynamics resulting from changes in environmental and operational conditions, posing challenges in their identification and associated condition assessment. To tackle this issue,
Luis David Avendaño-Valencia, Eleni N. Chatzi, Ki Young Koo, James M. W. Brownjohn   +3 more
doaj   +1 more source

Conformations of Steroid Hormones: Infrared and Vibrational Circular Dichroism Spectroscopy

Molecules, 2023
Steroid hormone molecules may exhibit very different functionalities based on the associated functional groups and their 3D arrangements in space, i.e., absolute configurations and conformations.
Yanqing Yang, Anna Krin, Xiaoli Cai, Mohammad Reza Poopari, Yuefei Zhang, James R. Cheeseman, Yunjie Xu   +6 more
doaj   +1 more source

Recent developments in empirical dynamic modelling

Methods in Ecology and Evolution, 2023
Ecosystems are complex and sparsely observed making inference and prediction challenging. Empirical dynamic modelling (EDM) circumvents the need for a parametric model and complete observations of all system variables.
Stephan B. Munch, Tanya L. Rogers, George Sugihara   +2 more
doaj   +1 more source

Multiphase flow applications of nonintrusive reduced-order models with Gaussian process emulation

Data-Centric Engineering, 2022
Reduced-order models (ROMs) are computationally inexpensive simplifications of high-fidelity complex ones. Such models can be found in computational fluid dynamics where they can be used to predict the characteristics of multiphase flows.
Themistoklis Botsas, Indranil Pan, Lachlan R. Mason, Omar K. Matar   +3 more
doaj   +1 more source

Gaussian Process Boosting

, 2020
We introduce a novel way to combine boosting with Gaussian process and mixed effects models. This allows for relaxing, first, the zero or linearity assumption for the prior mean function in Gaussian process and grouped random effects models in a flexible non-parametric way and, second, the independence assumption made in most boosting algorithms.
openaire   +3 more sources

Optimal drive cycle current supply of a wound field automotive electrical machine using surrogate models

Science and Technology for Energy Transition
Surrogate models have become a widely used solution for reducing computation times along design processes. In this work, a Gaussian Process surrogate model is built and used to predict the performance and losses of a wound field electrical machine in a ...
Mazloum Rebecca, Hlioui Sami, Laurent Luc, Belhadi M’Hamed, Mermaz-Rollet Guillaume, Gabsi Mohamed   +5 more
doaj   +1 more source

SCADA based nonparametric models for condition monitoring of a wind turbine

The Journal of Engineering, 2019
High operation and maintenance costs for offshore wind turbines push up the LCOE of offshore wind energy. Unscheduled maintenance due to unanticipated failures is the most prominent driver of the maintenance cost which reinforces the drive towards ...
Ravi Kumar Pandit, David Infield, David Infield   +2 more
doaj   +1 more source

Harmonic State Estimation Method Based on Bayesian Optimized Elastic Network Regression

Zhongguo dianli, 2022
When the regression algorithm is used to estimate the harmonic state of power system, the high correlation between harmonic sources will cause the ill condition of the normal matrix, which will significantly affect the accuracy of harmonic estimation. In
Siqi MA, Zhong WANG
doaj   +1 more source

A methionine‐lined active site governs carbocation stabilization and product specificity in a bacterial terpene synthase

FEBS Letters, EarlyView.
This study reveals a unique active site enriched in methionine residues and demonstrates that these residues play a critical role by stabilizing carbocation intermediates through novel sulfur–cation interactions. Structure‐guided mutagenesis further revealed variants with significantly altered product profiles, enhancing pseudopterosin formation. These
Marion Ringel, Carl P. O. Helmer, Shani Zev, Ronja Driller, Emily Buhr, Markus Reinbold, Renana Schwartz, Gabriel Foley, Mikael Boden, Daniel Garbe, Gerhard Schenk, Dan Thomas Major, Bernhard Loll, Thomas Brück   +13 more
wiley   +1 more source

Nonlinear deformation prediction of tunnel surrounding rock with computational intelligence approaches

Geomatics, Natural Hazards & Risk, 2020
Deformation of surrounding rock is widely monitored to discover surrounding rock behaviors for purpose of event forecasting. This article aims to present a comparative study on surrounding rock nonlinear deformation prediction using computational ...
Peng He, Fei Xu, Shang-qu Sun
doaj   +1 more source