Results 21 to 30 of about 4,460 (214)

Simulation of the Oxidation and Combustion of Mixed Diesel-Biodiesel Fuel

MATEC Web of Conferences, 2018
A comparative simulation-based research has been set up to obtain valid kinetic models of the oxidation and combustion of biodiesel surrogate and diesel surrogate, as well as mixed diesel-biodiesel surrogates which is used to predict their ignition delay
Muharam Yuswan, Leonardi Danny, Ramadhania Alisya P   +2 more
doaj   +1 more source

An Offline Weighted-Bagging Data-Driven Evolutionary Algorithm with Data Generation Based on Clustering

Mathematics, 2023
In recent years, a variety of data-driven evolutionary algorithms (DDEAs) have been proposed to solve time-consuming and computationally intensive optimization problems.
Zongliang Guo, Sikai Lin, Runze Suo, Xinming Zhang   +3 more
doaj   +1 more source

On the use of gradients in Kriging surrogate models [PDF]

Proceedings of the Winter Simulation Conference 2014, 2014
The use of Kriging surrogate models has become popular in approximating computation-intensive deterministic computer models. In this work, the effect of enhancing Kriging surrogate models with a (partial) set of gradients is investigated. While, intuitively, gradient information is useful to enhance prediction accuracy, another motivation behind this ...
Selvakumar Ulaganathan, Ivo Couckuyt, Tom Dhaene, Eric Laermans, Joris Degroote   +4 more
openaire   +2 more sources

Rapidly Tuning the PID Controller Based on the Regional Surrogate Model Technique in the UAV Formation

Entropy, 2020
The leader–follower structure is widely used in unmanned aerial vehicle formation. This paper adopts the proportional-integral-derivative (PID) and the linear quadratic regulator controllers to construct the leader–follower formation.
Binglin Wang, Xiaojun Duan, Liang Yan, Juan Deng, Jiangtao Chen   +4 more
doaj   +1 more source

Universal Prediction Distribution for Surrogate Models [PDF]

SIAM/ASA Journal on Uncertainty Quantification, 2017
The use of surrogate models instead of computationally expensive simulation codes is very convenient in engineering. Roughly speaking, there are two kinds of surrogate models: the deterministic and the probabilistic ones. These last are generally based on Gaussian assumptions.
Ben Salem, Malek, Roustant, Olivier, Gamboa, Fabrice, Tomaso, Lionel   +3 more
openaire   +5 more sources

A surrogate FRAX model for Nepal [PDF]

Archives of Osteoporosis
Abstract Summary A surrogate FRAX® model for Nepal has been constructed using age- and sex-specific hip fracture rates for Indians living in Singapore and age- and sex-specific mortality rates from Nepal. Introduction FRAX
Johansson, H., Pandey, D., Lorentzon, M., Harvey, N.C., McCloskey, E.V., Kanis, J.A.   +5 more
openaire   +5 more sources

Detecting and Isolating Adversarial Attacks Using Characteristics of the Surrogate Model Framework

Applied Sciences, 2023
The paper introduces a novel framework for detecting adversarial attacks on machine learning models that classify tabular data. Its purpose is to provide a robust method for the monitoring and continuous auditing of machine learning models for the ...
Piotr Biczyk, Łukasz Wawrowski
doaj   +1 more source

A DNN-Based Surrogate Constitutive Equation for Geometrically Exact Thin-Walled Rod Members

Computation
Kinematically exact rod models were a major breakthrough to evaluate complex frame structures undergoing large displacements and the associated buckling modes.
Marcos Pires Kassab, Eduardo de Morais Barreto Campello, Adnan Ibrahimbegovic   +2 more
doaj   +1 more source

Feasibility and Safety of Somato‐Cognitive Coordination Therapy for Cerebellar Ataxia Following Pediatric Brain Tumor Treatment

Pediatric Blood &Cancer, EarlyView.
ABSTRACT Background Cerebellar ataxia after pediatric brain tumor treatment can cause persistent gait, balance, and speech impairment, yet no established rehabilitation strategy exists. Somato‐cognitive coordination therapy (SCCT) is a virtual reality–guided intervention designed to promote sensorimotor integration through visually constrained reaching
Masanobu Takeuchi, Takashi Matsuzawa, Jun Yamanishi, Masahiro Yoshitomi, Junji Ikeda, Shin‐Ichi Tsujimoto, Yasuteru Yamaguchi, Norio Shiba, Dhroov Pathare, Ayumi Kato, Masahiko Hara   +10 more
wiley   +1 more source

Surrogate-Assisted Symbolic Time-Series Discretization Using Multi-Breakpoints and a Multi-Objective Evolutionary Algorithm

Mathematical and Computational Applications
The enhanced multi-objective symbolic discretization for time series (eMODiTS) method employs a flexible discretization scheme using different value cuts for each non-equal time interval, which incurs a high computational cost for evaluating each ...
Aldo Márquez-Grajales, Efrén Mezura-Montes, Héctor-Gabriel Acosta-Mesa, Fernando Salas-Martínez   +3 more
doaj   +1 more source