Results 31 to 40 of about 9,630 (234)

Implementation of four kriging models for depth inpainting

ICT Express, 2020
Image inpainting is a process of reconstructing the missing pixels by inferencing information from the known part of an image. This paper aims to increase the precision of depth inpainting by proposing four models based on kriging techniques. Our four kriging models are based on two different semivariance models (exponential model and spherical model ...
Yossawee Keaomanee, Apichat Heednacram, Prakarnkiat Youngkong   +2 more
openaire   +2 more sources

Optimization of aero-engine combustion chambers with the assistance of Hierarchical-Kriging surrogate model based on POD downscaling method

Advances in Aerodynamics, 2023
In view of the long calculation cycle, high processing test and cost of the traditional aero-engine combustion chamber design process, which restricts the engine optimization design cycle, this paper innovatively proposes a surrogate model for the ...
Shuhong Tong, Yue Ma, Mingming Guo, Ye Tian, Wenyan Song, Heng Wang, Jialing Le, Hua Zhang   +7 more
doaj   +1 more source

Optimization of Combustion Chamber for Diesel Engine Using Kriging Model

Journal of Fluid Science and Technology, 2006
Diesel engine combustion chamber which reduces exhaust emission has been designed using CFD analysis and optimization techniques. In order to save computational time for design, the Kriging model, one of the response surface models, is adopted here.
Shinkyu JEONG, Youichi MINEMURA, Shigeru OBAYASHI   +2 more
doaj   +1 more source

Theta-regularized Kriging: Modeling and algorithms

Applied Mathematical Modelling
To obtain more accurate model parameters and improve prediction accuracy, we proposed a regularized Kriging model that penalizes the hyperparameter theta in the Gaussian stochastic process, termed the Theta-regularized Kriging. We derived the optimization problem for this model from a maximum likelihood perspective.
Xuelin Xie, Xiliang Lu
openaire   +2 more sources

Kriging Models that are Robust with Respect to Simulation Errors [PDF]

SSRN Electronic Journal, 2007
In the field of the Design and Analysis of Computer Experiments (DACE) meta-models are used to approximate time-consuming simulations. These simulations often contain simulation-model errors in the output variables. In the construction of meta-models, these errors are often ignored. Simulation-model errors may be magnified by the meta-model. Therefore,
Siem, A.Y.D., Hertog, D. den
openaire   +4 more sources

Low-Boom and Low-Drag Optimization of the Twin Engine Version of Silent Supersonic Business Jet

Journal of Fluid Science and Technology, 2008
Multi-Objective Optimization has been applied to a design problem of the twin engine concept for Silent Supersonic Business Jet (SSBJ). This problem aims to find main wing, body, tail wing and engine nacelle configurations, which can minimize both sonic ...
Koma SATO, Takayasu KUMANO, Masahito YONEZAWA, Hiroshi YAMASHITA, Shinkyu JEONG, Shigeru OBAYASHI   +5 more
doaj   +1 more source

Optimization of MOSFET Copper Clip to Enhance Thermal Management Using Kriging Surrogate Model and Genetic Algorithm

Mathematics
Metal–oxide–semiconductor field-effect transistors (MOSFETs) are critical in power electronic modules due to their high-power density and rapid switching capabilities.
Yubin Cheon, Jaehyun Jung, Daeyeon Ki, Salman Khalid, Heung Soo Kim   +4 more
doaj   +1 more source

Optimum layout of vortex generators for upper surface of wing using efficient global optimization

Nihon Kikai Gakkai ronbunshu, 2015
The “buffet” which is the shock wave vibration on the wing at transonic speed has influence to the aerodynamic performance of the civil transport. It is significant because the wing cannot maintain its aerodynamic performance and it is also led to the ...
Norikazu KOZAKAI, Hiroyuki KATO, Kazuyuki NAKAKITA, Masahiro KANAZAKI   +3 more
doaj   +1 more source

Kriging with mixed effects models

Statistica, 2007
In this paper the effectiveness of the use of mixed effects models for estimation and prediction purposes in spatial statistics for continuous data is reviewed in the classical and Bayesian frameworks. A case study on agricultural data is also provided.
POLLICE, Alessio, BILANCIA, Massimo
openaire   +3 more sources

Human‐in‐the‐Loop Swarms: A Bionic Swarm Approach to Real‐World Soil Mapping

Advanced Intelligent Systems, EarlyView.
This article introduces the “Bionic Swarm,” a novel system that lowers the barriers to real‐world swarm validation by abstracting difficult hardware tasks to app‐guided human agents. We demonstrate the system's utility through the experimental validation of a geotechnical soil‐mapping swarm algorithm and show superior performance to baseline approaches
Petras Swissler, Mohammadali Rashidioun, Nicholas Sahu, Raaid Kabir, Ayodeji Aderibigbe, Oladoyin Kolawole   +5 more
wiley   +1 more source