Journal ArticleDOI
Kriging metamodel management in the design optimization of a CNG injection system
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TLDR
The metamodel management issue to find the tradeoff between accuracy and efficiency is addressed and a comparative analysis of different strategies is conducted for a case study devoted to the design of a component of the injection system for Compressed Natural Gas engines.About:
This article is published in Mathematics and Computers in Simulation.The article was published on 2009-04-01. It has received 56 citations till now. The article focuses on the topics: Kriging & Metamodeling.read more
Citations
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Journal ArticleDOI
AK-MCS: An active learning reliability method combining Kriging and Monte Carlo Simulation
TL;DR: An iterative approach based on Monte Carlo Simulation and Kriging metamodel to assess the reliability of structures in a more efficient way and is shown to be very efficient as the probability of failure obtained with AK-MCS is very accurate and this, for only a small number of calls to the performance function.
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Surrogate-assisted evolutionary computation: Recent advances and future challenges
TL;DR: This paper provides a concise overview of the history and recent developments in surrogate-assisted evolutionary computation and suggests a few future trends in this research area.
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LIF: A new Kriging based learning function and its application to structural reliability analysis
TL;DR: Results show that LIF and the new method proposed in this research are very efficient when dealing with nonlinear performance function, small probability, complicated limit state and engineering problems with high dimension.
Journal ArticleDOI
Crashworthiness optimization design for foam-filled multi-cell thin-walled structures
TL;DR: In this paper, the authors investigated the energy absorption characteristics of FMTSs by nonlinear finite element analysis through LS-DYNA and found that the FMTS with nine cells had the most excellent crashworthiness characteristics in the considered cases.
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An exploratory approach for adaptive policymaking by using multi-objective robust optimization
TL;DR: The proposed multi-objective robust simulation optimization approach can be efficiently used for developing policy suggestions and for improving decision support for policymakers and is possible to apply in dynamically complex and deeply uncertain systems such as public health, financial systems, transportation, and housing.
References
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Journal ArticleDOI
A fast and elitist multiobjective genetic algorithm: NSGA-II
TL;DR: This paper suggests a non-dominated sorting-based MOEA, called NSGA-II (Non-dominated Sorting Genetic Algorithm II), which alleviates all of the above three difficulties, and modify the definition of dominance in order to solve constrained multi-objective problems efficiently.
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The design and analysis of computer experiments
TL;DR: This paper presents a meta-modelling framework for estimating Output from Computer Experiments-Predicting Output from Training Data and Criteria Based Designs for computer Experiments.
Journal ArticleDOI
A Taxonomy of Global Optimization Methods Based on Response Surfaces
TL;DR: This paper presents a taxonomy of existing approaches for using response surfaces for global optimization, illustrating each method with a simple numerical example that brings out its advantages and disadvantages.
Journal ArticleDOI
Comparative studies of metamodelling techniques under multiple modelling criteria
TL;DR: This paper systematically compare four popular metamodelling techniques – polynomial regression, multivariate adaptive regression splines, radial basis functions, and kriging – based on multiple performance criteria using fourteen test problems representing different classes of problems.
Book
Introduction to Modeling and Control of Internal Combustion Engine Systems
TL;DR: In this paper, a cost-effective model-based control-system design for internal combustion engines (ICE) is presented, where the primary emphasis is put on the ICE and its auxiliary devices.
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