2014
DOI: 10.1016/j.advengsoft.2014.08.002
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Optimization design of corrugated beam guardrail based on RBF-MQ surrogate model and collision safety consideration

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Cited by 39 publications
(12 citation statements)
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“…, mexisting results greater than 1 (8) where, m is the total number of times the experiment has been conducted, EMS i is the mathematical expectation of the mean square error. The equation for the mean square error MS i is shown below [33,34]:…”
Section: Three-level Unreplicated Saturated Factorial Design Methodsmentioning
confidence: 99%
“…, mexisting results greater than 1 (8) where, m is the total number of times the experiment has been conducted, EMS i is the mathematical expectation of the mean square error. The equation for the mean square error MS i is shown below [33,34]:…”
Section: Three-level Unreplicated Saturated Factorial Design Methodsmentioning
confidence: 99%
“…Since the neural network model has a strong ability to approximate complex nonlinear functions, the learning speed is fast, has excellent generalization ability, and is highly fault-tolerant. It is used by many scholars and engineers in aircraft wingtips [44], highway traffics [45], turbomachinery [46], engineering optimization [47], compressors [48], gas cyclone separator [49], MMES controllers [50], and many other applications. The relationships between the vibrational sound radiation of the volute casing surface and the volute panel thickness are typically nonlinear.…”
Section: Rbf Approximation Surrogate Models and Validationmentioning
confidence: 99%
“…The main Contents lists available at ScienceDirect journal homepage: www.elsevier.com/locate/caor advantage of this approach is that the surrogate model has a lower computational complexity than the original model of the problem, thereby significantly reducing the computational cost. Because of this advantage, surrogate models are widely utilized in many fields, such as the optimization of helicopter rotor blades [19], the optimization design of corrugated beam guardrails [20], and the inverse calculation of in situ stress in rock mass [21]. However, selecting the appropriate surrogate model is a challenge because a certain surrogate model cannot be suitable for all kinds of problems [22].…”
Section: Introductionmentioning
confidence: 99%