Combining sensitivity and uncertainty analysis to efficiently quantify parametric uncertainties in NVH system simulation models

stability and attraction domains of traffic equilibria in day-to-day dynamical system formulation

در این پژوهش مسئله واگذاری ترافیک را از دید سیستم های دینامیکی فرمول بندی می کنیم.فرض کرده ایم که همه فاکتورهای وابسته در طول زمان ثابت باشند و تعادل کاربر را از طریق فرایند منظم روزبه روز پیگیری کنیم.دینامیک ترافیک توسط یک نگاشت بازگشتی نشان داده می شود که تکامل سیستم در طول زمان را نشان می دهد.پایداری تعادل و دامنه جذب را توسط مطالعه ویژگی های توپولوژیکی تکامل سیستم تجزیه و تحلیل می کنیم.پاید...

Computational Approaches to Efficiently Maximize Solution Capabilities and Quantify Uncertainty for Inverse Problems in Mechanics

Supplementary Materials to “Combining parametric, semi-parametric, and non-parametric survival models with stacked survival models”

Section 1 demonstrates the connection between the Brier Score in the absence of censoring versus the inverse probability-of-censoring weighted Brier Score. Section 2 derives the meansquared error decomposition presented in Section 3 of the main paper, and presents illustrations and examples regarding the impact of candidate survival models on performance. In addition, a simple example illustrat...

Sensitivity Analysis of Simulation Models

This contribution presents an overview of sensitivity analysis of simulation models, including the estimation of gradients. It covers classic designs and their corresponding (meta)models; namely, resolution-III designs including fractional-factorial twolevel designs for …rst-order polynomial metamodels, resolution-IV and resolution-V designs for metamodels augmented with twofactor interactions,...

Uncertainty and Sensitivity Analysis in Complex Plasma Chemistry Models

The purpose of a plasma chemistry model is prediction of chemical species densities, including understanding the mechanisms by which such species are formed. These aims are compromised by an uncertain knowledge of the rate constants included in the model, which directly causes uncertainty in the model predictions. We recently showed that this predictive uncertainty can be large—a factor of ten ...