Fitting hyperelastic models to experimental data

Fitting hyperelastic models to experimental data

This paper is concerned with determining material parameters in incompressible isotropic elastic strain–energy functions on the basis of a non-linear least squares optimization method by fitting data from the classical experiments of Treloar and Jones and Treloar on natural rubber. We consider three separate forms of strain-energy function, based respectively on use of the principal stretches, ...

Fitting Models to Grouped Data

Fitting straight lines to experimental data.

The problem associated with use of statistical methods for determining a best linear relationship of the form Y = AX +B have been examined for a condition quite prevalent with experimental research, i.e., when the values of both variables are subject to essentially unknown errors. Under this condition standard least-squares regression analysis underestimates the value of the slope A. A very sim...

a new approach to credibility premium for zero-inflated poisson models for panel data

هدف اصلی از این تحقیق به دست آوردن و مقایسه حق بیمه باورمندی در مدل های شمارشی گزارش نشده برای داده های طولی می باشد. در این تحقیق حق بیمه های پبش گویی بر اساس توابع ضرر مربع خطا و نمایی محاسبه شده و با هم مقایسه می شود. تمایل به گرفتن پاداش و جایزه یکی از دلایل مهم برای گزارش ندادن تصادفات می باشد و افراد برای استفاده از تخفیف اغلب از گزارش تصادفات با هزینه پائین خودداری می کنند، در این تحقیق ...

Fitting models to data: Accuracy, Speed, Robustness

In vision and machine learning, almost everything we do may be considered to be a form of model fitting. Whether estimating the parameters of a convolutional neural network, target tracking, computing low-dimensional representations of datasets, computing structure and motion from image collections, estimating parameters for an inference model such as Markov random fields, or pretty much anythi...