Statistical Modeling and Boundary Conditions References

Hello

I want to develop a statistical model to estimate pressure on an object. I am new on this and just started reading literature. I am thinking to develop a boundary condition for the normal (original, undeformed) object and then apply an interpolation and a curve fitting solution for all conditions between maximum and minimum states of deformation. I have data for various (random) loads and deformations of the object from testing set. I just need to define its maximum force (load) and its maximum deformation and the same done for minimum states. Those are going to be my limits and all states in between will be interpolated to give me the loads and deformations. The zero state will be the boundary condition assigned to its original undeformed state. The undefromed state will be defined by a mesh generation or contour defined from edges.

The material is a nonlinear viscoelastic one.

I need suggestions, references anything.

Thanks for your time, reading this.

Answer 1

[Yogesh Khurana]

MATLAB’s Statistical and Machine Learning Toolbox provides functions and apps to describe, analyze and model the data according to your requirement. If you are new to Machine Learning I would suggest you to please refer some online courses. If you are new to MATLAB and its toolboxes in Machine Learning., I would suggest you refer to some of the links given below. MATLAB’s features documentation also contains a dub section of references at the last. You can also refer to these references to get an idea of how the features are implemented.

Please refer to following links for more information:

https://in.mathworks.com/products/statistics.html#machine-learning

https://in.mathworks.com/help/curvefit/linear-and-nonlinear-regression.html

https://in.mathworks.com/help/curvefit/fit.html

https://in.mathworks.com/help/curvefit/curve-fitting.html

Hope this helps!