Impact-Site-Verification: dbe48ff9-4514-40fe-8cc0-70131430799e

## Search This Blog

Curve fitting is a technique used to fit mathematical models to your data, helping you understand the relationship between different factors within your data set. Learn how to apply various curve fitting techniques using MATLAB® to wind turbine analysis with the aim of understanding how various factors influence power output.

With MATLAB, you can:

- Interactively fit curves and surfaces to your data using the Curve Fitter app: https://bit.ly/3xFxIVe

- Explore higher dimensional models through linear and nonlinear regression methods from Statistics and Machine Learning Toolbox™:  https://bit.ly/441Cok0

- Optimize fitted models by specifying bounds and constraints with the functionality from Optimization Toolbox™: https://bit.ly/3Jh6s1w

- Incorporate your curve fits from the Curve Fitter app as a lookup table for use in Simulink®: https://bit.ly/3TX90XJ

Related videos:

- Curve Fitting Toolbox Product Overview:

• What Is Curve Fitting Toolbox?

- Low-Code Data Analysis with MATLAB: https://bit.ly/3vYWgI0

- How to Fit a Linear Regression Model in MATLAB:

• How to Fit a Linear Regression Model ...

Chapters:

00:23 – What is Curve Fitting?

01:32 – Overview of different fitting techniques covered in this video

02:03 – Example: Wind turbine analysis

02:55 – Curve Fitting using the Curve Fitter App

04:21 – Non-linear regression model to capture effects of various factors

05:18 – Optimizing fitted model coefficients

07:06 – Incorporating curve fit into Simulink

08:05 – Conclusion