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?  
LowCode 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 – Nonlinear regression model to capture effects of various factors
05:18 – Optimizing fitted model coefficients
07:06 – Incorporating curve fit into Simulink
08:05 – Conclusion


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