How to use ANFIS Toolbox in MATLAB
In this MATLAB tutorial, the presenter introduces the Adaptive Neuro-Fuzzy Inference System (ANFIS) toolbox for population prediction. ANFIS is a hybrid system combining the merits of neural networks and fuzzy logic. It is designed to adaptively adjust its parameters using an optimization algorithm.
The tutorial demonstrates how to use the ANFIS toolbox with an example of population prediction. The data is sourced from Wikipedia, containing population values over different years. The steps are outlined as follows:
Load the population data into MATLAB.
Create a matrix with two columns, representing years and corresponding populations.
Use the ANFIS toolbox for population prediction.
Train the ANFIS model using the generated data and optimize its parameters.
Test the trained model with different years to predict population values.
The tutorial highlights the process of generating initial fuzzy rules using grid partitioning and training the ANFIS model with various parameters. The presenter discusses the importance of optimizing the model to achieve minimum error, emphasizing the mean squared error.
After training, the presenter exports the ANFIS model to a file for later use. Testing the model with specific years demonstrates its predictive capabilities. The tutorial concludes by saving the trained ANFIS model for future use.
In summary, the tutorial provides a comprehensive guide on using the ANFIS toolbox in MATLAB for population prediction, covering data preparation, model training, optimization, testing, and model export. The tutorial encourages viewers to subscribe to the channel for more content.