[Power System] Power Consumption Prediction Based on Matlab SVM

Table of contents

Prediction of power consumption based on matlab SVM

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Prediction of power consumption based on matlab SVM

The basic steps of using the SVM algorithm in MATLAB for electricity consumption forecasting are as follows:

1. Collect power data and import it into MATLAB. You can use the database that comes with MATLAB (such as load nile), or you can read data from a file.

2. Preprocess the data for later modeling with SVM. This step includes operations such as data cleaning and data normalization.

3. Divide the dataset into training and testing sets. You can use the cvpartition function that comes with MATLAB to randomly divide the data set into a training set and a test set.

4. Use the svmtrain function to train the SVM model. Before training the SVM model, it is necessary to select hyperparameters such as the kernel function type, kernel function parameters, and software upper limit used by the SVM classifier.

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