Power load forecasting based on LSTM Adaboost

Version 1.0.0 (3.17 KB) by ZHANG muzhi
The LSTM AdaBoost load forecasting model first trains multiple base learners in series using the AdaBoost ensemble algorithm and calculates
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Updated 2 Aug 2024

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The LSTM AdaBoost load forecasting model first trains multiple base learners in series using the AdaBoost ensemble algorithm and calculates the weight coefficients of each base learner. Then, the prediction results of each base learner are linearly combined to generate the final prediction result

Cite As

ZHANG muzhi (2025). Power load forecasting based on LSTM Adaboost (https://se.mathworks.com/matlabcentral/fileexchange/170766-power-load-forecasting-based-on-lstm-adaboost), MATLAB Central File Exchange. Retrieved .

MATLAB Release Compatibility
Created with R2024a
Compatible with any release
Platform Compatibility
Windows macOS Linux
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Version Published Release Notes
1.0.0