Optimization of short-term wind power prediction of Multi-kernel Extreme Learning Machine based on Sparrow Search Algorithm

Aiming at the problem that the single kernel function of kernel extreme learning machine (KELM) cannot adapt to the variable actual wind power. This paper proposes a modified prediction model which can increase the accuracy of prediction. The prediction model uses multiple kernel functions instead o...

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Bibliographic Details
Published in:Journal of physics. Conference series Vol. 2527; no. 1; pp. 12075 - 12079
Main Authors: Wang, Fan, Gao, Guige
Format: Journal Article
Language:English
Published: Bristol IOP Publishing 01.06.2023
Subjects:
Accuracy
Artificial neural networks
Kernel functions
Machine learning
Optimization
Physics
Prediction models
Search algorithms
Wind power
ISSN:1742-6588, 1742-6596
Online Access:Get full text
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Summary:Aiming at the problem that the single kernel function of kernel extreme learning machine (KELM) cannot adapt to the variable actual wind power. This paper proposes a modified prediction model which can increase the accuracy of prediction. The prediction model uses multiple kernel functions instead of a single kernel function and optimizes the kernel parameters by using a sparrow search algorithm (SSA). Finally, through the simulation and comparison experiments, the proposed prediction model has better prediction accuracy than the conventional prediction model.
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ISSN:1742-6588
1742-6596
DOI:10.1088/1742-6596/2527/1/012075