Improved bacterial foraging optimization algorithm with machine learning-driven short-term electricity load forecasting: a case study in peninsular Malaysia
Accurate electricity demand forecasting is crucial for ensuring the sustainability and reliability of power systems. Least square support vector machines (LSSVM) are well suited to handle complex non-linear power load series. However, the less optimal regularization parameter and the Gaussian kernel...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Multidisciplinary Digital Publishing Institute
2024
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| Online Access: | http://psasir.upm.edu.my/id/eprint/114311/1/114311.pdf http://psasir.upm.edu.my/id/eprint/114311/ https://www.mdpi.com/1999-4893/17/11/510 |
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