Optimal short term load forecasting using LSSVM and improved BFOA considering Malaysia pandemic disrupted situation
The COVID-19 pandemic's unprecedented disruptions significantly impacted electricity demand patterns across the globe. In Peninsular Malaysia, strict lockdown measures (Movement Control Orders - MCOs) led to the closure of non-essential businesses and stay-at-home orders. These sudden and drama...
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| Format: | Thesis |
| Language: | English English |
| Published: |
2024
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| Online Access: | http://eprints.utem.edu.my/id/eprint/28544/1/Optimal%20short%20term%20load%20forecasting%20using%20LSSVM%20and%20improved%20BFOA%20considering%20Malaysia%20pandemic%20disrupted%20situation.pdf http://eprints.utem.edu.my/id/eprint/28544/2/Optimal%20short%20term%20load%20forecasting%20using%20LSSVM%20and%20improved%20BFOA%20considering%20Malaysia%20pandemic%20disrupted%20situation.pdf http://eprints.utem.edu.my/id/eprint/28544/ https://plh.utem.edu.my/cgi-bin/koha/opac-detail.pl?biblionumber=124368 |
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http://eprints.utem.edu.my/id/eprint/28544/1/Optimal%20short%20term%20load%20forecasting%20using%20LSSVM%20and%20improved%20BFOA%20considering%20Malaysia%20pandemic%20disrupted%20situation.pdfhttp://eprints.utem.edu.my/id/eprint/28544/2/Optimal%20short%20term%20load%20forecasting%20using%20LSSVM%20and%20improved%20BFOA%20considering%20Malaysia%20pandemic%20disrupted%20situation.pdf
http://eprints.utem.edu.my/id/eprint/28544/
https://plh.utem.edu.my/cgi-bin/koha/opac-detail.pl?biblionumber=124368