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Doctor of Philosophy（Knowledge Science） >
R06) (Jun.2024 - Mar.2025 >
Please use this identifier to cite or link to this item:
http://hdl.handle.net/10119/19378
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| Title: | COVID-19による混乱状況下での日次需要予測のためのハイブリッドモデルに関する研究: タイ王国における電力消費量の予測応用 |
| Authors: | Lalitpat, Aswanuwath |
| Authors(alternative): | らりぱっと, あさわぬわっと |
| Keywords: | hybrid approach
daily peak load forecasting
disrupted situation
VMD
EDM
FFT
similar day selection method
stepwise regression
artificial neural network
long short-term memory
COVID-19 |
| Issue Date: | Sep-2024 |
| Description: | Supervisor:HUYNH, Van Nam
先端科学技術研究科
博士 |
| Title(English): | A Study on Hybrid Models for Daily Demand Forecasting in Disrupted Situations: Application to Predict Thailand's Electricity Consumption During COVID-19 |
| Authors(English): | Lalitpat, Aswanuwath |
| Language: | eng |
| URI: | http://hdl.handle.net/10119/19378 |
| Academic Degrees and number: | 甲第1479号 |
| Degree-granting date: | 2024-09-24 |
| Degree name: | 博士(知識科学) |
| Degree-granting institutions: | 北陸先端科学技術大学院大学 |
| Appears in Collections: | D-KS. 2024年度(R06) (Jun.2024 - Mar.2025)
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Files in This Item:
| File |
Description |
Size | Format |
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| abstract.pdf | 要旨 | 101Kb | Adobe PDF | View/Open | | paper.pdf | 本文 | 2100Kb | Adobe PDF | View/Open | | summary.pdf | 内容の要旨及び論文審査の結果の要旨 | 221Kb | Adobe PDF | View/Open |
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