Use of Wavelet and Bootstrap Methods in Streamflow Prediction
Streamflow prediction is vital to control the effects of floods and mitigation. Physical prediction model often provides satisfactory results, but these models require massive computational work and hydrogeomorphological variables to develop a prediction system. At the same time, data-driven predict...
| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Hindawi Limited
2023-01-01
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| Series: | Journal of Mathematics |
| Online Access: | http://dx.doi.org/10.1155/2023/4222934 |
| _version_ | 1811158491965947904 |
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| author | Adnan Bashir Muhammad Ahmed Shehzad Aamna Khan Ayesha Niaz Muhammad Nabeel Asghar Ramy Aldallal Mutua Kilai |
| author_facet | Adnan Bashir Muhammad Ahmed Shehzad Aamna Khan Ayesha Niaz Muhammad Nabeel Asghar Ramy Aldallal Mutua Kilai |
| author_sort | Adnan Bashir |
| collection | DOAJ |
| description | Streamflow prediction is vital to control the effects of floods and mitigation. Physical prediction model often provides satisfactory results, but these models require massive computational work and hydrogeomorphological variables to develop a prediction system. At the same time, data-driven prediction models are quick to apply, easy to handle, and reliable. This study investigates a new hybrid model, the wavelet bootstrap quadratic response surface, for accurate streamflow prediction. Wavelet analysis is a well-known time-frequency joint analysis technique applied in various fields like biological signals, vibration signals, and hydrological signals. The wavelet analysis is used to denoise the time series data. Bootstrap is a nonparametric method for removing uncertainty that uses an intensive resampling methodology with replacement. The authors analyzed the results of the studied models with different statistical metrics, and it has been observed that the wavelet bootstrap quadratic response surface model provides the most efficient results. |
| first_indexed | 2024-04-10T05:25:36Z |
| format | Article |
| id | doaj.art-40aaecc7f3e346c2be8acd90cdcc25a0 |
| institution | Directory Open Access Journal |
| issn | 2314-4785 |
| language | English |
| last_indexed | 2024-04-10T05:25:36Z |
| publishDate | 2023-01-01 |
| publisher | Hindawi Limited |
| record_format | Article |
| series | Journal of Mathematics |
| spelling | doaj.art-40aaecc7f3e346c2be8acd90cdcc25a02023-03-08T00:00:34ZengHindawi LimitedJournal of Mathematics2314-47852023-01-01202310.1155/2023/4222934Use of Wavelet and Bootstrap Methods in Streamflow PredictionAdnan Bashir0Muhammad Ahmed Shehzad1Aamna Khan2Ayesha Niaz3Muhammad Nabeel Asghar4Ramy Aldallal5Mutua Kilai6Department of StatisticsDepartment of StatisticsDepartment of StatisticsDepartment of StatisticsDepartment of Computer ScienceDepartment of AccountingDepartment of MathematicsStreamflow prediction is vital to control the effects of floods and mitigation. Physical prediction model often provides satisfactory results, but these models require massive computational work and hydrogeomorphological variables to develop a prediction system. At the same time, data-driven prediction models are quick to apply, easy to handle, and reliable. This study investigates a new hybrid model, the wavelet bootstrap quadratic response surface, for accurate streamflow prediction. Wavelet analysis is a well-known time-frequency joint analysis technique applied in various fields like biological signals, vibration signals, and hydrological signals. The wavelet analysis is used to denoise the time series data. Bootstrap is a nonparametric method for removing uncertainty that uses an intensive resampling methodology with replacement. The authors analyzed the results of the studied models with different statistical metrics, and it has been observed that the wavelet bootstrap quadratic response surface model provides the most efficient results.http://dx.doi.org/10.1155/2023/4222934 |
| spellingShingle | Adnan Bashir Muhammad Ahmed Shehzad Aamna Khan Ayesha Niaz Muhammad Nabeel Asghar Ramy Aldallal Mutua Kilai Use of Wavelet and Bootstrap Methods in Streamflow Prediction Journal of Mathematics |
| title | Use of Wavelet and Bootstrap Methods in Streamflow Prediction |
| title_full | Use of Wavelet and Bootstrap Methods in Streamflow Prediction |
| title_fullStr | Use of Wavelet and Bootstrap Methods in Streamflow Prediction |
| title_full_unstemmed | Use of Wavelet and Bootstrap Methods in Streamflow Prediction |
| title_short | Use of Wavelet and Bootstrap Methods in Streamflow Prediction |
| title_sort | use of wavelet and bootstrap methods in streamflow prediction |
| url | http://dx.doi.org/10.1155/2023/4222934 |
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