| Type of Material: | Thesis |
| Title: | Short-term prediction of wind speed and wind power using hybrid signal processing and machine learning techniques |
| Researcher: | Naik, Jyotirmayee |
| Guide: | Dash, P.K. |
| Department: | Department of Electrical Engineering |
| Publisher: | Siksha O Anusandhan University |
| Place: | Bhubaneswar |
| Year: | 2022 |
| Language: | English |
| Subject: | Short-term prediction | Wind speed | Wind power | Hybrid signal | Machine learning techniques | Electrical Engineering |
| Dissertation/Thesis Note: | PhD |
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| 001 | 445689 | |
| 003 | IN-AhILN | |
| 005 | 2023-01-19 15:17:25 | |
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| 100 | __ | |aNaik, Jyotirmayee|eResearcher |
| 110 | __ | |aDepartment of Electrical Engineering|bSiksha O Anusandhan University|dBhubaneswar |
| 245 | __ | |aShort-term prediction of wind speed and wind power using hybrid signal processing and machine learning techniques |
| 260 | __ | |aBhubaneswar|bSiksha O Anusandhan University|c2022 |
| 502 | __ | |bPhD |
| 650 | __ | |aElectrical Engineering|2UGC |
| 653 | __ | |aShort-term prediction |
| 653 | __ | |aWind speed |
| 653 | __ | |aWind power |
| 653 | __ | |aHybrid signal |
| 653 | __ | |aMachine learning techniques |
| 700 | __ | |aDash, P.K.|eGuide |
| 905 | __ | |anotification |
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