A new technique combining semi-supervised and active learning for non-intrusive load monitoring / Ahmed Mohamed Fatouh Ahmed ; Supervised Omar Ahmed Ali Nasr
Material type:
- دمج التعلم الشبه إشرافي والتعلم النشط كأسلوب جديد في المتابعة الغير متداخلة للأحمال [Added title page title]
- Issued also as CD
Item type | Current library | Home library | Call number | Copy number | Status | Barcode | |
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قاعة الرسائل الجامعية - الدور الاول | المكتبة المركزبة الجديدة - جامعة القاهرة | Cai01.13.08.M.Sc.2019.Ah.N (Browse shelf(Opens below)) | Not for loan | 01010110079270000 | ||
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مخـــزن الرســائل الجـــامعية - البدروم | المكتبة المركزبة الجديدة - جامعة القاهرة | Cai01.13.08.M.Sc.2019.Ah.N (Browse shelf(Opens below)) | 79270.CD | Not for loan | 01020110079270000 |
Thesis (M.Sc.) - Cairo University - Faculty of Engineering - Department of Electronics And Communications
The current work introduces a new technique that leverages both the semi-supervised and active learning together to the benefit of non-intrusive load monitoring, that is the procedure used to disaggregate the contributions of different appliances in a building. The main idea is that semi-supervised learning improves the results of active learning aiming to decrease the need to the user. Two different approaches were utilized, one used active and reactive power features and the other used current waveform harmonics to use them later in the machine learning model
Issued also as CD
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