Kernel-based swarm optimization for renewable energy application / Sarah Osama Talaat Ibrahim ; Supervised Aly Aly Fahmy , Aboul Ella Hassanien
Material type:
TextLanguage: English Publication details: Cairo : Sarah Osama Talaat Ibrahim , 2018Description: 102 Leaves : charts , facsimiles ; 30cmOther title: - أمثلية الذكاء السربي المعتمد على دالة النواة لتطبيقات الطاقة المتجددة [Added title page title]
- Issued also as CD
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Thesis
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قاعة الرسائل الجامعية - الدور الاول | المكتبة المركزبة الجديدة - جامعة القاهرة | Cai01.20.03.M.Sc.2018.Sa.K (Browse shelf(Opens below)) | Not for loan | 01010110077124000 | ||
CD - Rom
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مخـــزن الرســائل الجـــامعية - البدروم | المكتبة المركزبة الجديدة - جامعة القاهرة | Cai01.20.03.M.Sc.2018.Sa.K (Browse shelf(Opens below)) | 77124.CD | Not for loan | 01020110077124000 |
Thesis (M.Sc.) - Cairo University - Faculty of Computers and Information - Department of Computer Science
Forecasting wind and solar behaviors (e.g., wind speed and global solar radiation) is importantfor energy managers and electricity traders. Moreover, the scientific prediction methods for renewable energy can improve the reliability and efficiency of the renewable power generation units. In the last few years, Support Vector Regression (SVR) has been applied to forecast the renewable energy. The performance and stability of SVR depend on their meta-parameters
Issued also as CD
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