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العنوان
Kernel-based swarm optimization for renewable energy application /
الناشر
Sarah Osama Talaat Ibrahim ,
المؤلف
Sarah Osama Talaat Ibrahim
هيئة الاعداد
باحث / Sarah Osama Talaat Ibrahim
مشرف / Aly Aly Fahmy
مشرف / Aboul Ella Hassanien
مشرف / Essam Halim Houssein
تاريخ النشر
2018
عدد الصفحات
102 Leaves :
اللغة
الإنجليزية
الدرجة
ماجستير
التخصص
Computer Science (miscellaneous)
تاريخ الإجازة
1/1/2018
مكان الإجازة
جامعة القاهرة - كلية الحاسبات و المعلومات - computer science
الفهرس
Only 14 pages are availabe for public view

from 126

from 126

Abstract

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