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Artificial intelligence based approach for electrical load forecasting compared with stochastic modelling / Ahmed Seif Elnasr Mohammed Gabr ; Supervised Ossama Y. Abulhaggag , M. A. Moustafa Hassan

By: Contributor(s): Material type: TextTextLanguage: English Publication details: Cairo : Ahmed Seif Elnasr Mohammed Gabr , 2011Description: 114 P. : charts ; 30cmOther title:
  • التنبؤ بالحمل الكهربى باستخدم الذكاء الاصطناعى ومقارنتة بالنمذجة العشوائية [Added title page title]
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  • Issued also as CD
Dissertation note: Thesis (M.Sc.) - Cairo University - Faculty of Engineering - Department of Electrical Power and Machines Summary: Electric load forecasting is crucial for managing electric power systems economically and safely . It is necessary for improving power grid management . Many techniques and approaches have been investigated to tackle this problem in tecent decades . These are often different in nature and apply different engineering considerations and economic analyses
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Item type Current library Home library Call number Copy number Status Date due Barcode
Thesis Thesis قاعة الرسائل الجامعية - الدور الاول المكتبة المركزبة الجديدة - جامعة القاهرة Cai01.13.07.M.Sc.2011.Ah.A (Browse shelf(Opens below)) Not for loan 01010110055624000
CD - Rom CD - Rom مخـــزن الرســائل الجـــامعية - البدروم المكتبة المركزبة الجديدة - جامعة القاهرة Cai01.13.07.M.Sc.2011.Ah.A (Browse shelf(Opens below)) 55624.CD Not for loan 01020110055624000

Thesis (M.Sc.) - Cairo University - Faculty of Engineering - Department of Electrical Power and Machines

Electric load forecasting is crucial for managing electric power systems economically and safely . It is necessary for improving power grid management . Many techniques and approaches have been investigated to tackle this problem in tecent decades . These are often different in nature and apply different engineering considerations and economic analyses

Issued also as CD

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