Using Artificial Intelligence Models in System Identification / Wesam Samy Mohammed Elshamy ; Supervised Ahmed Bahgat Gamal Bahgat , Hassan Mohammed Rashad
Language: Eng Publication details: Cairo : Wesam Samy Mohammed Elshamy , 2007Description: 155P. : charts ; 30cmOther title:- استخدام نماذج الذكاء الاصطناعي في التعرف على النظم [Added title page title]
- Issued also as CD
Item type | Current library | Home library | Call number | Copy number | Status | Date due | Barcode | |
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Thesis | قاعة الرسائل الجامعية - الدور الاول | المكتبة المركزبة الجديدة - جامعة القاهرة | Cai01.13.07.M.Sc.2007.We.U (Browse shelf(Opens below)) | Not for loan | 01010110047194000 | |||
CD - Rom | مخـــزن الرســائل الجـــامعية - البدروم | المكتبة المركزبة الجديدة - جامعة القاهرة | Cai01.13.07.M.Sc.2007.We.U (Browse shelf(Opens below)) | 47194.CD | Not for loan | 01020110047194000 |
Thesis (M.Sc.) - Cairo University - Faculty Of Engineering - Department Of Electrical Power and Machines
In this research , Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) methods are modified to best suit the multimodal problem of system identification.In the first case , an extension to the basic GA was deployed by introducing redundant genetic material.While in the second case , the Clubs - based PSO (C - PSO) dynamic neighborhood structure was introduced.These models were used in the system identification problem of an induction motor.The results showed the superior performance of the PSO over the GA.Moreover , the C - PSO topology used significantly outperformed the other static topologies.
Issued also as CD
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