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Applications and development of stochastic global optimization methods for thermodynamic problems / Ahmed Mohamed Elsayed Ahmed Aly Khalil ; Supervised Mai K. Fouad , Seif-Eddeen K. Fateen

By: Contributor(s): Material type: TextTextLanguage: English Publication details: Cairo : Ahmed Mohamed Elsayed Ahmed Aly Khalil , 2014Description: 115 P. : charts , facsimiles ; 30cmOther title:
  • تطبيق طرق الامثلة العشوائية وتطويرها فى حل مسائل الديناميكا الحرارية [Added title page title]
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Dissertation note: Thesis (M.Sc.) - Cairo University - Faculty of Engineering - Department of Chemical Engineering Summary: Thermodynamic problems of phase stability and phase equilibrium of reactive and non-reactive systems were evaluated using three stochastic swarm algorithms. These algorithms were Monkey Algorithm (MA), Gravitational Search Algorithm (GSA), and Krill Herd Algorithm (KHA). Then a new developed hybrid, MAKHA was found to be more reliable and more efficient in solving 24 out of the 27 tested benchmark problems compared to the performance of its two parent algorithms, MA and KHA. Also MAKHA outperformed its parent algorithms in solving nine difficult thermodynamic problems
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Item type Current library Home library Call number Copy number Status Barcode
Thesis Thesis قاعة الرسائل الجامعية - الدور الاول المكتبة المركزبة الجديدة - جامعة القاهرة Cai01.13.04.M.Sc.2014.Ah.A (Browse shelf(Opens below)) Not for loan 01010110064647000
CD - Rom CD - Rom مخـــزن الرســائل الجـــامعية - البدروم المكتبة المركزبة الجديدة - جامعة القاهرة Cai01.13.04.M.Sc.2014.Ah.A (Browse shelf(Opens below)) 64647.CD Not for loan 01020110064647000

Thesis (M.Sc.) - Cairo University - Faculty of Engineering - Department of Chemical Engineering

Thermodynamic problems of phase stability and phase equilibrium of reactive and non-reactive systems were evaluated using three stochastic swarm algorithms. These algorithms were Monkey Algorithm (MA), Gravitational Search Algorithm (GSA), and Krill Herd Algorithm (KHA). Then a new developed hybrid, MAKHA was found to be more reliable and more efficient in solving 24 out of the 27 tested benchmark problems compared to the performance of its two parent algorithms, MA and KHA. Also MAKHA outperformed its parent algorithms in solving nine difficult thermodynamic problems

Issued also as CD

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