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A hybrid approach for generating futures scenarios / Amany Mohamed Mamdouh Mohamed Mounier ; Supervised Mohammed H. Rasmy , Abdelhady N. Ahmed , Mohamed Mostafa Saleh

By: Contributor(s): Material type: TextTextLanguage: English Publication details: Cairo : Amany Mohamed Mamdouh Mohamed Mounier , 2015Description: 112 Leaves : charts ; 30cmOther title:
  • أسلوب مهجن لتوليد السيناريوهات المستقبلية [Added title page title]
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  • Issued also as CD
Dissertation note: Thesis (M.Sc.) - Cairo University - Faculty of Computers and Information - Department of Operations Research and Decision Support Summary: Decisions are made for the future, Futures Studies investigate possible fan of futures scenarios and its probabilities for easier decision making processes, taking into consideration unprecedented future events (wildcards) for clear vision of the future. Markov Chain method generally used as a mean of characterizing or summarizing data and of projecting the time path of certain variables. The main ideas of this paper rely on using the slope and curvature of variables historical data time series to convert it to historical states time series, followed by Association Rule Mining to build a Markov Chain Transition Probability Matrix from the variables historical states time series. Finally we introduce hybridization between the Futures Studies and Markov chain by building "a Dynamic Multiplicative Model for Probability Impact Analysis". Our introduced methodologies allow studying the occurrence impact of multiple wildcards on multiple variables states' probabilities at future years
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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 Cai01.20.02.M.Sc.2015.Am.H (Browse shelf(Opens below)) Not for loan 01010110066369000
CD - Rom CD - Rom مخـــزن الرســائل الجـــامعية - البدروم المكتبة المركزبة الجديدة - جامعة القاهرة Cai01.20.02.M.Sc.2015.Am.H (Browse shelf(Opens below)) 66369.CD Not for loan 01020110066369000

Thesis (M.Sc.) - Cairo University - Faculty of Computers and Information - Department of Operations Research and Decision Support

Decisions are made for the future, Futures Studies investigate possible fan of futures scenarios and its probabilities for easier decision making processes, taking into consideration unprecedented future events (wildcards) for clear vision of the future. Markov Chain method generally used as a mean of characterizing or summarizing data and of projecting the time path of certain variables. The main ideas of this paper rely on using the slope and curvature of variables historical data time series to convert it to historical states time series, followed by Association Rule Mining to build a Markov Chain Transition Probability Matrix from the variables historical states time series. Finally we introduce hybridization between the Futures Studies and Markov chain by building "a Dynamic Multiplicative Model for Probability Impact Analysis". Our introduced methodologies allow studying the occurrence impact of multiple wildcards on multiple variables states' probabilities at future years

Issued also as CD

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