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A novel Modular form of rough decision models / Ahmed Taisser Shawky ; Supervised Ashraf H. Abdelwahab , Hesham A. Hefny

By: Contributor(s): Material type: TextTextLanguage: English Publication details: Cairo : Ahmed Taisser Shawky , 2014Description: 192 Leaves : forms ; 30cmOther title:
  • شكل وحداتى جديد لنماذج إتخاذ القرار التقريبية [Added title page title]
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  • Issued also as CD
Dissertation note: Thesis (Ph.D.) - Cairo University - Institute of Statistical Studies and Researches - Department of Computer and Information Sciences Summary: Many real world applications need to deal with huge amount of data. Therefore, there is a need for new techniques which can manage the data with such magnitude. Also, the variety of decision makers and the variance of their visions can cause inconsistency in decisions. Modularity techniques are appropriate for dealing with complexity of data to support decision makers. The difference in visions of decision makers requires dealing with data in the framework of inaccuracy. Computational Intelligence (CI) techniques like genetic algorithms, neural networks, and fuzzy logic are effective for dealing with imprecise data to support decision makers. Now using rough sets is getting quite necessary to be used for its ability to mining such type of data
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Thesis Thesis قاعة الرسائل الجامعية - الدور الاول المكتبة المركزبة الجديدة - جامعة القاهرة Cai01.18.02.Ph.D.2014.Ah.N (Browse shelf(Opens below)) Not for loan 01010110064966000
CD - Rom CD - Rom مخـــزن الرســائل الجـــامعية - البدروم المكتبة المركزبة الجديدة - جامعة القاهرة Cai01.18.02.Ph.D.2014.Ah.N (Browse shelf(Opens below)) 64966.CD Not for loan 01020110064966000

Thesis (Ph.D.) - Cairo University - Institute of Statistical Studies and Researches - Department of Computer and Information Sciences

Many real world applications need to deal with huge amount of data. Therefore, there is a need for new techniques which can manage the data with such magnitude. Also, the variety of decision makers and the variance of their visions can cause inconsistency in decisions. Modularity techniques are appropriate for dealing with complexity of data to support decision makers. The difference in visions of decision makers requires dealing with data in the framework of inaccuracy. Computational Intelligence (CI) techniques like genetic algorithms, neural networks, and fuzzy logic are effective for dealing with imprecise data to support decision makers. Now using rough sets is getting quite necessary to be used for its ability to mining such type of data

Issued also as CD

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