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العنوان
A HYBRID INTELLIGENT SYSTEM FOR DATABASE MINING \
الناشر
MAHA MOHAMED RSHAD MOHAMED ZEEDAN،
المؤلف
ZEEDAN, MAHA MOHAMED RSHAD MOHAMED.
هيئة الاعداد
باحث / MAHA MOHAMED RSHAD MOHAMED ZEEDAN
مشرف / IBRAHIM ZAKARIA MORSI
مناقش / ALAA EL-DINE MOHAMED RIAD
مناقش / WAIEL FATHI ABD EL-WAHED
الموضوع
Metals. Database. Electronic data processing. Distributed processing. NEURAL NETWORK.
تاريخ النشر
2008 .
عدد الصفحات
142 P. :
اللغة
الإنجليزية
الدرجة
ماجستير
التخصص
علوم الحاسب الآلي
تاريخ الإجازة
1/1/2008
مكان الإجازة
جامعة المنوفية - كلية الهندسة الإلكترونية - .COMPUTER ENGINEERING
الفهرس
Only 14 pages are availabe for public view

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Abstract

THE APPLICATIONS OF DATA MINING TECHNOLOGY IN THE FIELD OF FAULT DIAGNOSIS BECOME A HOT TOPIC FOR DECISION-MAKERS AS IT IS THE SEARCH FOR VALUABLE, NON TRIVIAL INFORMATION IN A LARGE AMOUNT OF HISTORICAL DATA USING THE ARTIFICIAL INTELLIGENCE TECHNIQUES. DATA MINING DIFFERS from OTHER DATA ACCESS MECHANISMS BOTH IN PROCESS AND TECHNIQUE.
A TYPICAL DATA MINING SYSTEM CONSISTS CONSISTS OF A DATA MINING MODELS IN THE PROCESS. THE MODELS CAN TAKE THA FORM OF A GRAPHICAL REPRESENTATION. THE MODELS CAN TAKE THE FORM OF A GRAPHICAL REPRESENTATION, A NEURAL NETWORK OR EVEN A COLLECTION OF RULES. such models capture the essential characteristics of the undeerlying data, helpiing humans gain new insights and knowledge from the data. the actual data is obtained via a database connection. for classification models, the result of the built model is the bast prediction for target value in each record of the stored databased.