Using artificial neural networks models for predicting pancreas behavior
العناوين الأخرى
استخدام الشبكات العصوبنية في التنبؤ في سلوك البنكرياس
مقدم أطروحة جامعية
مشرف أطروحة جامعية
الجامعة
جامعة فيلادلفيا
الكلية
كلية تكنولوجيا المعلومات
القسم الأكاديمي
قسم علم الحاسوب
دولة الجامعة
الأردن
الدرجة العلمية
ماجستير
تاريخ الدرجة العلمية
2008
الملخص الإنجليزي
-Artificial Neural Network (ANN) is currently a 'hot' research area in medicine and this work is based on predicting the behavior of an organ of a human body called pancreas by using neural networks.
Neural networks, with their remarkable ability to derive meaning from complicated or imprecise data, can be used to extract patterns and detect trends that are too complex to be noticed by either humans or other computer techniques.
Their ability to learn by example makes them very flexible and powerful.
So we have data set from 102 of three different groups of subjects.
From data set examples, neural networks were learned by using two algorithms, Radial Basis Function (RBF) and General regression Neural Network (GRNN).
After learning, a simulation (testing) for learned data has been made and a comparison between both algorithms has been done subject to the learning performance.
Furthermore a comparison between RBF and GRNN algorithms was done based on the ability of both networks to generalize input data not seen before.
All simulations were made by MATLAB 7 neural network toolbox and the results showed that RBF and GRNN are good function approximators.
It was noticeable that RBF and GRNN were fast training algorithms even GRNN was faster.
It was apparent that neural network was a good choice for predicting a behavior of nonlinear and complex systems such as pancreas.
Also the results showed that the performance of RBF in learning was better than GRNN, and the ability of GRNN in generalization or testing was better than RBF.
التخصصات الرئيسية
الموضوعات
عدد الصفحات
76
قائمة المحتويات
Table of contents.
Abstract.
Abstract in Arabic.
Chapter One : Introduction.
Chapter Two : A literature review of neural network algorithms used for regulating glucose level.
Chapter Three : The pancreas and its endocrine system.
Chapter Four : Artificial neural networks algorithms for function approximation.
Chapter Five : Design and implementation.
Chapter Six : Results.
Chapter Seven : Conclusions and future work.
References.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Abid, Bassam Abd al-Rahman. (2008). Using artificial neural networks models for predicting pancreas behavior. (Master's theses Theses and Dissertations Master). Philadelphia University, Jordan
https://search.emarefa.net/detail/BIM-546112
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Abid, Bassam Abd al-Rahman. Using artificial neural networks models for predicting pancreas behavior. (Master's theses Theses and Dissertations Master). Philadelphia University. (2008).
https://search.emarefa.net/detail/BIM-546112
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Abid, Bassam Abd al-Rahman. (2008). Using artificial neural networks models for predicting pancreas behavior. (Master's theses Theses and Dissertations Master). Philadelphia University, Jordan
https://search.emarefa.net/detail/BIM-546112
لغة النص
الإنجليزية
نوع البيانات
رسائل جامعية
رقم السجل
BIM-546112
قاعدة معامل التأثير والاستشهادات المرجعية العربي "ارسيف Arcif"
أضخم قاعدة بيانات عربية للاستشهادات المرجعية للمجلات العلمية المحكمة الصادرة في العالم العربي
تقوم هذه الخدمة بالتحقق من التشابه أو الانتحال في الأبحاث والمقالات العلمية والأطروحات الجامعية والكتب والأبحاث باللغة العربية، وتحديد درجة التشابه أو أصالة الأعمال البحثية وحماية ملكيتها الفكرية. تعرف اكثر
