header
Image from OpenLibrary

Adaptive neuro-fuzzy system for hemodialysis treatment process / Ahmad Taher Saleh Azar ; Supervised Ahmed Hisham Kandil , Khaled M. A. Wahba , Ahmed M. Elgarhy

By: Contributor(s): Material type: TextTextLanguage: eng Publication details: Cairo : Ahmad Taher Saleh Azar , 2009Description: 373 P. : plans ; 30cmOther title:
  • نظام عصبى مبهم لعملية معالجة الغسيل الكلوى [Added title page title]
Subject(s): Available additional physical forms:
  • Issued also as CD
Dissertation note: Thesis (Ph.D.) - Cairo University - Faculty of Engineering - Department of System and Biomedical Engineering Summary: This thesis targets the task of predictive modeling and focuses on the adaptive neuro-fuzzy system for predictive modeling of dialysis variables. The aim is to extract models from data that not only have the required performance, but are also relatively interpretable. A novel automatic modeling methodology is developed, which supports both accurate prediction and interpretability in order to avoid blood urea samples during dialysis session
Tags from this library: No tags from this library for this title. Log in to add tags.
Star ratings
    Average rating: 0.0 (0 votes)
Holdings
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 Cai01.13.03.Ph.D.2009.Ah.A (Browse shelf(Opens below)) Not for loan 01010110051383000
CD - Rom CD - Rom مخـــزن الرســائل الجـــامعية - البدروم المكتبة المركزبة الجديدة - جامعة القاهرة Cai01.13.03.Ph.D.2009.Ah.A (Browse shelf(Opens below)) 51383.CD Not for loan 01020110051383000

Thesis (Ph.D.) - Cairo University - Faculty of Engineering - Department of System and Biomedical Engineering

This thesis targets the task of predictive modeling and focuses on the adaptive neuro-fuzzy system for predictive modeling of dialysis variables. The aim is to extract models from data that not only have the required performance, but are also relatively interpretable. A novel automatic modeling methodology is developed, which supports both accurate prediction and interpretability in order to avoid blood urea samples during dialysis session

Issued also as CD

There are no comments on this title.

to post a comment.