A decision support system using Neurofuzzy algorithm methods in selecting lecturer's teaching work load for bachelor in multimedia / Asmaa Musa

A large nimiber of techniques, such as Neurofuzzy algorithm methods are used to produce an efficient and effective system. A key stage in the system process is the selection of features. This paper discuss about a decision support system using Neurofuzzy algorithm methods in selecting lecturer�...

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Main Author: Musa, Asmaa
Format: Thesis
Language:English
Published: 2007
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Online Access:https://ir.uitm.edu.my/id/eprint/1380/2/1380.pdf
https://ir.uitm.edu.my/id/eprint/1380/
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spelling my.uitm.ir.13802024-08-20T15:32:55Z https://ir.uitm.edu.my/id/eprint/1380/ A decision support system using Neurofuzzy algorithm methods in selecting lecturer's teaching work load for bachelor in multimedia / Asmaa Musa Musa, Asmaa Electronic Computers. Computer Science A large nimiber of techniques, such as Neurofuzzy algorithm methods are used to produce an efficient and effective system. A key stage in the system process is the selection of features. This paper discuss about a decision support system using Neurofuzzy algorithm methods in selecting lecturer's teaching work load for Bachelor in Multimedia. The prototype of this project is design based on Neurofuzzy algorithm method. Decision support system is a system for making decisions. A decision is a choice between alternatives based on estimates of the values of those alternatives. Supporting a decision means supporting this choice by supporting the estimation, the evaluation and the comparison and choice Neurofuzzy controller works similar to a conventional system; it accepts an input value, performs some calculations, and generates an output value. There are three steps in designing Neurofuzzy algorithm method. The first step is to understand the physical system, its control requirements and identifies the controller's inputs and outputs. Secondly, to define the ranges and labels for the membership functions and describe the controller's operation using fuzzy rules. Finally, to debug and tune the controller by modifying membership functions, or rules, whenever appropriate 2007 Thesis NonPeerReviewed text en https://ir.uitm.edu.my/id/eprint/1380/2/1380.pdf A decision support system using Neurofuzzy algorithm methods in selecting lecturer's teaching work load for bachelor in multimedia / Asmaa Musa. (2007) Degree thesis, thesis, Universiti Teknologi MARA.
institution Universiti Teknologi Mara
building Tun Abdul Razak Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Mara
content_source UiTM Institutional Repository
url_provider http://ir.uitm.edu.my/
language English
topic Electronic Computers. Computer Science
spellingShingle Electronic Computers. Computer Science
Musa, Asmaa
A decision support system using Neurofuzzy algorithm methods in selecting lecturer's teaching work load for bachelor in multimedia / Asmaa Musa
description A large nimiber of techniques, such as Neurofuzzy algorithm methods are used to produce an efficient and effective system. A key stage in the system process is the selection of features. This paper discuss about a decision support system using Neurofuzzy algorithm methods in selecting lecturer's teaching work load for Bachelor in Multimedia. The prototype of this project is design based on Neurofuzzy algorithm method. Decision support system is a system for making decisions. A decision is a choice between alternatives based on estimates of the values of those alternatives. Supporting a decision means supporting this choice by supporting the estimation, the evaluation and the comparison and choice Neurofuzzy controller works similar to a conventional system; it accepts an input value, performs some calculations, and generates an output value. There are three steps in designing Neurofuzzy algorithm method. The first step is to understand the physical system, its control requirements and identifies the controller's inputs and outputs. Secondly, to define the ranges and labels for the membership functions and describe the controller's operation using fuzzy rules. Finally, to debug and tune the controller by modifying membership functions, or rules, whenever appropriate
format Thesis
author Musa, Asmaa
author_facet Musa, Asmaa
author_sort Musa, Asmaa
title A decision support system using Neurofuzzy algorithm methods in selecting lecturer's teaching work load for bachelor in multimedia / Asmaa Musa
title_short A decision support system using Neurofuzzy algorithm methods in selecting lecturer's teaching work load for bachelor in multimedia / Asmaa Musa
title_full A decision support system using Neurofuzzy algorithm methods in selecting lecturer's teaching work load for bachelor in multimedia / Asmaa Musa
title_fullStr A decision support system using Neurofuzzy algorithm methods in selecting lecturer's teaching work load for bachelor in multimedia / Asmaa Musa
title_full_unstemmed A decision support system using Neurofuzzy algorithm methods in selecting lecturer's teaching work load for bachelor in multimedia / Asmaa Musa
title_sort decision support system using neurofuzzy algorithm methods in selecting lecturer's teaching work load for bachelor in multimedia / asmaa musa
publishDate 2007
url https://ir.uitm.edu.my/id/eprint/1380/2/1380.pdf
https://ir.uitm.edu.my/id/eprint/1380/
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score 13.211869