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A HYBRID RULE BASED FUZZY-NEURAL EXPERT SYSTEM FOR PASSIVE NETWORK MONITORING

Publication from NRGDL / 2003-05-13 16:32:35
Oleh : AZRUDDIN AHMAD, GOBITHASAN RUDRUSAMY,, Network Research Group (azru@nrg.cs.usm.my, gobithasan@nrg.cs.usm.my, {rahmat,azman,sures}@cs.usm.my)
Dibuat : 2003-05-08, dengan 0 file

Keyword : rule-base, Neuro-Fuzzy, Learning, Artificial Intelligence, Network Monitoring.
Url : http://

An enhanced approach for network monitoring is to
create a network monitoring tool that has artificial intelligence characteristics. This will crete a totally independent monitoring system with a minimal amount of reliance on human network admins.

There are a number of approaches available. One
such approach is by the use of a combination of rule based, fuzzy logic and neural networks to create a hybrid system. Such system will have a dual knowledge database approach. One containing
membership function values to compare to and do
deductive reasoning and another database with rules deductively formulated by an expert (a network administrator). The knowledge database will be updated continuously with newly acquired patterns.

In short, the system will be composed of 2 parts,
learning from data sets and fine-tuning the
knowledge-base using neural net techniques and the use of fuzzy logic in making decision based on the rules and membership functions inside the
knowledge base. This paper will discuss the idea,
steps and issues involved in creating such a system.

Deskripsi Alternatif :

An enhanced approach for network monitoring is to
create a network monitoring tool that has artificial intelligence characteristics. This will crete a totally independent monitoring system with a minimal amount of reliance on human network admins.

There are a number of approaches available. One
such approach is by the use of a combination of rule based, fuzzy logic and neural networks to create a hybrid system. Such system will have a dual knowledge database approach. One containing
membership function values to compare to and do
deductive reasoning and another database with rules deductively formulated by an expert (a network administrator). The knowledge database will be updated continuously with newly acquired patterns.

In short, the system will be composed of 2 parts,
learning from data sets and fine-tuning the
knowledge-base using neural net techniques and the use of fuzzy logic in making decision based on the rules and membership functions inside the
knowledge base. This paper will discuss the idea,
steps and issues involved in creating such a system.

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PropertiNilai Properti
ID PublisherNRGDL
OrganisasiNetwork Research Group
Nama KontakNRG DIGITAL LIBRARY
AlamatSchool of Computer Science
KotaUSM
DaerahPenang
NegaraMalaysia
Telepon
Fax
E-mail Administratorpln@nrg.cs.usm.my
E-mail CKOpln@nrg.cs.usm.my

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