Connection admission control in ATM networks using survey-based type-2 fuzzy logic systems

2000 ◽  
Vol 30 (3) ◽  
pp. 329-339 ◽  
Author(s):  
J.M. Mendel ◽  
N.N. Karnik ◽  
Q. Liang
Keyword(s):  
Fuzzy Logic ◽  
Admission Control ◽  
Connection Admission Control ◽  
Atm Networks ◽  
Fuzzy Logic Systems ◽  
Logic Systems ◽  
Connection Admission

scholarly journals Sustaining Negotiated QoS in Connection Admission Control for ATM Networks Using Fuzzy Logic Techniques

10.28945/3275 ◽  
2008 ◽  
Author(s):  
Olufade F. Williams Onifade ◽  
G. Adesola Aderounmu ◽  
Oluwasikemi Tayo
Keyword(s):  
Fuzzy Logic ◽  
Admission Control ◽  
Bandwidth Allocation ◽  
Connection Admission Control ◽  
Atm Networks ◽  
Output Stage ◽  
Centroid Method ◽  
Average Cell ◽  
Connection Admission ◽  
Fuzzy Logic Technique

The objective of connection admission control (CAC) is to keep the network load moderate to achieve a performance objective associated with Quality of Service (QoS). Cell Loss Ratio (CLR), a key QoS parameter in ATM networks, is essential for proper network resources dimensioning, congestion control, bandwidth allocation and routing. In this research, we employed fuzzy logic technique in Statistical Connection Admission Control (S-CAC) - a CAC employing multiplexing of the bandwidth between the peak cell rate and the sustained (average) cell rate. The fuzzy technique consists of an input stage, a processing stage, and an output stage. We defined the rules with “max-min” inference method in which the output membership function is given the truth value generated by the premise. The results was defuzzi-fied to a crisp value using the “centroid” method which favors the rule with the output of the greatest area, and the result thereafter charted to compare it operation.

Design of back propagation optimized Nagar-Bardini structure-based interval type-2 fuzzy logic systems for fuzzy identification

2021 ◽  
pp. 014233122110066
Author(s):  
Yang Chen ◽  
Jiaxiu Yang
Keyword(s):  
Fuzzy Logic ◽  
Back Propagation ◽  
Membership Functions ◽  
Identification Problems ◽  
Fuzzy Logic Systems ◽  
Fuzzy Identification ◽  
Logic Systems ◽  
Academic Topic ◽  
Interval Type

In recent years, fuzzy identification based on system identification theory has become a hot academic topic. Interval type-2 fuzzy logic systems (IT2 FLSs) have become a rising technology. This paper designs a type of Nagar-Bardini (NB) structure-based singleton IT2 FLSs for fuzzy identification problems. The antecedents of primary membership functions of IT2 FLSs are chosen as Gaussian type-2 primary membership functions with uncertain standard deviations. Then, the back propagation algorithms are used to tune the parameters of IT2 FLSs according to the chain rule of derivation. Compared with the type-1 fuzzy logic systems, simulation studies show that the proposed IT2 FLSs can obtain better abilities of generalization for fuzzy identification problems.

Modeling the permeability of carbonate reservoir using type-2 fuzzy logic systems

2011 ◽  
Vol 62 (2) ◽  
pp. 147-163 ◽  
Author(s):  
Sunday Olusanya Olatunji ◽  
Ali Selamat ◽  
Abdulazeez Abdulraheem
Keyword(s):  
Fuzzy Logic ◽  
Carbonate Reservoir ◽  
Fuzzy Logic Systems ◽  
Logic Systems
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