Fuzzy Rule Base for Analytical Demand Forecasting Enhancement

2010 ◽  
Author(s):  
Agus Pratondo
Keyword(s):  
Demand Forecasting ◽  
Fuzzy Rule ◽  
Rule Base ◽  
Fuzzy Rule Base

Fuzzy Rule Base Design With Probabilistic Weights

2016 ◽  
Author(s):  
Leonardo G. Melo ◽  
Luís A. Lucas ◽  
Myriam R. Delgado
Keyword(s):  
Fuzzy Rule ◽  
Rule Base ◽  
Fuzzy Rule Base ◽  
Base Design

Congestion Control Using Soft Computing

2010 ◽  
pp. 271-289
Author(s):  
T. Revathi ◽  
K. Muneeswaran
Keyword(s):  
Queue Length ◽  
Fuzzy Rule ◽  
Vital Role ◽  
Rate Of Change ◽  
Rule Base ◽  
Queue Management ◽  
Internet Routers ◽  
Fuzzy Rule Base ◽  
The Status

In the recent Internet era the queue management in the routers plays a vital role in the provision of Quality of Service (QoS). Virtual queue-based marking schemes have been recently proposed for Active Queue Management (AQM) in Internet routers. In this chapter, the authors propose Fuzzy enabled AQM (F-AQM) scheme where the linguistics variables are used to specify the behavior of the queues in the routers. The status of the queue is continuously monitored and decisions are made adaptively to drop or mark the packets as is done in Random Early Discard (RED) and Random Early Marking (REM) algorthms or schemes. The authors design a fuzzy rule base represented in the form of matrix indexed by queue length and rate of change of queue. The performance of the proposed F-AQM scheme is compared with several well-known AQM schemes such as RED, REM and Adaptive Virtual Queue (AVQ).

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