Abstract
This paper presents a comparative study between the Mamdani and Sugeno fuzzy inference systems (FIS) for intelligent traffic transmission over optical code-division multiple-access (OCDMA) network architectures. This FIS is capable of mitigating environmental temperature variation effects in the transmission link which are known to play an important role in the overall performance of the network. The paper outlines the basic difference between both Mamdani and Sugeno type FIS for this approach. The results highlight the performance of the two systems and the computational advantages of using Sugeno- type over Mamdani-type.
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