This research paper introduces a novel
statement for optimizing Tsukamoto fuzzy inference system.
Suppose we are given some mathematical programming
problem that will solve using Tsukamoto Fuzzy Inference
System. We will using the linkable label of the variable that
construct from the Fuzzy Grid Partition in correcting the
limitation of Tsukamoto Fuzzy Inference System. Our
research will show the crisp value from the Tsukamoto
Fuzzy Inference System and the crisp value from the process
of optimization using Fuzzy Grid Partition. Our research
will find a fair optimal solution to the original fuzzy problem.
Published In:IJCSN Journal Volume 5, Issue 5
Date of Publication : October 2016
Pages : 786-791
Figures :09
Tables :--
Hartono : Hartono received the Master degree in 2010 from the University of
Putra Indonesia “YPTK” Padang, Indonesia in Computer Science and
Bachelor Degree in 2008 from STMIK IBBI Medan, Indonesia in
Computer Science. He is a lecturer at STMIK IBBI Medan. His
current interests are in data mining and artificial intelligence.
Nowadays, He Is a Student in a Doctoral Program in Computer
Science at University of Sumatera Utara.
The conclusion that can be drawn from this study are as
follows.
1. There is a limitation about Tsukamoto Fuzzy
Inference System.
2. We can make a linkable label in the membership
function of every label with the concept of Fuzzy Grid
Partition.
3. The new membership function as the result of Fuzzy
Grid Partition can correct the limitation of Tsukamoto
Fuzzy Inference System.
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