Question 111
Consider the following models:
M1: Mamdani model
M2: Takagi - Sugeno-Kang model
M3: Kosko's additive model (SAM)
Which of the following option contains examples of additive rule model?
Answer : M1: Mamdani model
M2: Takagi - Sugeno-Kang model
M3: Kosko's additive model (SAM)
Which of the following option contains examples of additive rule model?
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UGC NET CS December 2019 - Question 110 | UGC NET CS December 2019 - Question 112 |
Mamdani Fuzzy Inference Systems
Mamdani fuzzy inference was first introduced as a method to create a control system by synthesizing a set of linguistic control rules obtained from experienced human operators. In a Mamdani system, the output of each rule is a fuzzy set.Since Mamdani systems have more intuitive and easier to understand rule bases, they are well-suited to expert system applications where the rules are created from human expert knowledge, such as medical diagnostics.
Sugeno Fuzzy Inference Systems
Sugeno fuzzy inference, also referred to as Takagi-Sugeno-Kang fuzzy inference, uses singleton output membership functions that are either constant or a linear function of the input values. The defuzzification process for a Sugeno system is more computationally efficient compared to that of a Mamdani system, since it uses a weighted average or weighted sum of a few data points rather than compute a centroid of a two-dimensional area.
You can convert a Mamdani system into a Sugeno system using the convert To Sugeno function. The resulting Sugeno system has constant output membership functions that correspond to the centroids of the Mamdani output membership functions.
Reference 1 : Methods of Fuzzy Inference System (1) Mamdani Fuzzy Inference System (2) Takagi-Sugeno Fuzzy Model (TS Method)
Reference 2 : Mamdani and Sugeno Fuzzy Inference Systems
So, option 2 is correct answer