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ACIT4620 - Computational Intelligence > Module 3 - Lecture 08 - Fuzzy Systems > Flashcards

Module 3 - Lecture 08 - Fuzzy Systems Flashcards

1
Q

Fuzzy systems

What are some advantages of fuzzy modelling?

A

HFPLIS

  • Models based on human approximate reasoning
    Models are:
  • faster
  • good in practice (Good performance)
  • linguistic
  • interpretable (no black boxes)
  • simpler
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2
Q

Fuzzy systems

What is a rule base?

A

A collection of fuzzy rules

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3
Q

Fuzzy systems

What do you call the collection of fuzzy rules in a fuzzy inference system?

A

A rule base

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4
Q

Fuzzy systems

What is the basic structure of a fuzzy inference system? (RDI)

A
  • Rule base
  • Database of linguistic values for the fuzzy rules
  • Fuzzy reasoning engine (inference engine)
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5
Q

Fuzzy systems

What are the 3 steps in a FIS (Fuzzy inference system)? (FID)

A
  • Fuzzification
  • Fuzzy Inference
  • Defuzzification
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6
Q

Fuzzy systems

What input format does a FIS take?

A

Either crisp values or fuzzy values.

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7
Q

Fuzzy systems

What is a crisp value?

A

Traditional values, data without MFs.

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8
Q

Fuzzy systems

What do you call an input/output value that’s not fuzzy?

A

Crisp

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9
Q

Fuzzy systems

What is FIS short for?

A

Fuzzy inference system

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10
Q

Fuzzy systems

What input types can the Mamdani system take?

A

Either fuzzy or crisp.

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11
Q

Fuzzy systems

What do you need to do if the input is crisp?

A

Fuzzification of the input.

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12
Q

Fuzzy systems

What is the basic FIS?

A

Mamdani type.

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13
Q

Fuzzy systems

What’s a synonym for the Mamdani FIS type?

A

Basic FIS.

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14
Q

Fuzzy systems

What does defuzzification do?

A

It transforms fuzzy outputs to crisp values.

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15
Q

Fuzzy systems

In a Mamdani FIS, what T-norm is used?

A

T-norm operator: min / algebra product

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16
Q

Fuzzy systems

In a Mamdani FIS, what S-norm is used?

A

S-norm operator: max / sum

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17
Q

Fuzzy systems

In a Mamdani FIS, what is the Fuzzy implication? (What functions)

A

Fuzzy implication: Sum-product / max-min composition

18
Q

Fuzzy systems

How do you fuzzify the input value of 70 (x) in the image?

A

Read the values y = f(x) fro the graph and put them into a vector.

19
Q

Fuzzy systems

In the attached image, where are the T-norm and S-norm, respectively?

A

See image

20
Q

Fuzzy systems

What is the “centre of gravity” method an example of?

A

A defuzzification method.

21
Q

Fuzzy systems

What is the formula for the “centre of gravity” method?

A

See image.

22
Q

Fuzzy systems

What is the formula for the “bisector of area” method?

A

See image

23
Q

Fuzzy systems

What is the formula for the “mean of maximum” method?

A

See image

24
Q

Fuzzy systems

What is the formula for calculating z in Sugeno type?

A

If x is A and y is B, then z = f (x, y)

25
Q

Fuzzy systems

In a Sugeno type FIS, we have If x is A and y is B, then z = f (x, y).
What are A and B called?

A

The antecedents

26
Q

Fuzzy systems

In a Sugeno type FIS, we have If x is A and y is B, then z = f (x, y).
Where is the antecedent(s)?

A

A and B are antecedents.

27
Q

Fuzzy systems

In a Sugeno type FIS, we have If x is A and y is B, then z = f (x, y).
What is z = f (x, y) called?

A

The consequent.

28
Q

Fuzzy systems

In a Sugeno type FIS, we have If x is A and y is B, then z = f (x, y).
Where is the consequent(s)?

A

z = f (x, y) is the consequent.

29
Q

Fuzzy systems

In a Sugeno-type model with z = f(x, y), what is the function f(x, y)?

A

Usually, a polynomial of x and y.
E.g:
- Zero-order: z = f(x, y) = 3
- First-order: z = f(x, y) = 3x + 2y +3

30
Q

Fuzzy systems

In this rule example, what is the consequent and what is the antecedent?
If height is tall, then weight is fairly heavy.

A

Antecedent: If height is tall
Consequent: then weight is fairly heavy.

31
Q

Fuzzy systems

What do you use to build a FIS?

A

Data or knowledge/experience.

32
Q

Fuzzy systems

Can fuzzy systems be used for regression?

A

Yes.

33
Q

Fuzzy systems

Can fuzzy systems be used for clustering?

A

Yes.

34
Q

Fuzzy systems

How do you check how good a fuzzy system is?

A

Use error metrics like RMSE.

35
Q

Fuzzy systems

What is a neuro-fuzzy model?

A

A fuzzy model tuned using algorithms of NNs.

36
Q

Fuzzy systems

In a neuro-fuzzy system, what is tuned by the NN methods?

A

Locations and/or shapes of the membership functions.

37
Q

Fuzzy systems

What is ANFIS short for?

A

Adaptive Network-based Fuzzy Inference System

38
Q

Fuzzy systems

What is FCM short for?

A

Fuzzy Cognitive Maps

39
Q

Fuzzy systems

Who is behind FCM (Fuzzy Cognitive Maps)?

A

Kosko

40
Q

Fuzzy systems

What is Kosko known for?

A

FCM (Fuzzy Cognitive Maps)

41
Q

Fuzzy systems

What are FCMs?

A

FCMs are fuzzy graphs with possible feedback

42
Q

What’s the difference between Mamdani-type and Sugeno-type FIS?

A

Mamdani has fuzzy outputs, and Sugeno uses a polynomial evaluation for outputs.

Mamdani: If pressure is high, then volume is small
Sugeno: If speed is medium, then resistance = 5*speed

ACIT4620 - Computational Intelligence (7 decks)

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