CODEWITHSUNDEEP
fuzzy-logic
Rafael Reis
Rafael Reis

Reputation: 610

Fuzzy Logic - Aggregating fuzzy rules

I am starting in fuzzy logic and I have a model with several rules. The way I am aggregating them so I can defuzzify is by taking the maximum of each rule (that is how I saw in an exemple of the library that I am using). The problem is that if one of my rule returns a value that is too high the other rules become irrelevant to the output. My output kinds of saturates. Is ther other ways to aggregate fuzzy rules so that dos not happen?

Upvotes: 2

Views: 828

Answers (1)

Fabian
Fabian

Reputation: 223

You should look into T-norms and T-conorms. After you find out what T-norms and T-Conorms you can use in your library, you can choose one which fits your needs best.

You use the Maximum T-Conorm. So if one rule result is 0.8, the end result will always be 0.8 as long as the other rule result is smaller as 0.8.

But if you use another T-Conorm for example the Probabilistic sum it is not that way anymore:

Probabilistic sum: Probabilistic sum

Example:

Rule1 = 0.5
Rule2 = 0.6
EndResult = 0.5 + 0.6 - 0.5 * 0.6 = 0.8

Now both results have an influence on the end result, not just the bigger one.

Upvotes: 1

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