Fuzzy Inference System Walkthrough | Fuzzy Logic, Part 2

This video walks step-by-step through a fuzzy inference system. Learn concepts like membership function shapes, fuzzy operators, multiple-input inference systems, and rule firing strength.

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[leventbilal]

Hey Brian, it is so wonderful to see that how you make literally anything look way simpler than they actually are! Looking forward to see the following sections!

[Haa_r]

This type of work is the one that deserves support. Just to show some appreciation.

[maxmusterman]

If Brian uploads video then I am happy.. ok thats hard logic

[chenmkk]

ur vd help a lot, now i no need watch lectures from uni. it covers all the concept. Thanks a lot!

[thekamakaji]

Really looking forwards to the rest of this series. Super useful

[GiovanniBR]

Awsome! Such an amazing and intuitive video about this topic.

[coxfire]

I love fuzzy logic, we use it for diagnoses purposes

[pandax]

Great Video!! I don't known the fuzzy analysis and the video it was very clear. I will try this kind of solution in some real life situation.

[amjadali]

Very good illustration level. My special thanks ❤

[uchungnguyen]

crazy! tks a lot Brian, u made it simple and understandable! hat off!

[neux]

This is great and all, but I for one already interacted with making an FIS by using it with the tip example. Would like to see real applications of FIS with AI somewhere, lol. Though I will say that so far this has been the greatest walkthrough for demonstrating the fuzzy system.

[TonioLaggante]

What a great explanation, once again!

[IP__]

Thank you a lot! Your videos are amazing!

[ryanfoss]

very very cool. You are an amazing teacher brian, thank you.

[DavidSchalk-vo]

Hi Brian, thank you for your informative video! I have a question related to the graph shown in 15:32. Accross the whole service range, we can see a small dip in tip amount around food quality '8'. Is it not weird that the tip amount is slightly higher for food quality 6 than for food quality 8? I tried myself making such FIS and I wonder if there's a way of avoiding this, or should I see this as a small downside of the FIS approach?

[Suprdud]

This is kind of like a multivalued likelihood. For example, each fuzzy membership function is a possible distribution of how the values are distributed and the crisp evaluations are those likelihoods.

So should we be able to do maximum likelihood estimation for our fuzzy membership functions?

[billfrug]

so you suggest empirical verification of membership functions via polling but what about the interpretation of fuzzy operators?

[ahmedy.m.daraghma]

Fuzzyfierr : V1 > degree of membership 1
rule based inference : Degree of membership v 1 > Degree of membership v2
Defuzzifier :Degree of membership 2 > v 2

[florankacaku]

How did the 4th rule get added to the 3rd rule to produce the new value of High? Did you connect them by OR?

[AliHosseiniLaqa]

Dear brian, can u provide us with the matlab codes and simulink you've shown us in the videos?