Machine Intelligence - Lecture 17 (Fuzzy Logic, Fuzzy Inference)
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- čas přidán 14. 07. 2024
- SYDE 522 - Machine Intelligence (Winter 2019, University of Waterloo)
Target Audience: Senior Undergraduate Engineering Students
Instructor: Professor H.R.Tizhoosh (kimia.uwaterloo.ca/)
Course Outline - The objective of this course is to introduce the students to the main concepts of machine intelligence as parts of a broader framework of “artificial intelligence”. An overview of different learning, inference and optimization schemes will be provided, including Principal Component Analysis, Support Vector Machines, Self-Organizing Maps, Decision Trees, Backpropagation Networks, Autoencoders, Convolutional Networks, Fuzzy Inferencing, Bayesian Inferencing, Evolutionary algorithms, and Ant Colonies.
Lecture 17 - Fuzzy Logic/Inference/Control
Watched it without pausing the video. I wish I was your student. I like your energy.
Best lecture of fuzzy logic. Truly mind blowing.
Thank you very much Professor, now I like fuzzy logic because you was brilliant in explain this logic and
thank you very much to the one who shared this video
Such a good lecturer. Thank you sir.
Good ! Thanks for sharing !!! This is exactly what I was looking for .
Very helpful, this is what I need! Thanks.
I was losing all motivation to learn these modelling concepts, because I couldn't find clear explanations. This video filled all voids and drew me back into these interesting concepts again. Amazing teacher. Thank you very much :)
I must say sir best lec of fuzzy logic i found on youtube
What a great lecture!
Awesome, very good lecture! Thank you!
We would be so far in our capabilities as humans if everyone who took on the responsibility of teaching others had the same gift as you for it.
Thank you for the awesome lecture!
Thank you for sharing this lecture! The lecturer is very talented. He is making the material sound very easy to me. I am a data science master student in Australia! :)
he is iranian .... Thats Why
Congratulations, excellent explanation!!
This was very helpful, Thank you so much!
Awesome lecture, thank u very much, cheers from Chile!
This professor is awesome
Its a wonderful lecture thanks a lot it going to make my AGV automation easier.
awesome lecture. thank you so much Sir.
Fantastic lecturer! wow
fantastic lecture
This was great!
amazing lecture .. thank you from Libya
Very good lecture! thank you.
I love you Prof
Thank you so much!
Excelent!
it is very helpfull for computer science in this corona situation :) thank you for the prof that a very good explanation
Thank you for your lecture, it helps me a lot rather than Indian English that I can not understand what they said. One more thing, your example should be 0.6 (very cold), 0.4 (cold) to make sure membership function is normal.
I liked the lecture thank you for sharing.
thanks professor....lots of love from pakistan
Very good lecture, thank you.
Really great intro to fuzzy logic and control, thanks very much!
Perfect lecturer. Thank you!
This lecture is so educative. i really appreciate this. Please i need more video on fuzzy logic. I am currently working on a project and i require fuzzy logic to carry out the project.
Great lecturer, honestly l have learned alot from it. But I think you made unintentional mistake while explaining the rules of cart movement. Beacuse if the pendulum goes right, the cart should also go right to keep it upstanding.
Again thank you for your explanation. It is awesome.
Thank you, sir, for this valuable lecture...This concept helped me a lot in my project work.
Sir kindly make another video on fuzzy logic or recommend a book.
❤❤❤🇵🇰
A Very good Professor that explained FL and FS very well. I enjoyed a lot, does anybody knows his name?
Instructor: Professor H.R.Tizhoosh, according to the description.
Great lecture from Tom Hardy.
it is is very food
Ntaps Djiwa
25:58 just leave this here
Can someone explain to me what the advantage of using the membership function on the Angle and angular speed of the inverted pendulum is? Why not just use the actual values?
Because you do not have the real function(equations) to find out the relation ship between them
I think that some rules in the example are incorrect.
Either way, this lecture is very useful. Thanks!
They are not. Keep in mind it's INVERTED pendulum. So when the lever goes FORWARD, the vehicle should move BACKWARDS and vice versa. It confused me too for a while.
Yeah, you're absolutely right. It should be inverted.
czcams.com/video/XWhGjxdug0o/video.html
So many bots commenting. I guess it’s a nod to the lecture.
Fuzzy logic = computing with words?
How many liters of bleach have you consumed?
Thumbs down. I would like to see a real demo. I don't like lectures where the instructor is talking to the white board while copying notes.
Why is fuzzt logic better than any other method? How did the instructor come up with +/- 30 deg? The instructor is basically duplicating a Proportional-Derivative controller that has only two gains instead of all those rules, triangles and their shapes. What about the processing power requirements vs a PID? So why bother? Where in industry is fuzzy logic used? Most just use a PID.
If I were teaching, I would have all the text in a Mathematica or Jupyter Lab file or similar so I don't need to waste time writing. I could also change parameters and show the results. Today's students are getting charged today's prices but getting taught like it was 40 years ago.