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Fuzzy logic - Computing membership function given term set


Fuzzy logic - Computing membership function given term set

By : Matti Jr
Date : November 17 2020, 11:55 AM
I wish this helpful for you I suspect the lecturer didn't really mean 'compute' but rather 'construct'. Provided you have no restrictions regarding the type of membership function, you can just use a simple triangular one. For 'short male' you would then have a maximum (1.0) at 156.8 and minima (0.0) at 143.1 and 179.4.
code :


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Fuzzy logic membership function in C

Fuzzy logic membership function in C


By : user1581191
Date : March 29 2020, 07:55 AM
hope this fix your issue Disclaimer: I've never implemented a fuzzy controller (I've only ever used PI or PID in real-life) and control class was 10 years ago.
Here's an presentation demonstrating moving towards a target using distance and angle for inputs and power as the output. FuzzyTech's Example positioning a crane
Question on Fuzzy Logic (Fuzzy Grouping & Fuzzy Fuzzy Lookup) transformation in SSIS

Question on Fuzzy Logic (Fuzzy Grouping & Fuzzy Fuzzy Lookup) transformation in SSIS


By : prasann thakkar
Date : March 29 2020, 07:55 AM
This might help you Here is a good start for you to actually understand what the fuzzy lookup component does (Similar to the fuzzy grouping) : SSIS fuzzy lookup
I actually used this at a client where I was receiving their client data that was fat fingered in by someone. I created a static lookup table based on company names:
Fuzzy Cyclic Triangular membership function

Fuzzy Cyclic Triangular membership function


By : AK Constantino
Date : March 29 2020, 07:55 AM
Any of those help I am very new to fuzzy toolkit in R. I have been trying to create fuzzy function as show in the image. , I guess a start would be
code :
FIS <- newFIS("daytest")
FIS <- addVar(FIS, "input", "daytime", 0:2400)
FIS <- addMF(FIS, "input", 1, triMF("Midnight", 0:2400, c(0,0,600,1)))
FIS <- addMF(FIS, "input", 1, triMF("Morning", 0:2400, c(0,600,1200,1)))
FIS <- addMF(FIS, "input", 1, triMF("Noon", 0:2400, c(600,1200,1800,1)))
FIS <- addMF(FIS, "input", 1, triMF("Evening", 0:2400, c(1200,1800,2400,1)))
FIS <- addMF(FIS, "input", 1, triMF("Mignight", 0:2400, c(1800,2400,2400,1)))


class(FIS)
plotMF(FIS, "input",1)
FIS$inputList[[1]]$membershipFunctionList[[1]]$mfVals <- 
    FIS$inputList[[1]]$membershipFunctionList[[1]]$mfVals+
    FIS$inputList[[1]]$membershipFunctionList[[5]]$mfVals
FIS$inputList[[1]]$membershipFunctionList[[1]]$mfType <- "wrapmf"
FIS$inputList[[1]]$membershipFunctionList[[5]]<-NULL
Is fuzzy query in elasticsearch related to fuzzy logic?

Is fuzzy query in elasticsearch related to fuzzy logic?


By : dean qj
Date : March 29 2020, 07:55 AM
Fuzzy Logic function in R as in Matlab

Fuzzy Logic function in R as in Matlab


By : nitro
Date : March 29 2020, 07:55 AM
With these it helps Have a look at the sets package It does all the things you expect from a fuzzy logic toolbox. It allows to specify your fuzzy membership functions, set up your fuzzy rules, do fuzzy inference and defuzzify. The example in ?fuzzy_inference shows the restaurant example of the standard fuzzy logic textbook. I highly recommend it.
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