Fuzzy logic in R

fuzzyLogic.R

#
# author Huber Flores
#

# Example of fuzzy logic in R

# The main idea is to have fuzzy sets for each of the dimensions
# each attribute in the dimension can be defined as a fuzzy set with their respective linguistic variables, terms and membership functions

library(sets)

U1 <- seq(from = 0, to = 1, by = 0.0001)

#DIMENSIONS

variables <-

set(

code =
fuzzy_partition(varnames= 
c(ELow = 0.2 , ENormal = 0.5, EHigh = 0.8),
FUN= fuzzy_cone, radius = 0.2, universe=U1),


bandwidth =
fuzzy_partition(varnames=
c(SLow = 0.2, SNormal=0.5, SHigh=0.8),
FUN = fuzzy_cone, radius = 0.2, universe=U1),


acceleration =
fuzzy_partition(varnames=
c(ALow = 0.2, ANormal=0.5, AHigh=0.8),
FUN = fuzzy_cone, radius = 0.2, universe=U1),


processing =
fuzzy_partition(varnames=
c(Local = 0.3, Remote = 0.7),
FUN = fuzzy_cone, radius = 0.3, universe=U1) 


)


rules <-
set(

fuzzy_rule(code %is% EHigh && bandwidth %is% SHigh && acceleration %is% AHigh, processing %is% Remote),

fuzzy_rule(code %is% EHigh && bandwidth %is% SHigh && acceleration %is% ANormal, processing %is% Remote),

fuzzy_rule(code %is% EHigh && bandwidth %is% SHigh && acceleration %is% ALow, processing %is% Local),

fuzzy_rule(code %is% EHigh && bandwidth %is% SNormal && acceleration %is% AHigh, processing %is% Remote),

fuzzy_rule(code %is% EHigh && bandwidth %is% SNormal && acceleration %is% ANormal, processing %is% Remote),

fuzzy_rule(code %is% EHigh && bandwidth %is% SNormal && acceleration %is% ALow, processing %is% Local),

fuzzy_rule(code %is% EHigh && bandwidth %is% SLow && acceleration %is% AHigh, processing %is% Remote),

fuzzy_rule(code %is% EHigh && bandwidth %is% SLow && acceleration %is% ANormal, processing %is% Local),

fuzzy_rule(code %is% EHigh && bandwidth %is% SLow && acceleration %is% ALow, processing %is% Local),

fuzzy_rule(code %is% EHigh && bandwidth %is% SHigh, processing %is% Remote),

fuzzy_rule(code %is% EHigh && bandwidth %is% SLow, processing %is% Local),

fuzzy_rule(code %is% EHigh && bandwidth %is% SNormal, processing %is% Local),

fuzzy_rule(code %is% ENormal && bandwidth %is% SLow, processing %is% Local),

fuzzy_rule(code %is% ENormal && bandwidth %is% SHigh, processing %is% Remote),

fuzzy_rule(code %is% ENormal && bandwidth %is% SNormal, processing %is% Local),

fuzzy_rule(code %is% ELow && bandwidth %is% SLow, processing %is% Local),

fuzzy_rule(code %is% ELow && bandwidth %is% SNormal, processing %is% Local),

fuzzy_rule(code %is% ELow && bandwidth %is% SHigh, processing %is% Local)

)


context <- fuzzy_system(variables, rules)

print(context)
#plot(context)

#fi <- fuzzy_inference(context, list(code=0.8123, bandwidth=0.912))
#0.7

#fi <- fuzzy_inference(context, list(code=0.5212, bandwidth=0.2121))
#0.3

#fi <- fuzzy_inference(context, list(code=0.1532, bandwidth=0.9321))
#0.3

#fi <- fuzzy_inference(context, list(code=0.2432, bandwidth=0.9323))
#0.3

#fi <- fuzzy_inference(context, list(code=0.4723, bandwidth=0.9542))
#0.7

#fi <- fuzzy_inference(context, list(code=0.2932, bandwidth=0.9484))
#0.3

#fi <- fuzzy_inference(context, list(code=0.2912, bandwidth=0.4324))
#0.3

#fi <- fuzzy_inference(context, list(code=0.2134, bandwidth=0.2194))
#0.3

#fi <- fuzzy_inference(context, list(code=0.4323, bandwidth=0.5345))
#0.3

#fi <- fuzzy_inference(context, list(code=0.8123, bandwidth=0.912, acceleration = NA))
#There is a rule code is High AND bandwidth is High -> Remote. 
#as well as a rule, code is High AND bandwidth is High and acceleration is High -> Remote.
#0.7

#fi <- fuzzy_inference(context, list(code=0.8123, bandwidth=0.912, acceleration = 0.93))
#0.7

#fi <- fuzzy_inference(context, list(code=0.8123, bandwidth=0.912, acceleration = 0.13))
#0.5

#fi <- fuzzy_inference(context, list(code=0.8123, bandwidth=0.2354, acceleration = 0.9243))
#0.4517523

#fi <- fuzzy_inference(context, list(code=0.4723, bandwidth=0.9542, acceleration=NA))
#This rule exists for the two variables provided
#0.7

#fi <- fuzzy_inference(context, list(code=0.8857, bandwidth=0.1194, acceleration=0.8921))
#0.4961897

fi <- fuzzy_inference(context, list(code=0.8857, bandwidth=0.1194, acceleration=0.1184))
#0.3


#dev.new()
#plot(fi)

gset_defuzzify(fi, "centroid")


U1 <- NULL