Implements defuzzification methods for fuzzy evaluation vectors, including weighted average and maximum membership methods.
Arguments
- mu
Numeric vector, membership degrees for evaluation levels, in
[0, 1].- scores
Numeric vector, scores corresponding to each evaluation level (e.g., c(100, 80, 60, 40) for "Excellent", "Good", "Fair", "Poor").
- method
Character, defuzzification method: "weighted_average", "max_membership", "centroid".
Examples
# Example: Defuzzify fuzzy evaluation vectors for three schemes
mu = c(0.318, 0.351, 0.203, 0.128)
scores = c(30, 60, 75, 90) # Scores for "Poor", "Fair", "Good", "Excellent"
defuzzify(mu, scores, method = "weighted_average")
#> [1] 57.345
defuzzify(mu, scores, method = "max_membership")
#> [1] 60
defuzzify(mu, scores, method = "centroid")
#> [1] 57.345