Table 4 Fuzzy metrics
Citation | Single fuzzy or combined with another SC technique | At what level of the localization process they are implemented | Type of inference used | Type of member ship functions | Number of rules, variable, and sets | Type defuzzification | Rule base construction and rule simplification |
|---|---|---|---|---|---|---|---|
Fuzzy LMS | Angle estimation | Mamdani | Triangle | 2 variables 9 rules | Centroid | LMS correlation product implication | |
[82] | Fuzzy Only | Position estimation and error measurement | Mamdani | Triangle | 6 variables | Centroid | Not reported |
[100] | Fuzzy only | Error measurement propose solution | Not used | Not reported | Not reported | Not reported | Not reported |
[89] | Fuzzy | Uncertainty and confidence interval | Not used | Trapezoidal | 3 variables | NaN | Not used |
[103] | Fuzzy | Enhance positioning accuracy | Mamdaniapproximate reasoning | Singleton | 3 to 4 variables with 12 rules | Center or area | Not reported |
[90] | Fuzzy | Location estimation | Mamdani | Triangle | 3 | Maximum | Min aggregation |
[107] | Fuzzy BLE and GA and Kalman | Location estimation | Mamdani | Triangle | 3 var with 30 rules | Mean of max | GA for membership function optimization |
[59] | Fuzzy and Kalman | Fine tuning the Kalman filter parameters | Mixed Mamdani-Sugeno | Triangle | Not reported | Center of gravity | Not reported |
[84] | Fuzzy | Location estimation (IFS) | Mamdani | Triangle | 9 variables | Not reported | Not reported |
[26] | Fuzzy | Pre-AFS Uncertainty with input data | Mamdani | Triangle | 2 variables | Maximum | No |
[104] | Fuzzy | Obtain confidence interval | Mamdani | Gaussian | 3 variables, 9 rules | Centroid | Not reported |
[88] | Fuzzy + EIF | Improve localization accuracy | Mamdani | Triangle | 3 inputs 45 rules | Max-min | GA |
[105] | Fuzzy | Map building | Mamdani | Gaussian | 16 input | Not reported | Not reported |
[79] | Fuzzy | Map building and position estimation | Mamdani | Trapezoidal | 6 inputs | Center of gravity | Product norm |
[91] | Fuzzy | Position estimation | Mamdani | Triangle | 5 inputs-3 variable 15 rules | Centroid | NAN |
[37] | Fuzzy + GA + NN | Weighting anchors | Mamdani | Trapezoidal | 5 variable 15 rules | Centroid | Not reported |
[87] | Fuzzy | Weighting near neighbors | Mamdani | Trapezoidal | 4 var 15 rules | Centroid | Not reported |
[93] | Fuzzy | Position classification | Mamdani | Trapezoidal | 4 var 28 rules | Centroid | Yes/tree reduction |
[94] | Fuzzy + Neural Net | Position estimation and movement tracking | TKS | Triangle | 4 var 19 rules | Not reported | ANFIS |
[135] | Fuzzy + Machine learning | Location estimation and Enhance estimation by compensating the small scale variations | Max-MinWinner rule | Triangle | 6 and 12 inputs with 3–9 linguistic terms and 2 var 266 rules | Max | Similarity analysis |
[95] | Fuzzy | Distance estimation | TKS | Triangle | 2 variables | Not reported | Not reported |
[86] | Fuzzy | Degree of satisfaction estimation | Mamdani | Trapezoidal | 4 variables | Max | Not reported |
[101] | Fuzzy | Enhance the positioning accuracy | Mamdani | Trapezoidal | 1 variable | Max | No |
[96] | Fuzzy | Position estimation | Mamdani | Triangle | 3 variables | Not reported | Not reported |
[39] | Fuzzy | Coordinate estimation | Mamdani | Triangle | 1 variable | Height | Not reported |
[62] | Fuzzy | Weighting Anchor | Mamdani | trapezoidal | 4 variables | Centroid | Not reported |
[51] | Fuzzy + Kalman | Estimate the state prediction of the filter | TKS | Gaussian | 6 variables | Not reported | Not reported |
[98] | Fuzzy C-Mean | Determine the position at multi-stage clustering system | Not reported | Not reported | k-inputs | Centroid | Not reported |
[136] | Fuzzy sets | Represent uncertainty in sensor measurements | Not reported | Trapezoidal | 2 inputs | Max | Not reported |
[51] | Fuzzy – Kalman | Tune the covariance matrix of KF | Mamdani | Trapezoidal-triangle | 1 input 9 rules | Weighted average | Not reported |
[53] | Fuzzy | Score weight for neighbor hop | Mamdani | Trapezoidal | 5 inputs 15 rules | Max | Not reported |
[47] | Fuzzy | More than one level including the position estimation | Mamdani | Triangle | 2 inputs 18 rules | Weighted average | Not reported |
[137] | Fuzzy + Neural Net | Symbolic estimation after training phase | TKS | Gaussian | 3 inputs 3 rules | Not reported | FCM |
[99] | Fuzzy | Location estimation | Mamdani + TKS | Trapezoidal | 5 rules | Weighted average | Not reported |
[106] | Fuzzy | Radio propagation model noise compensation | Mamdani | Trapezoidal | 3 inputs 24 rules | Weighted average | Not reported |
[138] | Fuzzy | Weighting nearest neighbor edges | Not reported | Not reported | 5 inputs | Not reported | Not reported |
[36] | Fuzzy C-Mean | Carry out fuzzy partition | Not reported | Not reported | 5 inputs | Not reported | Not reported |
[34] | Fuzzy | Position estimation and weighting kNN | TKS | Trapezoidal | 2 inputs 32 rules | Not reported | Not reported |