Applied Computational Intelligence and Soft Computing

Research Article

Prediction of Surface Roughness in End Milling Process Using Intelligent Systems: A Comparative Study

Table 8

The optimal premise parameters of ANFIS FO Sugeno model trained with HL algorithm.
Input variableOptimal premise
parameters		Input variableOptimal premise
parameters		Input variableOptimal premise
parameters
𝑆 𝐶 𝑆 1 = 0 . 5 3 6 1 𝐹 𝐶 𝐹 1 = 0 . 2 1 8 5 𝐷 𝐶 𝐷 1 = 0 . 1 9 9 9
𝜎 𝑆 1 = 0 . 0 9 4 7 𝜎 𝐹 1 = 0 . 0 9 5 7 𝜎 𝐷 1 = 0 . 1 6 9 6
𝐶 𝑆 2 = 0 . 7 5 1 6 𝐶 𝐹 2 = 0 . 5 4 8 7 𝐶 𝐷 2 = 0 . 6 0 0 7
𝜎 𝑆 2 = 0 . 0 3 4 7 𝜎 𝐹 2 = 0 . 0 9 5 8 𝜎 𝐷 2 = 0 . 1 6 7 0
𝐶 𝑆 3 = 0 . 9 7 1 5 𝐶 𝐹 3 = 0 . 9 5 1 8 𝐶 𝐷 3 = 1 . 0 0 0 0
𝜎 𝑆 3 = 0 . 0 9 2 3 𝜎 𝐹 3 = 0 . 2 0 3 2 𝜎 𝐷 3 = 0 . 1 6 9 6