For the construction and training of
the model, 50 sets of trial samples are designated as training
data. According to the ANFIS system, the numbers of input
subjection functions for the shear force model and SBD model
are set to [3 2 3 2 2 2] and [2 2 2 2 2 2], respectively. The input
subjection functions are all set to be a Gauss function and the
output subjection functions are set to be a constant value. Based
on the basic settings, the ANFIS-based prediction model is
implemented through the ANFIS Editor GUI module of the
Matlab software. In the software, the hybrid-study algorithm is
selected as the training method of the ANFIS. As a result, the
shear force model is created and has an error of 2.5028 N after
25 iterative epochs, and the SBD model is also created and
reaches an error of 0.35μm after 100 iterative epochs. Fig. 2
shows the training error curve of the two models. The shear
force model produces 144 (= 3×2×3×2×2×2) rules, the SBD
model produces 64 (= 2×2×2×2×2×2) rules. These rules cover
the whole range of the parameters selected in Table 4.
For the construction and training ofthe model, 50 sets of trial samples are designated as trainingdata. According to the ANFIS system, the numbers of inputsubjection functions for the shear force model and SBD modelare set to [3 2 3 2 2 2] and [2 2 2 2 2 2], respectively. The inputsubjection functions are all set to be a Gauss function and theoutput subjection functions are set to be a constant value. Basedon the basic settings, the ANFIS-based prediction model isimplemented through the ANFIS Editor GUI module of theMatlab software. In the software, the hybrid-study algorithm isselected as the training method of the ANFIS. As a result, theshear force model is created and has an error of 2.5028 N after25 iterative epochs, and the SBD model is also created andreaches an error of 0.35μm after 100 iterative epochs. Fig. 2shows the training error curve of the two models. The shearforce model produces 144 (= 3×2×3×2×2×2) rules, the SBDmodel produces 64 (= 2×2×2×2×2×2) rules. These rules coverthe whole range of the parameters selected in Table 4.
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