A Hybrid Computational Method of Desirability, Fuzzy Logic, ANFIS, and LAPO Algorithm for Multiobjective Optimization Design of Scott Russell Compliant Mechanism

<table class="table-group" id="tab11"><tr><td><table class="table"><tr><td class="thead-hr" colspan="2"><hr/></td></tr><tr><td class="align_left">Number of nodes</td><td class="align_center">78</td></tr><tr><td class="align_left">Number of linear parameters</td><td class="align_center">108</td></tr><tr><td class="align_left">Number of nonlinear parameters</td><td class="align_center">27</td></tr><tr><td class="align_left">Total number of parameters</td><td class="align_center">135</td></tr><tr><td class="align_left">Number of training data pairs</td><td class="align_center">15</td></tr><tr><td class="align_left">Number of testing data pairs</td><td class="align_center">0</td></tr><tr><td class="align_left">Number of fuzzy rules</td><td class="align_center">27</td></tr><tr class="table-tr"><td colspan="2"><hr class="tbody-hr"/></td></tr></table></td></tr></table>

Mathematical Problems in Engineering

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Table 11

Table 11: A Hybrid Computational Method of Desirability, Fuzzy Logic, ANFIS, and LAPO Algorithm for Multiobjective Optimization Design of Scott Russell Compliant Mechanism 

Table 11 | A Hybrid Computational Method of Desirability, Fuzzy Logic, ANFIS, and LAPO Algorithm for Multiobjective Optimization Design of Scott Russell Compliant Mechanism 