## 7 Conclusions and Future Works
\begin{table}
\begin{tabular}{l l l l l l l l l l l} \hline \hline
**ID** & & \multicolumn{2}{l}{**bWSO-log**} & **bAAA** & **bBAT** & **bFA** & **bGWO** & **bMFO** & **bMVO** & **bPSO** & **bWOA** \\ \hline \multirow{4}{*}{N11} & \(\uparrow\)mean & 0.930 & 0.927 & 0.911 & 0.928 & **0.931** & 0.924 & 0.928 & 0.918 & 0.913 \\  & \(\pm\)std & 0.026 & 0.021 & 0.026 & 0.025 & 0.022 & **0.021** & 0.023 & 0.023 & 0.028 \\  & \(\uparrow\)best & **0.990** & 0.971 & 0.955 & 0.981 & 0.981 & 0.969 & 0.969 & 0.960 & 0.959 \\  & \(\uparrow\)worst & 0.853 & 0.876 & 0.854 & **0.889** & 0.872 & 0.881 & 0.882 & 0.874 & 0.859 \\ \hline \multirow{4}{*}{N12} & \(\uparrow\)mean & 0.820 & 0.804 & 0.805 & 0.797 & 0.818 & 0.809 & 0.826 & 0.801 & **0.828** \\  & \(\pm\)std & **0.041** & 0.051 & 0.059 & 0.060 & 0.048 & 0.059 & 0.052 & 0.054 & 0.059 \\  & \(\uparrow\)best & 0.917 & 0.930 & 0.891 & 0.915 & 0.904 & 0.889 & 0.917 & 0.949 & **0.965** \\  & \(\uparrow\)worst & **0.743** & 0.716 & 0.689 & 0.640 & 0.722 & 0.634 & 0.696 & 0.718 & 0.674 \\ \hline \multirow{4}{*}{N13} & \(\uparrow\)mean & 0.917 & 0.939 & 0.682 & 0.933 & **0.948** & 0.947 & 0.933 & 0.875 & 0.928 \\  & \(\pm\)std & 0.068 & 0.036 & 0.064 & 0.042 & **0.030** & 0.031 & 0.034 & 0.096 & 0.045 \\  & \(\uparrow\)best & 0.986 & **1.000** & 0.791 & 0.985 & **1.000** & **1.000** & **1.000** & 0.984 & **1.000** \\  & \(\uparrow\)worst & 0.730 & 0.843 & 0.576 & 0.803 & **0.876** & 0.838 & 0.862 & 0.688 & 0.776 \\ \hline \multirow{4}{*}{N14} & \(\uparrow\)mean & 0.903 & 0.902 & 0.895 & 0.895 & 0.932 & 0.915 & 0.930 & 0.920 & **0.941** \\  & \(\pm\)std & 0.139 & 0.125 & 0.132 & 0.148 & **0.101** & 0.109 & 0.122 & 0.127 & 0.112 \\  & \(\uparrow\)best & **1.000** & **1.000** & **1.000** & **1.000** & **1.000** & **1.000** & **1.000** & **1.000** \\  & \(\uparrow\)worst & 0.546 & 0.533 & 0.602 & 0.389 & 0.636 & **0.652** & 0.544 & 0.467 & 0.625 \\ \hline \multirow{4}{*}{N15} & \(\uparrow\)mean & 0.813 & **0.826** & 0.776 & 0.821 & 0.817 & 0.824 & 0.816 & 0.800 & 0.816 \\  & \(\pm\)std & 0.024 & 0.025 & 0.046 & **0.022** & 0.036 & 0.029 & 0.031 & 0.030 & 0.032 \\  & \(\uparrow\)best & 0.844 & 0.863 & 0.861 & 0.859 & **0.879** & 0.876 & 0.864 & 0.846 & 0.875 \\  & \(\uparrow\)worst & 0.751 & **0.777** & 0.651 & 0.771 & 0.744 & 0.746 & 0.742 & 0.727 & 0.742 \\ \hline \multirow{4}{*}{N16} & \(\uparrow\)mean & **0.536** & 0.404 & 0.380 & 0.422 & 0.374 & 0.415 & 0.395 & 0.433 & 0.377 \\  & \(\pm\)std & 0.195 & 0.188 & **0.139** & 0.187 & 0.198 & 0.209 & 0.211 & 0.228 & 0.217 \\  & \(\uparrow\)best & 0.867 & 0.841 & 0.657 & 0.886 & 0.778 & 0.778 & **1.000** & **1.000** & **1.000** \\  & \(\uparrow\)worst & 0.111 & 0.111 & 0.083 & **0.167** & 0.000 & 0.095 & 0.000 & 0.083 & 0.000 \\ \hline \multirow{4}{*}{N17} & \(\uparrow\)mean & **0.914** & 0.914 & 0.766 & 0.904 & 0.893 & 0.907 & 0.908 & 0.849 & 0.911 \\  & \(\pm\)std & **0.008** & 0.008 & 0.017 & 0.012 & 0.013 & 0.010 & 0.013 & 0.055 & 0.010 \\  & \(\uparrow\)best & 0.928 & 0.933 & 0.807 & 0.930 & 0.927 & **0.942** & 0.928 & 0.921 & 0.932 \\  & \(\uparrow\)worst & **0.902** & 0.889 & 0.736 & 0.871 & 0.874 & 0.892 & 0.881 & 0.764 & 0.889 \\ \hline \multirow{4}{*}{N18} & \(\uparrow\)mean & **0.790** & 0.789 & 0.783 & 0.759 & 0.782 & 0.782 & 0.766 & 0.784 & 0.762 \\  & \(\pm\)std & 0.067 & 0.051 & 0.075 & 0.062 & 0.051 & **0.048** & 0.070 & 0.066 & 0.072 \\  & \(\uparrow\)best & 0.904 & 0.879 & 0.905 & 0.857 & 0.893 & 0.857 & 0.927 & **0.929** & 0.879 \\  & \(\uparrow\)worst & 0.658 & **0.708** & 0.637 & 0.647 & 0.697 & 0.660 & 0.619 & 0.676 & 0.595 \\ \hline \multirow{4}{*}{N19} & \(\uparrow\)mean & **0.888** & 0.863 & 0.565 & 0.816 & 0.764 & 0.861 & 0.848 & 0.814 & 0.866 \\  & \(\pm\)std & **0.020** & 0.020 & 0.085 & 0.028 & 0.042 & 0.029 & 0.035 & 0.048 & 0.025 \\ \cline{1-1}  & \(\uparrow\)best & 0.929 & 0.907 & 0.738 & 0.878 & 0.826 & 0.904 & 0.907 & 0.901 & **0.931** \\ \cline{1-1}  & \(\uparrow\)worst & **0.832** & 0.814 & 0.395 & 0.759 & 0.644 & 0.770 & 0.788 & 0.718 & 0.832 \\ \hline \multirow{4}{*}{N13}  
To more clearly assess the contribution of the proposed logarithmic transfer function, a version of the algorithm without any transfer function, referred to as bWSO-0, was also included in the experiments.