# A New Fuzzy Harmony Search Algorithm Using Fuzzy Logic for Dynamic Parameter Adaptation
## 4 Experiment Results Comparison of the Simple Harmony Search Algorithm with Fuzzy Harmony Search
\begin{table}
\begin{tabular}{l c c c c c c c} \hline \hline \multicolumn{6}{c}{**FHS2 Rules Increase in Range 0 to 1**} & \multicolumn{6}{c}{**FHS2 Rules Decrease in Range 0 to 1**} \\ \hline
**Function** & **Best** & **Worst** & **Average** & **Function** & **Best** & **Worst** & **Average** \\ \hline
**Spherical** & \(1.19\mathrm{E}-04\) & \(1.01\mathrm{E}-02\) & \(1.14\mathrm{E}-03\) & **Spherical** & \(3.02\mathrm{E}-05\) & \(1.54\mathrm{E}-02\) & \(9.06\mathrm{E}-04\) \\
**[PERSON]** & \(1.20\mathrm{E}-12\) & \(1.51\mathrm{E}-08\) & \(7.31\mathrm{E}-10\) & **[PERSON]** & \(7.01\mathrm{E}-13\) & \(1.58\mathrm{E}-09\) & \(1.34\mathrm{E}-10\) \\
**[PERSON]** & \(3.66\mathrm{E}-11\) & \(6.40\mathrm{E}-07\) & \(6.42\mathrm{E}-08\) & **[PERSON]** & \(1.62\mathrm{E}-10\) & \(2.76\mathrm{E}-06\) & \(2.86\mathrm{E}-07\) \\
**[PERSON]** & \(6.86\mathrm{E}-06\) & \(7.98\mathrm{E}-04\) & \(2.30\mathrm{E}-04\) & **[PERSON]** & \(1.49\mathrm{E}-05\) & \(9.57\mathrm{E}-04\) & \(2.36\mathrm{E}-04\) \\
**[PERSON]** & \(3.40\mathrm{E}-03\) & \(3.29\mathrm{E}+00\) & \(7.89\mathrm{E}-01\) & **[PERSON]** & \(2.40\mathrm{E}-03\) & \(3.86\mathrm{E}+00\) & \(7.74\mathrm{E}-01\) \\
**Sum Square** & \(2.20\mathrm{E}-03\) & \(1.26\mathrm{E}-01\) & \(2.00\mathrm{E}-02\) & **Sum Square** & \(7.08\mathrm{E}-04\) & \(1.26\mathrm{E}-01\) & \(1.33\mathrm{E}-02\) \\ \hline \hline \end{tabular}
\end{table} 
Table 6: Results obtained with FHS2 using fuzzy logic to increase and decrease _PArate_ with 0 to 1 range applied to six benchmark mathematical functions. \begin{table}
\begin{tabular}{l c c c c c c c} \hline \hline \multicolumn{6}{c}{**FHS2 Rules Increase in Range 0 to 1**} & \multicolumn{6}{c}{**FHS2 Rules Decrease in Range 0 to 1**} \\ \hline
**Function** & **Best** & **Worst** & **Average** & **Function** & **Best** & **Worst** & **Average** \\ \hline
**Spherical** & \(1.54\mathrm{E}-09\) & \(2.64\mathrm{E}-04\) & \(1.38\mathrm{E}-05\) & **Spherical** & \(5.15\mathrm{E}-14\) & \(7.60\mathrm{E}-03\) & \(9.08\mathrm{E}-04\) \\
**Rosenbrock** & \(5.44\mathrm{E}-14\) & \(2.80\mathrm{E}-10\) & \(1.76\mathrm{E}-11\) & **Rosenbrock** & \(4.14\mathrm{E}-14\) & \(8.64\mathrm{E}-10\) & \(7.31\mathrm{E}-11\) \\
**[PERSON]** & \(1.20\mathrm{E}-11\) & \(1.28\mathrm{E}-07\) & \(1.08\mathrm{E}-08\) & **[PERSON]** & \(c1.44\mathrm{E}-10\) & \(2.58\mathrm{E}-06\) & \(2.22\mathrm{E}-07\) \\
**[PERSON]** & \(1.07\mathrm{E}-08\) & \(4.28\mathrm{E}-04\) & \(9.55\mathrm{E}-06\) & **[PERSON]** & \(4.31\mathrm{E}-05\) & \(2.00\mathrm{E}-03\) & \(4.98\mathrm{E}-04\) \\
**[PERSON]** & \(1.10\mathrm{E}-10\) & \(7.55\mathrm{E}-04\) & \(4.72\mathrm{E}-05\) & **[PERSON]** & \(6.91\mathrm{E}-04\) & \(3.54\mathrm{E}+00\) & \(5.94\mathrm{E}-01\) \\
**Sum Square** & \(2.06\mathrm{E}-08\) & \(5.50\mathrm{E}-06\) & \(2.53\mathrm{E}-06\) & **Sum Square** & \(1.00\mathrm{E}-03\) & \(5.70\mathrm{E}-03\) & \(3.13\mathrm{E}-03\) \\ \hline \hline \end{tabular}
\end{table} 
Table 7: Results obtained with FHS2 using fuzzy logic to increase and decrease _PArate_ with a range from 0.7 to 1, applied to 6 benchmark mathematical functions.