Algorithm 1 Fuzzy Simulation for Entropy, FSE, Huang [33]
Step 1.	Initialize the numbers of sample points K and integration points N, and a sufficiently small positive number $ϵ$. Set $H=0$ and $g=0$.
Step 2.	Randomly generate real numbers $u_{is}$ such that ${\mu }_i(u_{is})\ge ϵ$, $i=1,2,\cdots ,n,s=1,2,\cdots ,K,$ respectively.
Step 3.	Set $p=\underset{1\le s\le K}{min}f({\mathbf{u}}_s)$, and $q=\underset{1\le s\le K}{max}f({\mathbf{u}}_s)$.
Step 4.	Randomly generate r from $[p,q]$.
Step 5.	Calculate $H_g=-tlnt-(1-t)ln(1-t)$, where $t=\mathrm{Cr}\{f({\xi }_1,{\xi }_2,\cdots ,{\xi }_n)=r\}$ is estimated via Equation (42).
Step 6.	Set $H\leftarrow H+H_g$. If $g<N$, let $g=g+1$ and go to Step 4.
Step 7.	Return $H·(q-p)/N$ as the estimated value of $H[f({\xi }_1,{\xi }_2,\cdots ,{\xi }_n)]$.