Discovering Human Activities from Binary Data in Smart Homes

. 2020 Apr 29;20(9):2513. doi: 10.3390/s20092513

Algorithm 15 findPotentialClusters.

Input:

\vec{Z}

Output: $η, r^{*}$ , $c^{*}$

1:
${\hat{\vec{d}}}^{r} \leftarrow 0, {\hat{\vec{d}}}^{c} \leftarrow 0, {\hat{\vec{d}}}^{s} \leftarrow 0$
2:
$r^{*} = 0, c^{*} = 0, b^{*} = 0, η = 0$
3:
for $i \leftarrow 1$ to $\hat{N}$ do
4:
${\hat{d}}_{i}^{r} = i$
5:
${\hat{d}}_{i}^{s} = max (\vec{Z} (i, *))$
6:
${\hat{d}}_{i}^{c} = i^{*}$
7:
end for
8:
$η = max ({\hat{\vec{d}}}^{s})$
9:
$r^{*} = {\hat{d}}_{b^{*}}^{r}$
10:
$c^{*} = {\hat{d}}_{b^{*}}^{c}$