A Robust Multi-Sensor Data Fusion Clustering Algorithm Based on Density Peaks

. 2019 Dec 31;20(1):238. doi: 10.3390/s20010238

Algorithm 1 Clustering without any overlapping cluster in dataset

Z

Input: dataset Z. Output: cluster

C_{i}

and its cluster center

z_{i}

i \in {1, 2, \dots, k}

1.1: Calculate

ρ_{i}

according to (10) and determine whether there is any overlapping cluster in dataset

Z

according to (16). If there is no overlapping cluster, go to step 1.2; otherwise, see Algorithm 2.

1.2: Calculate

C_{T}

and

\sum k_{i}

according to (14) and (15), then cluster

C_{T}

using the k-means algorithm.

1.3: Revisit each cluster

C_{i}

to make sure that the CL constraint was satisfied, then calculate the cluster center

z_{i}

of each cluster.