Subsection 'Performance measurement of clustering molecules' describes how to quantify the quality of a clustering of some algorithm with a given reference clustering.
Real-life experiments with the proposed algorithm for a cluster of three vehicles will demonstrate the usefulness of the approach.
In step 3, the FLSOM algorithm performs a clustering of the fingerprints and generates a U-Matrix visualization [2].
The performance of a clustering routing algorithm can thus be evaluated by CHs energy consumption, as shown in Figure 3.
The objective of a clustering algorithm is to identify homogeneous clusters of data points based on similarity of the data points.
However, the design of a clustering algorithm with the goal of enhancing localization performance has not been addressed to the best of these authors knowledge.
Measuring the quality of a clustering algorithm has shown to be as important as the algorithm itself.
The number of clusters was determined by Figure of merit (FOM) analysis, which basically is an estimate of the predictive power of a clustering algorithm [ 81].
The reviewers have raised a concern regarding the forcing of a clustering algorithm to allot cells into a pre-defined number of clusters.
In this paper we propose a family of algorithms combining tree-clustering with conditioning that trade space for time.
