'To analyze the relationship among objective functions and design variables, some of the representative solutions from the pareto optimal front (POF) were selected by performing K- mean clustring'.
I want to know what this method means? And how to apply it?
I am working on mutli objective optimazation of microchannel heat sink. So can anyone give me some basic lead related to that?
The k-means algorithm takes the input parameter, k, and partitions a set of n objects into k clusters so that the resulting intra-cluster similarity is high but the inter-cluster similarity is low.Cluster similarity is measured in regard to the mean value of the objects in a cluster, which can be viewed as the cluster’s centroid or center of gravity.
“How does the k-means algorithm work?” The k-means algorithm proceeds as follows. First, it randomly selects k of the objects, each of which initially represents a cluster mean or center. For each of the remaining objects, an object is assigned to the cluster to which it is the most similar, based on the distance between the object and the cluster mean. It then computes the new mean for each cluster. This process iterates until the criterion function converges. Typically, the square-error criterion is used.
Referred Book: Data Mining by J. Han and M. Kamber
- Badges
- Science topic
- Similar topics
- Heat