A Self-Adaptive Fuzzyc-Means Algorithm for Determining the Optimal Number of Clusters

A Self-Adaptive Fuzzy c-Means Algorithm for Determining the Optimal Number of Clusters

For the shortcoming of fuzzy c-means algorithm (FCM) needing to know the number of clusters in advance, this paper proposed a new self-adaptive method to determine the optimal number of clusters. Firstly, a density-based algorithm was put forward. The algorithm, according to the characteristics of the dataset, automatically determined the possible maximum number of clusters instead of using the...

OptCluster : an R package for determining the optimal clustering algorithm and optimal number of clusters

An Expansion of -means for Automatically Determining the Optimal Number of Clusters

We expand a non-hierarchical clustering algorithm that can determine the optimal number of clusters by using iterations of -means and a stopping rule based on Bayesian Information Criterion (BIC). The procedure requires merging the clusters that a -means iteration has made to avoid unsuitable division caused by the division order. By using this additional merging operation, the case of adequate...

Using Electromagnetism Algorithm for Determining the Number of kanbans in a Multi-stage Supply Chain System

This paper studies the multi-stage supply chain system (MSSCM) controlled by the kanban mechanism. In the kanban system, decision making is based on the number of kanbans as well as batch sizes. A kanban mechanism is employed to assist in linking different production processes in a supply chain system in order to implement the scope of just-in-time (JIT) philosophy. For a MSSCM, a mixed-integer...

Determining the Optimal Number of Clusters in Cluster Analysis

Cluster analysis is the multivariate method which objective is to classify the objects. In current literature there are many methods and many distances measures, which can be mutually combined. There is no manual and rule which would clearly identify the appropriate combination method and distance measures during clustering. Simultaneously, in cluster analysis it is often necessary to determine...