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The algorithm utilizes two major heuristics based solutions to make the clustering capable to handle large datasets.
Constrained Clustering allows to make the clustering task more accurate by integrating user constraints, which can be instance-level or cluster-level constraints.
However, it may make the clustering result with excessive overlap and cluster bridge edge and border edge mistakenly to adjacent communities.
As the initial clustering centers throughout the whole solution space, it is effective to make the clustering results insensitive to the initial centers.
Hence, we have chosen the classical FCM algorithm in the current work rather than its variants and applied GA on it for optimizing the cluster centers by searching a global optimum to make the clustering approach more robust.
Average linkage was used as the clustering method to make the clustering as unbiased as possible.
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"There are a wealth of fantastically interesting targets for astrophysics that can be observed in the ecliptic plane, which were not accessible in the original Kepler field, notably brighter clusters of stars – where the common origins and distances to these stars make the clusters excellent laboratories for testing our understanding of stars – and young, star-forming regions," said Chaplin.
How can the cluster header optimally make the cluster decision?
Hierarchical clustering requires a branch pruning procedure to make the clusters more meaningful with respect to the cluster sizes and the number of clusters.
Therefore, a node with a lower RVM value is preferred to act as the cluster head to make the cluster more stable.
Second, the multi-satellite autonomous assembly algorithm and control algorithm of the cluster motion are developed to make the cluster system combine into a variety of configurations in order to achieve different types of functionality.
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