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The performance of NL means method is comparable with the WS detector [15].

So, the specialization improved nonlocal means method is developed for the damage identification of generator bearing.

The effectiveness of specialization improved nonlocal means method is verified by fault identification cases study including variable speed condition.

The objective of the k means method is to minimize the value of cost which is defined by begin{aligned} mathrm{Cost}=sum _{i=1}^n mathrm{dist}(d_i,c_k) end{aligned} (1 where (mathrm{dist}(d_i,c_k)) represents the Euclidean distance between (d_i) and (c_k) (the cluster center).

As the ratio of means method is unitless, this method can be used irrespective of the units used in trial outcome measures.

Similar(54)

In addition, linear regression with the least squares means method was used to determine adjusted mean values attributable to SSI due to MRSA and methicillin-resistance for postoperative total hospital days and 90-day hospital charges.

Cluster analysis (k means method) was used to identify the subgroups of patients homogeneous with respect to overall adaptation to disease, and analysis of variance was applied to compare the mean scores on social support dimensions between the identified subgroups.

The K-means method is numerical, unsupervised and iterative.

An adaptive K-means method is incorporated in the proposed group-based PSO (Stage I) for global search.

The k-means method is a simple, non-parametric clustering method that minimizes within-cluster variability and maximizes between cluster variability.

The standard K-means method is the most popular clustering method due to its simplicity and reasonable execution efficiency when applied to small datasets.

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