Sentence examples for ranking estimation from inspiring English sources

This MCDM method is based on two processes, the weights assessment of each criterion using the FAHP and the ranking estimation of each possible solution by means of one of the following techniques: the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS), Simple Additive Weighting (SAW), Multiplicative Exponential Weighting (MEW), or the Grey Relational Analysis (GRA) [14 19].

The work flow proceeds by the following steps: 1) parameter estimation, 2) ranking estimated parameters according to their identifiability, 3) calculating parameter variances, and 4) simplifying those parts of the model that contain the least identifiable parameters.

The final weights were created using an iterative process (ranking ratio estimation).

Kanatani and Matsunaga [2] proposed a method for estimating the number of independently moving objects based on the rank estimation of the affine space using the geometric minimum description length (MDL).

The extrapolated rank estimation for motif extraction was 1,286.

The matrix can then be restructured as low-rank estimation.

Table 3 Latent rank estimation for MQs and HQs Eval.

This rank estimation of molecules enables the quantitative comparison of similarity values of different fingerprint types.

Though we have shown a rank estimation method in this paper, it is a time-consuming brute force searching way.

This phenomenon is attributed to the rank constrains of MC leading to a low rank estimation which causes an incorrect estimation of missing measurements.

In [14], clutter rank estimation was investigated with waveform diversity and it was derived that the clutter covariance matrix could be a function of waveform covariance matrix.