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The resulting IRRs were combined using Rubin's combination rules [ 18].
Fifteen imputed datasets were generated and combined using Rubin's combination rules [ 23].
The number of imputations was set at 15, and imputed data sets were combined using Rubin's combination rules.
Several feature combination rules were tested by combining the similarity maps using different computations.
The results illustrate that the approximate combination rules can considerably over- or underestimate the extremes of combined responses depending on the ratio and correlation coefficient of the response components.
The uncertainties associated with MCDA techniques applied to LSM are due to incomplete and inaccurate data on landslide contributing factors, rules governing how the input data are combined into landslide susceptibility values and parameters used in the combination rules (Ascough et al., 2008).
This study re-evaluates the performance of some approximate combination rules used in practice for estimating the mean extremes of linearly combined correlated wind load effects.
Relationships between sources of evidence determine appropriate combination rules.
The obtained results outperform those obtained with the existing combination rules.
However, their combination rules yield counter-intuitive results in high conflicting activities.
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We also explored a multiplicative combination rule whereby we combined the maps in a point-wise multiplicative manner.
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