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CA based approaches are based on a discrete representation of the simulated environment.

Traditional model-based approaches are based on periodic iterations, where the continuous-time model is discretized with a fixed period.

The statistical-based approaches are based on extracting the features that correspond to mean, variance, moments, and energy.

For example, traditional approaches are based on Tarjan's algorithm; search-based approaches are based on metaheuristics, usually genetic algorithms (GA).

Unlike the aggregation-based MCDM approaches which are based on explicit mathematical formula as a fixed preference, the synthesizing criterion-based approaches are based on implicit rules.

CS-based approaches are based on the fact that communications signals are not accurately described as stationary, but rather more appropriately modeled as cyclostationary.

Phenotypic effect-based approaches are based on the various phenotypic responses, such as expression profiles and side effects, to external compounds [2] [5].

Distribution-based approaches are based on statistical characteristics of the PROM scores in a patient sample.

However, distribution-based approaches are based on the statistical characteristics of the sample.

Distribution-based approaches are based on statistical characteristics of the obtained samples.

Distribution-based approaches are based on statistical characteristics of the sample at issue.