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In [40], multiple additive decision trees are also employed, but they train this structure using minimum generation error (MGE) criterion.
Similarly, [50] proposed another additive structure with multiple decision trees, but a minimum generation error (MGE) measure was used as the selection criterion instead of the more common maximum likelihood (ML) measure.
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Values obtained after ten generations of management in the scenario involving one introgression event according to number of exogenous individuals per generation; errors for native representation ranging between 0.000 and 0.012 and for ΔF 10 between 0.002 and 0.012.
However, we do not intend to focus on a general error rate, but rather assess the effect of several variables on error generation.
This led to the generation of error in ortho-rectification due to change of landform.
A scenario-based and chance constrained optimization method is hired to consider the WF power generation prediction error.
Issues related to concept refinement, default implementations of requirements, and the generation of error messages are also discussed.
SBL is a parametric forecast approach which assumes that the wind power generation forecast error at each moment follows a Gaussian distribution.
First, digraph generation is error prone, time consuming and second, a large number of spurious solutions are generated due to the qualitative nature of the analysis.
We propose two criteria for rule generation: system error and ε-completeness reflecting both a performance and sample coverage of an existing rule base.
To ensure a good transmission rate of the transmitter, it is based on a double data rate (DDR) interface, and to ensure data integrity, detection modules based on the generation and error checking cyclic redundancy check (CRC) were developed.
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