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First generation (1984-1987) models are simpler and lighter while second generation (1988-1991) care are more refined and heavier.
Both models are simpler than most of the decoupled mechanisms reported in the literature.
We also observed that aggregation-based models are simpler (less over-parameterized) than detail-based models.
Artificial neural network pattern identification and function approximation models are simpler techniques, based only on whole-pattern similarity relations.
Our study demonstrated that ANN models are simpler, adaptive and more reliable tools for the prediction of flexural strength of corroded RC beams.
The eye models are simpler and less powerful compared to the face model and comprise five stages only and less features, because searching within face regions will lead to few false positives.
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Computational models are simple because they do not involve complex mathematical analysis.
Logical models are simple because they deal only with the logical sequence of events.
Population models are simple enough for evaluation before use to inform public policy making.
However, these two models are simple.
Because such BLUP models are simple and have low computational requirements, they have become popular approaches for practical genomic prediction.
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