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MLR and ANN are both practicable for modeling the quantitative relationship between the MDEV index and the KOA of PBDEs.
In addition, the result demonstrates MLR and L-ANN are both practicable for modeling the quantitative relationship between the MDEV index and KOA of PBDEs.
It has been recognized [19] that mathematically modeling the quantitative data [8], [20] could resolve these "threshold" issues, and there has been considerable progress in statistical computer models for interpreting complex DNA evidence [9], [21], [22], [23].
Several individual-based models in this special issue include more complexity by modeling the quantitative inheritance of traits and ecological feedback (Dunlop et al. 2009; Enberg et al. 2009; Okamoto et al. 2009; Wang and Höök 2009).
The phage-determined regulation of gene expression provides a basis for understanding and modeling the quantitative dynamics of the intracellular life cycle; this understanding likewise provides a basis for positioning design elements to avoid disrupting genes and regulatory elements.
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Thus, we firstly investigate whether MLR can model the quantitative relationship between the MDEV index and the lgKOA of these PBDEs.
A 2-1 RBF-ANN (i.e. there are 2 nodes in the input layer and 1 node in the output layer) was used to model the quantitative relationship between the MDEV index and the lgKOA.
The above models are prospective models, that is, they model the quantitative phenotype in terms of the offspring genotype.
We formally modeled the quantitative allocation of input nutrients among the branches of the metabolic network (AIO).
These authors modeled the quantitative utility function based on a set of axioms that described decision-maker's behavior.
Zhu et al. modeled the quantitative relationship between HMs and CE inclusion by linear regression and showed that HMs were predictive of exon inclusion levels [ 26].
Related(18)
introducing the quantitative
samples the quantitative
design the quantitative
shaped the quantitative
rendering the quantitative
modeling the inbreeding
modeling the effective
modeling the mean
modeling the specific
modeling the whole
modeling the spatial
modeling the exact
modeling the late
modeling the long
modeling the inquisitive
modeling the basic
modeling the ancient
simulation the quantitative
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