Sentence examples for model prediction approaches from inspiring English sources

A signal sequence was considered present when it was predicted both by the artificial neural network and the hidden Markov model prediction approaches (SignalPNN and SignalP-HMM, available as options within SignalP).

The modelling and prediction approaches developed here (see also Chowell et al. [34] for a comparison to other methods) provide tools for real time estimation of epidemiological parameters that are appropriate for emerging infectious diseases.

These approaches can be further divided into data-driven (from-omics to model) and hypothesis-driven (from kinetics data to mathematical model to predictions) approaches.

The results of two real world case studies demonstrate the effectiveness, practicability and accuracy of the proposed modeling and prediction approach.

In this paper, we proposed a TFBS modeling and prediction approach - MIL3D.

Functional data analysis provides a relatively novel modeling and prediction approach, with the potential for many significant applications across a range of public health and biomedical applications.

Many existing prediction approaches model concurrent behaviour insufficiently and yield inaccurate results due to hard underlying assumptions.

For some estimation approaches, adjustment of model prediction bias [15] is also carried out.

For some estimation approaches, adjustment of model prediction bias [ 15] is also carried out.

Compared with other prediction approaches, our RBM model can capture not only the correlations of drug-target pairs in a DTI network but also the correlations of different types of DTIs.

This approach can upscale model prediction for a small watershed with the calibrated SWAT model to a large watershed, generating spatial and temporal estimations of groundwater recharge and nitrate loading for the large watershed.