Sentence examples for model combinations and from inspiring English sources

For breaking random wave cases, the computed results of the two model combinations and FUNWAVE agreed well with the measurements.

Similarly to autumn season, there is a general trend according to which winter precipitation variation range is wider compared to the corresponding variation range of the historical period, thus indicating increment in precipitation extremes, either low or high, for most of the examined model combinations and sub-periods.

Based on the overall results produced by the examined model combinations and taking into account that the reference period (1981 2000) includes a severe drought period (Loukas and Vasiliades 2004) which significantly affected the water balance of PRB, the anticipated effects of climate change in water resources availability and management are expected to be severe.

The motivation for doing this is (1) to avoid the unnecessary simplifying assumptions that currently exist in many evolutionary analysis packages and (2) to provide new model combinations and a flexible system for model specification so that researchers can tailor their evolutionary analyses to their specific set of questions.

The combination module has the functions that include the 3D model combination and 1D relevance.

Results obtained with first- and second-order CRF models alone (without model combination) and after post-processing are shown with differences compared to the corrected run.

For the model combination and refinement step of our pipeline, we used a novel global local model combination algorithm.

As mentioned, MULTICOM-REFINE, MUProt and MULTICOM all focus on model combination and refinement, and all implement the global local model combination algorithm just described.

MULTICOM-REFINE, MUProt, and MULTICOM (our human-expert predictor) implemented the fourth and fifth portions of our general pipeline (model evaluation, model combination and refinement).

Our multi-level combination pipeline (Fig. 1) for protein structure prediction is generally comprised of five steps: (i) template identification and ranking, (ii) multi-template combination, (iii) model generation, (iv) model evaluation and (v) model combination and refinement.

The top 50% of the models generated by MULTICOM-CMFR and MULTICOM-RANK in addition to all the models generated by MULTICOM-CLUSTER were selected for model combination and refinement.