The phrase "a combination model of" is correct and usable in written English.
It can be used when referring to a model that integrates multiple elements or components to form a cohesive whole.
Example: "The researchers developed a combination model of climate change impacts and socioeconomic factors to better understand future scenarios."
Alternatives: "an integrated model of" or "a composite model of".
Here, as a new approach, a combination model of heat balance and linear temperature profile estimation has represented which makes the nodal analysis three times faster and it is as accurate as heat balance calculations.
The tip can be simplified as a combination model of a cone and a spherical cap when the radius of the tip apex is small relative to the distance z [16 20].
Carrying out a nonlinear inversion based on the displacements obtained by two of the four pairs, we found that a combination model of an open crack and a deflation sill is better than a model of an open crack only.
Using SELDI-TOF MS, Hart et al. [ 80] characterized the oral flora and salivary proteome in caries-free and caries-active children, and found that a combination model of microbial-proteomic data was far more accurate than microbial or proteomic models alone.
Since the mixed model was a combination of models of higher coefficient of determination, it was considered that the mixed model was the most valid model for our study.
The tweet didn't specify if this was a combination of Model S, Model X and Model 3 vehicles.
In other words; the new model is a combination of model (11) and goal programming modeling.
Because the mixed model was a combination of models with a higher coefficient of determination, we believed the mixed model to be the most valid for this study.
It returns a set of parameters for each realization of the sample (the number specified using the 'num' parameter setting), with a corresponding flux and flux uncertainty for the input model component or a combination of model components.
The Smoothing M Model is a combination of Models M and U, with weighting factors of 0.75 and 0.25, respectively.
Other methods include using Information Criterion which measure a combination of model fit with penalization for additional classes in the model.
