Sentence examples for models use multiple from inspiring English sources

Generally speaking, the difference between spatial Markov chain model and Markov mesh model is that the latter uses directly the local conditional probabilities in Eq. (3) or the joint probability in Eq. (2), and spatial Markov chain models use multiple one-dimensional transition probabilities or simplified formulas of the local conditional probabilities in Eq. (3).

In Fig. 1, the existing macroscopic models use multiple vertical uniaxial elements of concrete and re-bar in order to describe the flexure-compression responses of walls such as the relocation of neutral axis in wall cross-sections, tension stiffening behavior of concrete, flexural crack opening and closing, and the confinement effect of the concrete in boundary elements.

For example, several of these models use multiple low-intensity insults to induce the widespread hyperalgesia (for example, multiple acid injections, fatigue with acid injections, hyperalgesic priming), while another uses disruption of biogenic amines in the central nervous system mimicking underlying changes observed in FMS.

The experimental data were fitted to quadratic response surface models using multiple regression analysis.

The experimental data were satisfactorily fitted to quadratic models using multiple regression analysis.

We present an approach for human body parts tracking in 3D with prelearned motion models using multiple cameras.

Finally this study confirms that the calibration of models using multiple environmental timeseries (such as MODIS ETobs and Q) can be used to identify structural model issues.

The experimental data were fitted to quadratic response surface models using multiple regression analysis with high coefficient of determination value (R) of 0.9906.

We built various multi-kernel models using multiple subsets of sensors and analyzed their performance when increasing the number of faulty sensors.

In this study, we developed regionalization models using multiple linear regression and regression tree analysis to derive relationships between hydrologic response and watershed physical characteristics for 163 watersheds in the Great Lakes basin.

When constructing prediction models using multiple parameters, it is important to choose the most optimal parameter set[19].