Sentence examples for modeling complex relationships from inspiring English sources

As ANN are non-linear statistical data modeling tools their achievement for modeling complex relationships between inputs and outputs or to find patterns in data are more successful than statistical methods.

A semiparametric GAM was used since it is well-suited to modeling complex relationships where an underlying nonlinear relationship is not known a priori (Wood 2006).

They concluded that the whole model should be able to adapt to different conditions by making separated sub-models for different states of the process, because a single uniform model always had problem in modeling complex relationships in the whole WTP process.

Network science has gained popularity in biological sciences thanks to its ability of modeling complex relationships among a large number of entities [ 20, 21].

Here we present the mechanistic insight derived from a mathematical structure ("wiring diagram") used to model complex relationships between a highly relevant (p = 9.43 × 10− 12) global "cancer network" of 32 genes and their known links.

They can be used to model complex relationships between inputs and outputs.

ANFIS has been applied in many aspects of mineral processing to model complex relationships (For flotation, ANFIS is applied to the prediction of collision probability, recovery, gas holdup, diameter, and surface area flux of bubbles) (Jorjani et al. 2008, 2009; Chelgani et al. 2010, 2011a, b; Chelgani and Makaremi 2013; Shahbazi et al. 2013a, b).

It has been widely established that to model complex relationships, when regression (linear or non-linear) cannot accurately correlate variables, soft computing methodology can effectively be used, as this technique is developed to exploit tolerance for imprecision, uncertainty, and partial truth.

To model complex relationships (one species influencing multiple others), methods employing mathematical and statistical models have been developed recently.

ANN is often applied to model complex relationships between inputs and outputs or to find patterns in data.

The artificial neural networks, a non-linear statistical data modeling tool, can be used to model complex relationships between inputs and outputs.