Generally, positive solutions can build more complicated models with parts embedded inside other parts.
However, it is not the case for more complicated models.
Some more complicated models designed to incorporate more realistic fluid transfer were also proposed.
The more complicated models (called Markov) represent dynamics with some memory, allowing past events to influence the ongoing gameplay dynamics.
However, they have rarely been applied to solving more complicated models, such as the incompressible Navier Stokes equations.
Then more complicated models are developed and used to investigate the effects of multiple wheels on a rail.
An alternative approach, instead using a set of {0,1} dummy variables, produces more complicated models with larger standard errors, while reaching substantially similar conclusions.
We applied different log models, multiplicative models and models with square root transformed variables but in the end multiple linear regression performed as well as more complicated models.
It has been shown that NOE effects can be mitigated using higher RF amplitude (>2.0 uT) [73, 74] or more complicated models taking into account different exchange pathways.
Therefore we did not attempt to find more complicated models or techniques (non-parametric approaches) that could help to improve our results.
This conclusion supports the use of this very simple method to demarcate groundwater productivity zones instead of using more complicated models such as Shannon's entropy model.
