Exact(18)
In case of large systems (e.g. several agents, multiple procedures, many technical equipment), building a FRAM model may become a difficult task, moreover resulting in a complex model, with limited benefits for the purpose of the analysis.
The experimental results were obtained by running experiments with the underwater snake robot Mamba, while the simulation results were obtained by using the complex model of the robot described in "A complex model of underwater snake robots".
Simulation results for the control-oriented model are shown in Figs. 6a and 7a, while Figs. 6b and 7b show simulation results for the complex model presented in "A complex model of underwater snake robots".
The simulation results show that the properties derived based on the control-oriented model hold also for the complex model presented in "A complex model of underwater snake robots", something which supports the assumption that the control-oriented model is a valid approximation of the complex model for analysis and control design.
Based on the closed form model which is briefly presented in "A complex model of underwater snake robots", empirical rules are derived in [46] through an extensive simulation study for the relationships between the parameters of the gait patterns, the consumed energy and the forward velocity for different motion patterns for underwater snake robots.
The fluid dynamic model of the control-oriented model presented in [44] is notably less complex than the fluid dynamic model presented in "A complex model of underwater snake robots", which takes into account significant parameters such as added mass effects, linear drag forces, torques due to the added mass and linear drag forces.
Similar(42)
In training a complex model, such as a deep neural network, the use of small data sets can lead to something called overfitting, which is a common pitfall in machine learning.
However, in condensing a complex model into a single score, there are caveats to consider.
Construction of a proxy model, and its subsequent use in calibration of a complex model, and in analysing the uncertainties of predictions made by that model, is implemented in the PEST suite.
Generally, a simple model should always be chosen in preference to a complex model, if the latter does not fit the data better.
The system of differential equations we have presented in (1) is a complex model with a large number of parameters.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
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