The modification implements an error-handling mechanism which lowers the incidence of an expert's careless errors.
We implement an error indicator and a shock identifier to capture shocks with slope-limited linear elements, while using high-order Legendre polynomials for smooth solution regions.
Usually, the effects of this problem are minimized by using low thermal-expansion materials in the arm design or by implementing an empirical error correction model based on the outputs of several temperature sensors placed inside the arm.
Numerical results show the reliability of the implemented a posteriori error estimators.
For some simulations, we implemented a typing error to assess any reduction in correct classification rate of RCAs.
Therefore, create a new model (run3.mod) based on run2.mod and implement a combined error model using e.g.: Y = IPRED * (1+EPS(1)) + EPS(2) W = SQRT IPRED**2*SIGMA(1,1)**2 + SIGMA 2,2)**2) IWRES = (DV-IPRED /W It must be noteDV-IPRED / plot mentioned above is only informative at loW ε-shrItkage (as a rule of thumustat ε-shrinkage greater than ~5%, this plot loses informativeness).
The adjustment is implemented with an error correction algorithm like Least Mean Square (LMS).
In the proposed scheme, it is possible to implement both an error concealment algorithm and a tampering detection algorithm.
The motivation for using the quantile rather than the actual value is that it implements a simple normalization of the error.
Similarly, the model implementing a combined residual error was superior to that with an additive residual error only (ΔOFV of −6002).
This is consistent with the idea that, in an uncertain feeding environment, the variability serves to implement a trial-and-error diversification of the feeding movements until a movement succeeds [21], [58].
