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These comparisons showed that all the available methods were tuned using data obtained from small to medium diameter pipes extrapolated poorly to large diameter pipelines.
The model parameters were tuned using the experimental data of one gait trial, which resulted in a good fitting accuracy (RMSEs between 0.0491 and 0.1399) between the simulation and experimental synergy activations.
Subtractive clustering was employed to transform crisp input data into fuzzy sets and radius of the clusters were tuned using a hybrid of particle swarm optimization and pattern search algorithms.
In the automatic mode, 48 models were formed while parameters of linear and radial basis function (RBF) kernels were tuned using different optimization techniques, cost functions and encoding schemes.
Parameters were tuned using only the training data.
The parameters of the algorithms were tuned using the Taguchi method.
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Alternative, the controller can be tuned using a single parameter.
Multiple PSSs can be tuned using the DNP method sequentially.
The designed controllers are tuned using the introduced procedure.
That rate of release can be tuned using different linkers, says Fetzer.
The model parameters are tuned using only three sets of isothermal data.
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