However, in the conventional error states-based GPS aided inertial navigation system (GPS/INS), the stochastic model tuning is difficult for the IMU's measurements due to the amalgamation of the observables from inertial sensor and other aiding sensors.
This is to be expected, since this is the building floor that was used for model tuning purposes.
2, while Sect. 3 presents the general model, Sect. 4 describes the specific proposed model, the Kalman filtering technique and the heuristics used for model tuning, Sect. 5 describes the proposed experiment and results.
The parameters for model tuning were the value of γ (the parameter of the RBF kernel) and the number of features.
We use a cross-validation strategy for assessment of model prediction (Molinaro et al., 2005; Simon et al., 2011), with an additional inner level of cross-validation for model tuning in training data (Goeman, 2011).
The model, tuned both for the thermo-mechanical analysis and the phase transformation through experimental data, is able to predict the phase volume fraction in the typical zones of the joints at the varying of the main process parameters.
This paper proposes a generic method for the stochastic model tuning about the random errors in IMU measurements together with other sensors.
Further, we show how the proposed approach allows for considering the model tuning and spatial grid design as a joint problem with respect to the purpose of the proxy model.
We take a novel approach to GPU code implementation and use run-time code generation techniques and a high level programming language (Python) to achieve state of the art performance, while allowing easy experimentation with different LBM models and tuning for various types of hardware.
The Model 3 tuned for better performance might inherit more of the muscle of the Model S, in a smaller, lighter package, but Musk says not to expect it to ever top the Model S on acceleration, since the original Tesla electric luxury sedan will always be able to accommodate a larger battery.
