Hence, a closed loop simulation study was performed to see the differences between the performance of model predictive controller using previously estimated linear and nonlinear models and a standard proportional integral (PI) controller.
We can therefore "group together" a number of statements and execute them in one "atomic" rewrite step; this significantly improves the performance of model checking compared to standard approaches where each action is performed by a rewrite step.
In order to evaluate the performance of model in this study, we used the eight different models to perform independent test on ten multiclass datasets.
The diagnostic performance of model 2 was confirmed in the validation set (AUC: 0.87; sensitivity: 0.84; specificity: 0.90) (Fig. 2c).
The diagnostic performance of model 1 was confirmed in the validation set, revealing that the model was very accurate (AUC: 1.00; sensitivity: 0.99; specificity: 1.00) (Fig. 1c).
Warren, D. L. & Seifert, S. N. Ecological niche modeling in Maxent: the importance of model complexity and the performance of model selection criteria.
The quality of a model determines the closed loop performance of model predictive controllers.
Simulation shows that the wind load performance of model 2 is better than model 1.
Investars, for instance, a tracking service in Hoboken, N.J., reviewed the performance of model stock portfolios based on the firms' stock recommendations from July 25 , 2000 through July 24 this year.
Supervised heatmaps have two primary aims: to provide a means of visual extraction of the information contained within high-dimensional datasets, and to provide a visual assessment of the performance of model fits to these datasets.
