Computational fluid dynamics (CFD) analysis is widely used in chemical engineering. Although CFD calculations are accurate, the computational cost associated with complex systems makes it difficult to obtain empirical equations between system variables. Here, we combine active learning (AL) and symbolic regression (SR) get a equation for variables from simulations. Gaussian process regression-b...

For the classification problem in practice, one of challenging issues is to obtain enough labeled data for training. Moreover, even if such has been sufficiently accumulated, most datasets often exhibit long-tailed distribution with heavy class imbalance, which results a biased model towards majority class. To alleviate semi-supervised learning methods using additional unlabeled have considered...

In order to tracking the desired discontinuous output trajectory, we explore P-type iterative learning control law with initial state learning for impulsive differential equations. The sufficient conditions of open-loop and closed-loop iterative learning schemes in the sense of L-norm are established. Finally, an example is given to illustrate our theoretical results. 2014 Elsevier B.V. All rig...