Transfer learning is a machine technique that takes pre-trained model has already been trained on related task, and adapts it for use new, task. This particularly useful in the context of predictive control (MPC), where deep transfer used to improve training MPC by leveraging knowledge gained from controllers. One way which applied using MPC, then fine-tuning controller new process automation s...

in this paper two different methods are presented to approximate the solution of the fractional black-scholes equation for valuation of barrier option. also, the two schemes need less computational work in comparison with the traditional methods. in this work, we propose a new generalization of the two-dimensional differential transform method and decomposition method that will extend the appli...

We propose a StochAstic Fault diagnosis AlgoRIthm, called Safari, which trades off guarantees of computing minimal diagnoses for computational efficiency. We empirically demonstrate, using the 74XXX and ISCAS85 suites of benchmark combinatorial circuits, that Safari achieves several orders-of-magnitude speedup over two well-known deterministic algorithms, CDA∗ and HA∗, for multiple-fault diagno...