In this paper, a novel denoising algorithm based on the denoising methods of partial differential equations

is presented. The proposed algorithm is obtained by using a stochastic algorithm for combining two denoising ...

We introduce a practical generalization of the standard personnel assignment problem. In this problem, we have a set of personnel and a set of lost and found centers. Each center receives a stochastic demand. Some constraints, ...

different load reduction strategies. In the presented problem the uncertainty of market price is considered and the risk of aggregator participation is managed in stochastic optimization problem with CVaR. The feasibility of this problem is studied on a case...

In this paper, nonlinear stochastic differential equations solved by a new approach. In this approach a nonlinear ...

different load reduction strategies. In the presented problem the uncertainty of market price is considered and the risk of aggregator participation is managed in stochastic optimization problem with CVaR. The feasibility of this problem is studied on a case...

of probability in the optimization process, and then an analytical approach is used to solve the new model of stochastic congestion management. In this approach, the stochastic optimization problem is transformed into an equivalent deterministic problem. Moreover...

The optimization of spatially complex groundwater management models over long time horizons

requires the use of computationally efficient groundwater flow models. This paper presents a new

stochastic multi-cell ...

‎Control theory is a mathematical description of how to act optimally‎ ‎to gain future rewards‎. ‎In this paper we give an introduction to deterministic‎ ‎and stochastic control theory; partial observability‎ ‎, ‎learning ...