Blind voice separation refers to retrieve a set of independent sources combined by an unknown destructive system. The proposed separation procedure is based on processing of the observed sources without having any information about the combinational model or statistics of the source signals. Also, the number of combined sources is usually predefined and it is difficult to estimate based on the ...

Real World is filled with various hard and complex problems. One such complex problem is an optimization problem. Optimization has been an active area of research for several decades. . Optimized solutions are hard to find so there are no deterministic algorithms that can find exact solution in polynomial time. In large domain of applications of intelligence techniques we are interested in expl...

In this study, the performance of the algorithms of whale, Differential evolutionary, crow search, and Gray Wolf optimization were evaluated to operate the Golestan Dam reservoir with the objective function of meeting downstream water needs. Also, after defining the objective function and its constraints, the convergence degree of the algorithms was compared with each other and with the absolut...

This paper proposes a novel approach called the Harris’s Hawk Multi-Objective Optimizer (HHMO), which is used for solving reference point multi-objective problems. This algorithm is based on the grey wolf multi-objective optimization algorithm and motivated by the cooperative hunting behaviors of the Harris’s Hawk. These hawks are known as the wolf pack of the sky. The hunting party consists of...

In this article, a multi-objective planning is demonstrated for reactive power compensation in radial distribution networks with wind generation via unified power quality conditioner (UPQC). UPQC model, based on phase angle control (PAC), is used. In presented method, optimal locating of UPQC-PAC is done by simultaneous minimizing of objective functions such as: grid power loss, percentage of n...

Exploration and exploitation are two essential components for any optimization algorithm. Much exploration leads to oscillation and premature convergence while too much exploitation slows down the optimization algorithm and the optimizer may be stuck in local minima. Therefore, balancing the rates of exploration and exploitation at the optimization lifetime is a challenge. This study evaluates ...