A constrained version of the Big Bang-Big Crunch algorithm for the efficient solution of the optimal reservoir operation problems is proposed in this paper. Big Bang-Big Crunch (BB-BC) algorithm is a new meta-heuristic population-based algorithm that relies on one of the theories of the evolution of universe namely, the Big Bang and Big Crunch theory. An improved formulation of the algorithm na...

With the rapid development of swarm intelligence research field, a large number of algorithms in swarm intelligence are proposed one after another. The strong points and the drawbacks of a specific swarm intelligence algorithm becomes clear to be seen when the number of its application increases. To overcome the handicaps, some hybrid methods are invented. In this review, three hybrid swarm int...

Multilevel thresholding is a method that is widely used in image segmentation. The thresholding problem is treated as an optimization problem with an objective function. In this article, a simple and histogram based approach is presented for multilevel thresholding in image segmentation. The proposed method combines Tsallis objective function and Particle Swarm Optimization (PSO). The PSO algor...

The basic theories, development and applications of particle swarm optimization and genetic algorithm are introducedd.Some models of improved PSO algorithms are outlined. Characteristics of PSO and GA are compared. Two methods of hybrid of PSO and GA at present was summarized:hybrid with two algorithms entirely or with only a few steps ,and illustrated with flowchart.Limitation of two methods o...

Bilinear models can approximate a large class of nonlinear systems adequately and usually with considerable parsimony in the number of coefficients required. This paper presents the application of Particle Swarm Optimization (PSO) algorithm to solve both offline and online parameter estimation problem for bilinear systems. First, an Adaptive Particle Swarm Optimization (APSO) is proposed to inc...

The Optimal Power Flow (OPF) is one of the most important issues in the power systems. Due to the complexity and discontinuity of some parameters of power systems, the classic mathematical methods are not proper for this problem. In this paper, the objective function of OPF is formulated to minimize the power losses of transmission grid and the cost of energy generation and improve the voltage ...

This paper introduces the application of particle swarm optimization techniques to generalized adaptive nonlinear and reeursive fdter structures. Particle swarm optimization (PSO) is a population based optimization algorithm, similar to the genetic algorithm (GA), that performs a struetored randomized search of an unknown parameter space by manipulating a population of parameter estimates to co...

Mining Sequential Patterns in large databases has become an important data mining task with broad applications. It is an important task in data mining field, which describes potential sequenced relationships among items in a database. There are many different algorithms introduced for this task. Conventional algorithms can find the exact optimal Sequential Pattern rule but it takes a long time,...

This paper introduces the application of particle swarm optimization techniques to generalized adaptive nonlinear and recursive filter structures. Particle swarm optimization (PSO) is a population based optimization algorithm, similar to the genetic algorithm (GA), that performs a structured randomized search of an unknown parameter space by manipulating a population of parameter estimates to c...