This paper deals with the tuning of parameters for Automatic Generation Control (AGC). A two area interconnected hydrothermal system with PI controller is considered. Genetic Algorithm (GA) and Particle Swarm optimization (PSO) algorithms have been applied to optimize the controller parameters. Two objective functions namely Integral Square Error (ISE) and Integral of Time-multiplied Absolute v...

This paper deals with the tuning of parameters for Automatic Generation Control (AGC). A two area interconnected hydrothermal system with PI controller is considered. Genetic Algorithm (GA) and Particle Swarm optimization (PSO) algorithms have been applied to optimize the controller parameters. Two objective functions namely Integral Square Error (ISE) and Integral of Time-multiplied Absolute v...

Social Spider Optimization (SSO) algorithm is a swarm intelligence optimization algorithm based on the mating behavior of social spiders. Numerical simulation results have shown that SSO outperformed some classical swarm intelligence algorithms such as Particle Swarm Optimization (PSO) algorithm and Artificial Bee Colony (ABC) algorithm and so on. However, there are still some deficiencies abou...

An effective hybrid artificial bee colony algorithm is proposed in this paper for nonnegative linear least squares problems. To further improve the performance of algorithm, orthogonal initialization method is employed to generate the initial swarm. Furthermore, to balance the exploration and exploitation abilities, a new search mechanism is designed. The performance of this algorithm is verifi...

Evolutionary Algorithms (EAs) are a fascinating branch of computational intelligence with much potential for use in many application areas. The fundamental principle of EAs is to use ideas inspired by the biological mechanisms observed in nature, such as selection and genetic changes, to find the best solution for a given optimization problem. Generally, EAs use iterative processes, by growing ...

This study addresses swarm intelligence-based approaches in data quality detection. First, three typical swarm intelligence models and their applications in abnormity detection are introduced, including Ant Colony Optimization (ACO), Particle Swarm Optimization (PSO), Bee Colony Optimization (BCO). Then, it presents three approaches based on ACO, PSO and BCO for detection of attribute outliers ...

The firefly algorithm has become an increasingly important tool of Swarm Intelligence that has been applied in almost all areas of optimization, as well as engineering practice. Many problems from various areas have been successfully solved using the firefly algorithm and its variants. In order to use the algorithm to solve diverse problems, the original firefly algorithm needs to be modified o...

Particle swarm optimization method is based on artificial intelligence technique. It is an optimization method that was developed in 1995 by Eberhart and Kennedy based on the social behaviors of fish schooling or birds flocking. By increasing the overall rate of fault detection, a greater number of errors can be found more rapidly in the code. Particle , fitness function , local best , global b...

Swarm intelligence algorithms are amongst the most e±cient approaches toward solving optimization problems. Up to now, most of swarm intelligence approaches have been proposed for optimization in static environments. However, numerous real-world problems are dynamic which could not be solved using static approaches. In this paper, a novel approach based on arti ̄cial ̄sh swarm algorithm (AFSA) ha...

the dogleg severity is one of the most important parameters in directional drilling. improvement of these indicators actually means choosing the best conditions for the directional drilling in order to reach the target point. selection of high levels of the dogleg severity actually means minimizing well trajectory, but on the other hand, increases fatigue in drill string, increases torque and d...