With regard to the improvement of image quality, image enhancement is an important process to assist human with better perception. This paper presents an automatic image enhancement method based on Artificial Bee Colony (ABC) algorithm. In this method, ABC algorithm is applied to find the optimum parameters of a transformation function, which is used in the enhancement by utilizing the local an...

This paper proposes an artificial bee colony (ABC) algorithm for solving optimal power flow (OPF) problem. The objective of the OPF problem is to minimize total cost of thermal units while satisfying the unit and system constraints such as generator capacity limits, power balance, line flow limits, bus voltages limits, and transformer tap settings limits. The ABC algorithm is an optimization me...

In this study, a new artificial intelligence based optimization method is applied to optimize the gains of PID controller for Automatic Voltage Regulator (AVR) system. A dynamic performance of the controller which is optimized with ABC algorithm is compared with the results which are obtained with Particle Swarm Optimization (PSO). The transient response analysis is used in order to determine t...

In Neal (2010), a novel Approximate Bayesian Computation (ABC) algorithm, coupled ABC, was introduced. This paper shows how coupled ABC can be used in an efficient manner for model choice in a Bayesian framework. The methodology is applied to Gibbs random fields and stochastic epidemic models. Furthermore a very efficient simulation procedure for Gibbs random fields with a given sufficient summ...

Abstract This paper provides a new approximate Bayesian computation (ABC) algorithm with reduced hyper‐parameter scaling and its application to nonlinear structural model calibration problems. The initially takes the ABC‐SubSim structure sequentially estimates by autonomous adaptation following Markov chain approach, thus avoiding error associated modeler's choice for these hyper‐parameters. re...

Predicting the secondary structure of protein has been the focus of scientific research for decades, but it remains to be a challenge in bioinformatics due to the increasing computation complexity. In this paper, AB off-lattice model is introduced to transforms the prediction task into a numerical optimization problem. Artificial Bee Colony algorithm (ABC) is an effective swarm intelligence alg...

A rtificial bee Colony algorithm (ABC) is a population based heuristic search technique used for optimization problems. ABC is a very effective optimization technique for continuous optimization problem. Crossover operators have a better exploration property so crossover operators are added to the ABC. This paper presents ABC with different types of real coded crossover operator and its applica...

The Improved Artificial Bee Colony (IABC) algorithm is a variant of the well-known Artificial Bee Colony (ABC) algorithm. In IABC, a new initialization approach and a new search mechanism were added to the ABC for avoiding local optimums and a better convergence speed. New parameters were added for the new search mechanism. Specified values of these newly added parameters have a direct impact o...

Data clustering is a method to group the data records that are similar to each other. In recent days, researcher show significant attention towards the use of swarm based optimization algorithms to improve the performance of clustering process. This Performance analysis concentrates on the effectiveness of five different algorithms with respect to various distances metrics to find the effective...

Artificial bee colony (ABC) algorithm is an optimization algorithm based on the intelligent foraging behavior of honeybee swarm. Optimal reactive power flow (ORPF) based on ABC algorithm to minimize active power loss in power systems is studied in this paper. The advantage of ABC algorithm is that it does not require these parameters, because it is very difficult to determine external parameter...