In this study, segmentation of medical images using a fuzzy artificial bee colony algorithm with a cooling schedule is created. In this study, we embed ed fuzzy inference strategy into the artificial bee colony system to construct a segmentation system named Fuzzy Artificial Bee Colony System (FABCS). A conventional FCM algorithm did not utilize the spatial information in the image. We set a lo...

Artificial bee colony (ABC) algorithm is a swarm intelligence optimization algorithm inspired by the intelligent behavior of honey bees when searching for food sources. The various versions of the ABC algorithm have been widely used to solve continuous and discrete optimization problems in different fields. In this paper a new binary version of the ABC algorithm inspired by quantum computing, c...

Artificial Bee Colony (ABC) Algorithm is an optimization algorithm used to find out the global optima. In ABC, each bee stores the information of feasible solution or candidate solution and stochastically modifies this over time, based on the information provided by neighboring bees, it speculative modifies over time and based on the best solution found by the bee itself. . In this proposed wor...

In this paper, a novel hybrid optimization algorithm, which combines a firefly algorithms and Artificial Bee Colony algorithm (FFAABC), is proposed for solving the economic power dispatch (EPD) problem. The hybrid algorithm is structured with two stages. The first stage uses the search by firefly algorithm (FFA) and second stage is a search with Artificial Bee Colony algorithm (ABC). The hybrid...

Artificial Bee Colony (ABC) algorithm is a relatively new swarm intelligence algorithm which has shown a competitive performance with respect to other population-based algorithms. However, there are still some insufficiencies in ABC algorithm such as slow convergence and easily trapped in local optima. These drawbacks can be even more challenging when constraints are also involved. To address t...

A Modified Artificial Bee Colony (ABC) algorithm for Economic Dispatch (ED) problem has been proposed. The Artificial Bee Colony (ABC) algorithm which is inspired by the foraging behavior of honey bee swarm gives a solution procedure for solving economic dispatch problem. It provides solution more effective than Genetic Algorithm (GA), Particle Swarm Optimization (PSO) and Ant Colony Optimizati...

Artificial Bee Colony (ABC) algorithm is a Nature Inspired Algorithm (NIA) which based on intelligent food foraging behaviour of honey bee swarm. This paper introduces a local search strategy that enhances exploration competence of ABC and avoids the problem of stagnation. The proposed strategy introduces two new local search phases in original ABC. One just after onlooker bee phase and one aft...

The idea behind this work is to solve the Shortest Common Supersequence by using Artificial Bee Colony (ABC) Algorithm. This algorithm is considered as one of the newest nature-inspired swarm-based optimization algorithms and has a promising performance [6]. Shortest Common Supersequence is a classical problem in the field of strings and it is classified as NP-Hard problem [12]. Many algorithms...

Artificial Neural Networks (ANN) performance depends on network topology, activation function, behaviors of data, suitable synapse's values and learning algorithms. Researchers used different learning algorithms to train ANN for getting high performance. Artificial Bee Colony (ABC) algorithm is one of the latest successfully Swarm Intelligence based technique for training Multilayer Perceptron ...

in this paper proposes a fuzzy multi-objective hybrid genetic and bee colony optimization algorithm(ga-bco) to find the optimal restoration of loads of power distribution network under fault.restoration of distribution systems is a complex combinatorial optimization problem that should beefficiently restored in reasonable time. to improve the efficiency of restoration and facilitate theactivity...