BACKGROUND AND PURPOSE ABC/2 is still widely accepted for volume estimations in spontaneous intracerebral hemorrhage (ICH) despite known limitations, which potentially accounts for controversial outcome-study results. The aim of this study was to establish and validate an automatic segmentation algorithm, allowing for quick and accurate quantification of ICH. METHODS A segmentation algorithm ...

This paper presents the comparison results on the performance of the Artificial Bee Colony (ABC) algorithm for constrained optimization problems. The ABC algorithm has been firstly proposed for unconstrained optimization problems and showed that it has superior performance on these kind of problems. In this paper, the ABC algorithm has been extended for solving constrained optimization problems...

To further improve the performance of artificial bee colony algorithm (ABC), an improved ABC (IABC) algorithm is proposed for global optimization via employing orthogonal initialization method. Furthermore, to balance the exploration and exploitation abilities, a new search mechanism is also designed. The performance of this algorithm is verified by using 27 benchmark functions. And the compari...

This paper proposed a novel bionic selective visual attention mechanism to quickly select regions that contain salient objects to reduce calculations. Firstly, lateral inhibition filtering, inspired by the limulus' ommateum, is applied to filter low-frequency noises. After the filtering operation, we use Artificial Bee Colony (ABC) algorithm based selective visual attention mechanism to obtain ...

The artificial bee colony (ABC) algorithm is a swarm intelligence algorithm inspired by the intelligent foraging behavior of a honeybee swarm. In recent years, several ABC variants that modify some components of the original ABC algorithm have been proposed. Although there are some comparison studies in the literature, the individual contribution of each proposed modification is often unknown. ...

We develop the concept of ABC-Boost (Adaptive Base Class Boost) for multi-class classification and present ABC-MART, a concrete implementation of ABC-Boost. The original MART (Multiple Additive Regression Trees) algorithm has been very successful in large-scale applications. For binary classification, ABC-MART recovers MART. For multi-class classification, ABC-MART considerably improves MART, a...

A proper balance between global explorations and local exploitations is often considered necessary for complex, high dimensional optimization problems to avoid local optima and to find a good near optimum solution with sufficient convergence speed. This paper introduces Artificial Bee Colony algorithm with Adaptive eXplorations and eXploitations (ABC-AX), a novel algorithm that improves over th...

This paper presents a new approach for solving the Combined Heat and Economic Dispatch (CHPED) problem using an artificial bee colony algorithm (ABC). Artificial Bee Colony algorithm (ABC) is inspired by the foraging behavior of honey bee swarm, is a biological inspired optimization. It shows more effective than the other optimization algorithms. The performance of the proposed algorithm ABC is...

Artificial bee colony algorithm (ABC) is an efficient and popular evolutionary (EAs), which has been attracted wide attention by researchers, improved ABC with various characteristics (ABCs) have proposed. It widely acknowledged that the search operator core element in performance of ABC. However, generally designed operators ABCs are rotation-variable processes dependent mainly on natural coor...

Job Scheduling plays an important role for efficient utilization of grid resources available across different domains and geographical zones. Scheduling of jobs is challenging and NPcomplete. Evolutionary / Swarm Intelligence algorithms have been extensively used to address the NP problem in grid scheduling. Artificial Bee Colony (ABC) has been proposed for optimization problems based on foragi...