A hybrid of ant colony optimization and artificial bee colony algorithm for probabilistic optimal placement and sizing of distributed energy resources

2015 ◽  
Vol 92 ◽  
pp. 149-161 ◽  
Author(s):  
M. Kefayat ◽  
A. Lashkar Ara ◽  
S.A. Nabavi Niaki
Keyword(s):  
Ant Colony Optimization ◽  
Artificial Bee Colony Algorithm ◽  
Artificial Bee Colony ◽  
Ant Colony ◽  
Energy Resources ◽  
Optimal Placement ◽  
Distributed Energy Resources ◽  
Distributed Energy ◽  
Bee Colony

scholarly journals Comparative assessment of the optical-electronic images segmentation quality by the ant colony optimization and the artificial bee colony

2021 ◽  
pp. 104-113
Author(s):  
Г.В. Худов ◽  
І.А. Хижняк
Keyword(s):  
Ant Colony Optimization ◽  
Swarm Intelligence ◽  
Artificial Bee Colony ◽  
Visual Assessment ◽  
Comparative Assessment ◽  
Ant Colony ◽  
Bee Colony ◽  
Segmentation Methods ◽  
Segmentation Quality

The article discusses the methods of swarm intelligence, namely, an improved method based on the ant colony optimization and the method of an artificial bee colony. The goal of the work is to carry out a comparative assessment of the optical-electronic images segmentation quality by the ant colony optimization and the artificial bee colony. Segmentation of tonal optical-electronic images was carried out using the proposed methods of swarm intelligence. The results of the segmentation of optical-electronic images obtained from the spacecraft are presented. A visual assessment of the quality of segmentation results was carried out using improved methods. The classical errors of the first and second kind of segmentation of optoelectronic images are calculated for the proposed methods of swarm intelligence and for known segmentation methods. The features of using each of the proposed methods of swarm intelligence are determined. The tasks for which it is better to use each of the proposed methods of swarm intelligence are determined.

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