The bee swarm algorithm is adapted for the solution of the problem of deconvolution of complex spectral contours into components. Comparison of biological concepts relating to the behaviour of bees in a colony and mathematical concepts relating to the quality of the obtained solutions is carried out (mean square error, random solutions in the each iteration). Model experiments, which have been realized on the example of a signal representing a sum of three Lorentz contours of various intensity and half-width, confirm the efficiency of the offered approach
ABC algorithm or also called Artificial Bee Colony Algorithm is one of the popular algorithms of usi...
Thetheory and design of adaptive finite impulse response (FIR) filters are welldeveloped and widely ...
This chapter explores the use of the Artificial Bee Colony (ABC) algorithm to compute pixel classifi...
The bee swarm algorithm is adapted for the solution of the problem of deconvolution of complex spect...
Artificial bee colony (ABC) algorithm is a swarm intelligence algorithm, which simulates the foragin...
© Published under licence by IOP Publishing Ltd. The approach based on the stochastic algorithm of p...
Combinatorial optimization problems are problems that have a large number of discrete solutions and ...
© Published under licence by IOP Publishing Ltd. An application of the artificial immune system meth...
The minimum cross entropy thresholding (MCET) has been widely applied in image processing. In this...
Swarm intelligence is a research field that models the collective intelligence in swarms of insects ...
Artificial Bee Colony (ABC) algorithm which is one of the most recently introduced optimization algo...
Based on the metaphor of the foraging mechanism of honey bee swarms as well as on available works, a...
Classical methods often face great difficulties in solving image processing problems in images conta...
Artificial Bee Colony (ABC) algorithm is one of the most recently introduced swarm-based algorithms....
We demonstrate the derivation of a powerful and simple, as well as robust and flexible algorithm for...
ABC algorithm or also called Artificial Bee Colony Algorithm is one of the popular algorithms of usi...
Thetheory and design of adaptive finite impulse response (FIR) filters are welldeveloped and widely ...
This chapter explores the use of the Artificial Bee Colony (ABC) algorithm to compute pixel classifi...
The bee swarm algorithm is adapted for the solution of the problem of deconvolution of complex spect...
Artificial bee colony (ABC) algorithm is a swarm intelligence algorithm, which simulates the foragin...
© Published under licence by IOP Publishing Ltd. The approach based on the stochastic algorithm of p...
Combinatorial optimization problems are problems that have a large number of discrete solutions and ...
© Published under licence by IOP Publishing Ltd. An application of the artificial immune system meth...
The minimum cross entropy thresholding (MCET) has been widely applied in image processing. In this...
Swarm intelligence is a research field that models the collective intelligence in swarms of insects ...
Artificial Bee Colony (ABC) algorithm which is one of the most recently introduced optimization algo...
Based on the metaphor of the foraging mechanism of honey bee swarms as well as on available works, a...
Classical methods often face great difficulties in solving image processing problems in images conta...
Artificial Bee Colony (ABC) algorithm is one of the most recently introduced swarm-based algorithms....
We demonstrate the derivation of a powerful and simple, as well as robust and flexible algorithm for...
ABC algorithm or also called Artificial Bee Colony Algorithm is one of the popular algorithms of usi...
Thetheory and design of adaptive finite impulse response (FIR) filters are welldeveloped and widely ...
This chapter explores the use of the Artificial Bee Colony (ABC) algorithm to compute pixel classifi...