in this paper, a robust integral of the sign error (rise) feedback controller is designed for a rigid-link electrically driven (rled) robot manipulator actuated by direct current dc motor in presence of parametric uncertainties and additive disturbances. rise feedback with implicitly learning capability is a continuous control method based on the lyapunov stability analysis to compensate an add...

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...

A robust image watermarking scheme based on singular value decomposition (SVD) and discrete wavelet transform (DWT) with Artificial Bee Colony Algorithm is proposed in this paper. Previous SVD based watermarking algorithms have a major drawback of false positive detection. For solving this problem, the similarity measure of U matrix for ownership is checked. To achieve the highest possible robu...

In this paper an improved version of the Artificial Bee Colony (ABC) algorithm adjusted for constrained optimization problems is presented. It has been implemented and tested on several engineering benchmarks which contain discrete and continuous variables. Our results were compared to the results obtained by Simple Constrained Particle Swarm optimization algorithm (SiC-PSO) which showed a very...

In the process of material composition detection, image analysis is an inevitable problem. Multilevel thresholding based on the OTSU method is one of the most popular image segmentation techniques. The increase of the number of thresholds increases with the exponential increase in computing time. In order to overcome this problem, this paper proposes an artificial bee colony algorithm with a tw...

Artificial Bee Colony (ABC) algorithm is an optimization algorithm based on the intelligent behavior of honey bee swarm. The ABC algorithm was developed to solve optimizing numerical problems and revealed premising results in processing time and solution quality. In ABC, a colony of artificial bees search for rich artificial food sources; the optimizing numerical problems are converted to the p...

An enhanced Artificial Bee Colony (ABC) optimization algorithm, which is called the Interactive Artificial Bee Colony (IABC) optimization, for numerical optimization problems, is proposed in this paper. The onlooker bee is designed to move straightly to the picked coordinate indicated by the employed bee and evaluates the fitness values near it in the original Artificial Bee Colony algorithm in...

Artificial Bee Colony (ABC) optimization algorithm is one of the recent population based probabilistic approach developed for global optimization. ABC is simple and has been showed significant improvement over other Nature Inspired Algorithms (NIAs) when tested over some standard benchmark functions and for some complex real world optimization problems. Memetic Algorithms also become one of the...

As a relatively new global optimization technique, artificial bee colony (ABC) algorithm becomes popular in recent years for its simplicity and effectiveness. However, there is still an inefficiency in ABC regarding its solution search equation, which is good at exploration but poor at exploitation. To overcome this drawback, a Gaussian barebones ABC is proposed, where a new search equation is ...