In this paper we propose an improved self-adaptive artificial bee colony algorithm (IS-ABC) for accurate numerical function optimisation. A modified self-adaptive mechanism based on 1/5th success rule is embedded in the structure of ABC to enhance the speed of the algorithm. The proposed algorithm has been tested on various numerical benchmark functions including the non-traditional functions p...

One of the most important phases of pre-processing is Feature selection, which can improve the predictive accuracy of steganalysis. In this study, we have presented a novel feature selection-based method to image steganalysis for detecting stego images from cover images based on artificial bee colony (ISBC). The experiments show that the proposed method is easy to be employed for steganalysis p...

Particle swarm optimization (PSO) and artificial bee colony (ABC) are new optimization methods that have attracted increasing research interests because of its simplicity and efficiency. However, when being applied to high-dimensional optimization problems, PSO algorithm may be trapped in the local optimal because of its low global exploration efficiency; ABC algorithm has slower convergence sp...

In this paper we investigate iterative logic synthesis processes. A well known academic logic synthesis tool ABC incorporates many synthesis algorithms and scripts which may be run iteratively to possibly improve the result. When iterating the synthesis process, the whole network is considered. We propose an alternative approach to iterative synthesis – only properly selected parts of the circu...

Digital filters can be broadly classified into two groups: recursive (infinite impulse response (IIR)) and non-recursive (finite impulse response (FIR)). An IIR filter can provide a much better performance than the FIR filter having the same number of coefficients. However, IIR filters might have a multi-modal error surface. Therefore, a reliable design method proposed for IIR filters must be b...

A rtificial bee Colony algorithm (ABC) is a population based heuristic search technique used for optimization problems. ABC is a very effective optimization technique for continuous optimization problem. Crossover operators have a better exploration property so crossover operators are added to the ABC. This paper presents ABC with different types of real coded crossover operator and its applica...

White balancing is an important step to correct the color value of pixels under varied color temperature of illuminations for color image processing. We have to do the image preprocessing of the color cast, and use the zone system with the white balance to solve this problem. Then we implement the biological intelligent algorithms for images segmentation, such as Artificial Bee Colony (ABC) and...

Resource constrained project scheduling (RCPSP) is one of the most crucial problems in project problem. The aim of RCPSP, which is NP-hard, is to minimize the project duration. Sometimes the activity durations are not known in advance and are random variables. These problems are called stochastic resource constrained project scheduling problems or stochastic RCPSP. Various algorithms such as ge...

An improved method for adaptive noise canceller (ANC) is proposed for noisy speech signal in case of random noise. In this approach, ANC is implemented through four different metaheuristic techniques. A comparative study of the performance of various metaheuristic techniques such as Particle Swarm Optimization (PSO), Artificial Bee Colony (ABC), Cuckoo Search (CS) and Modified Cuckoo Search (MC...

To date, exploring an efficient method for optimizing Least Squares Support Vector Machines (LSSVM) hyperparameters has been an enthusiastic research area among academic researchers. LSSVM is a practical machine learning approach that has been broadly utilized in numerous fields. To guarantee its convincing performance, it is crucial to select an appropriate technique in order to obtain the opt...