Kernel fuzzy C-mean clustering (KFCM) algorithm is effective for high-dimensional data, but this algorithm has some defects of sensitivity to initialization and local optima. Artificial Bee Colony (ABC) algorithm is based on intelligent behaviors of honey bee swarm. It has the properties of strong global optimization and fast convergence speed. A KFCM algorithm based on improved ABC is proposed...

The integration of non-orthogonal multiple access (NOMA) technology and cognitive radio networks (CRNs) promises to enhance the spectrum utilization efficiency 5G beyond-5G (B5G) mobile communication systems. In this article, a NOMA-based spectrum-sharing scheme is proposed for dual-hop CRNs in which primary transmitter separated by long distance from receiver communicates via CRN. scenario, we...

Artificial bee colony (ABC) algorithm invented recently by Karaboga is a biological-inspired optimization algorithm, which has been shown to be competitive with some conventional biological-inspired algorithms, such as genetic algorithm (GA), differential evolution (DE) and particle swarm optimization (PSO). However, there is still an insufficiency in ABC algorithm regarding its solution search...

In this study, diagnosis of diabetes disease, which is one of the most important diseases, is conducted with artificial intelligence techniques. We have proposed a novel Artificial Bee Colony (ABC) algorithm in which a mutation operator is added to an Artificial Bee Colony for improving its performance. When the current best solution cannot be updated, a blended crossover operator (BLX-α) of ge...

The minimum cross entropy thresholding (MCET) has been widely applied in image processing. In this paper, a new multilevel MCET algorithm based on the artificial bee colony (ABC) algorithm is proposed. The proposed thresholding algorithm is called ABC-based MCET algorithm. Four different methods including the exhaustive search, the honey bee mating optimization (HBMO), the particle swarm optimi...

Most reservoirs offer a mean of managing and regulating the downstream water flow and demands over time and space. It is a challenging task for the reservoir operator to evaluate the trade-off during drought and heavy rainfall season. This study proposes a review on the application of different computational intelligent models, especially the Artificial Bee Colony (ABC) approach in reservoir in...

Artificial Bee Colony (ABC) algorithm is a Nature Inspired Algorithm (NIA) which based in intelligent food foraging behaviour of honey bee swarm. ABC outperformed over other NIAs and other local search heuristics when tested for benchmark functions as well as factual world problems but occasionally it shows premature convergence and stagnation due to lack of balance between exploration and expl...

The Artificial Bee Colony (ABC) algorithm is a population based meta-heuristic algorithm proposed by Karaboga in 2005 inspired by the intelligent foraging behaviour of honey bees. ABC as a powerful technique is easy to implement, has fewer control parameters, and could easily be integrated with other meta-heuristic algorithms due to which it continues to attract the interest of researchers from...

Artificial bee colony (ABC) algorithm is a swarm intelligence optimization algorithm inspired by the intelligent behavior of honey bees when searching for food sources. Various versions of the ABC algorithm have been widely used to solve continuous and discrete optimization problems in different fields. In this paper, a new binary version of the ABC algorithm inspired by quantum computing calle...

Data clustering is a method to group the data records that are similar to each other. In recent days, researcher show significant attention towards the use of swarm based optimization algorithms to improve the performance of clustering process. This Performance analysis concentrates on the effectiveness of five different algorithms with respect to various distances metrics to find the effective...