Artificial Bee Colony (ABC) is a distinguished optimization strategy that can resolve nonlinear and multifaceted problems. It is comparatively a straightforward and modern population based probabilistic approach for comprehensive optimization. In the vein of the other population based algorithms, ABC is moreover computationally classy due to its slow nature of search procedure. The solution exp...

Electronic nose technology is used in many areas, and frequently in the beverage industry for classification and quality-control purposes. In this study, four different aroma data (strawberry, lemon, cherry, and melon) were obtained using a MOSES II electronic nose for the purpose of fruit classification. To improve the performance of the classification, the training phase of the neural network...

Artificial Bee Colony (ABC) optimization algorithm is a swarm intelligence based nature inspired algorithm, which has been proved a competitive algorithm with some popular natureinspired algorithms. It is found that ABC is more efficient in exploration as compare to exploitation. With a motivation to balance exploration and exploitation capabilities of ABC, this paper presents an adaptive versi...

Gold price forecasting has been a hot issue in economics recently. In this work, wavelet neural network (WNN) combined with a novel artificial bee colony (ABC) algorithm is proposed for this gold price forecasting issue. In this improved algorithm, the conventional roulette selection strategy is discarded. Besides, the convergence statuses in a previous cycle of iteration are fully utilized as ...

The Artificial Bee Colony algorithm is an optimization algorithm than can be applied on the wide range of engineering problems. In this work, the standard ABC algorithm is extended by incorporating a cooperation approach and an algorithm called Split ABC (S-ABC) is developed. SABC aims at improving the performance of the standard ABC algorithm using benefits of cooperation as a social behaviour...

The artificial bee colony (ABC) algorithm is a swarm-based metaheuristic optimization technique, developed by inspiring foraging and dance behaviors of honey bee colonies. ABC consists of four phases named as initialization, employed bee, onlooker bee and scout bee. The employed bees try to improve their solution in employed bees phase. If an employed bee cannot improve self-solution in a certa...

The Optimal economic operation of their electric networks while considering the challenges of increasing fuel costs and increasing demand for electricity. The dynamic economic dispatch (DED) occupies important place in a power system’s operation and control. It aims to determine the optimal power outputs of on-line generating units in order to meet the load demand and reducing the fuel cost. Th...

Voting algorithms are extensively used to make decisions in fault tolerant systems where each redundant module gives inconsistent outputs. Popular voting algorithms include majority voting, weighted voting, and inexact majority voters. Each of these techniques suffers from scenarios where agreements do not exist for the given voter inputs. This has been successfully overcome in literature using...