A wide range of engineering design problems have been solved by the algorithms that simulates collective intelligence in swarms of birds or insects. The Artificial Bee Colony or ABC is one of the recent additions to the class of swarm intelligence based algorithms that mimics the foraging behavior of honey bees. ABC consists of three groups of bees namely employed, onlooker and scout bees. In A...

Transport of a wide variety of substrates, including xenobiotics, is one of the main functions attributed to human ATP-binding cassette (ABC) proteins. Overexpression of ABC genes is considered to be an important mechanism facilitating the development of chemoresistance. Relationships between the expression levels of ABC genes in tumor tissues and established clinicopathological features were e...

[Purpose] The present study aimed to investigate the discriminative validity of the short-form activities-specific balance confidence scale (ABC scale) in predicting falls, and its validity. [Subjects and Methods] 43 stroke survivors were identified as a group with a history of multiple falls (faller group) and a group without or with a history of one falls (non-faller group). The balance confi...

Best-so-far ABC is a modified version of the artificial bee colony (ABC) algorithm used for optimization tasks. This algorithm is one of the swarm intelligence (SI) algorithms proposed in recent literature, in which the results demonstrated that the best-so-far ABC can produce higher quality solutions with faster convergence than either the ordinary ABC or the current state-of-the-art ABC-based...

Logitboost is an influential boosting algorithm for classification. In this paper, we develop robust logitboost to provide an explicit formulation of tree-split criterion for building weak learners (regression trees) for logitboost. This formulation leads to a numerically stable implementation of logitboost. We then propose abc-logitboost for multi-class classification, by combining robust logi...

The atom-bond connectivity index—abbreviated ABC—has proven to describe the heat of formation of alkanes with an accuracy comparable to that of high-level ab initio and DFTmethods. Its physical interpretation in terms of quantumtheory, its generalization, and many of its mathematical properties have been reported. Here, a probabilistic interpretation of the generalized ABC index is provided. It...

The quest for a more powerful method for model evaluation has inspired Vrugt and Sadegh (2013) to introduce ‘‘likelihood-free’’ inference as vehicle for diagnostic model evaluation. This class of methods is also referred to as Approximate Bayesian Computation (ABC) and relaxes the need for a residualbased likelihood function in favor of one or multiple different summary statistics that exhibit ...

Artificial Bee Colony (ABC) algorithm is a relatively new swarm intelligence algorithm that has attracted great deal of attention from researchers in recent years with the advantage of less control parameters and strong global optimization ability. However, there is still an insufficiency in ABC regarding its solution search equation, which is good at exploration but poor at exploitation. This ...

parameter estimation of the nonlinear muskingum model is a highly nonlinear optimization problem. although various techniques have been applied to optimize the coefficients of the nonlinear muskingum flood routing models, but an efficient method for this purpose in the calibration process is still lacking. the accuracy of artificial bee colony (abc) algorithm is investigated in this paper to op...