The Ant Colony Optimization (ACO) technique was inspired by the ants' behavior throughout their exploration for food. In nature, ants wander randomly, seeking for food. After succeeding, they return to their nest. During their move, they lay down pheromone that forms an evaporating chemical path. Other ants that locate this trail, follow it and reinforce it, since they also lay down pheromone. ...

Creating accountable care organizations (ACOs) has been widely discussed as a strategy to control rapidly rising healthcare costs and improve quality of care; however, building an effective ACO is a complex process involving multiple stakeholders (payers, providers, patients) with their own interests. Also, implementation of an ACO is costly in terms of time and money. Immature design could cau...

The apical hook of dark-grown dicotyledonous seedlings is a protective structure resulting from an inhibition of cell elongation on the inner portion of the hook. This differential growth response is mediated by ethylene. Expression of the gene encoding 1-aminocyclopropane-1-carboxylate oxidase (ACO), the terminal enzyme in ethylene biosynthesis, is induced by ethylene via a positive feedback l...

This article proposes a novel MPPT algorithm based on the firefly and elite ant system-trained Elman neural network (FA-EAS-ElmanNN). First, position of fireflies is randomly initialized by (FA), meanwhile individuals with higher attractiveness degree value are selected as optimal solution. Second, extra pheromones artificially released to boost positive feedback effect convergence rate system ...

Ant colony optimization algorithm (ACO) is a heuristic bionic evolutionary system based on the population. The positive feedback of ACO helps to search the approximate optimal solution, however, it also makes it easier to get trapped in local optimal solution. In order to avoid prematurity and enhance its adaptability, this paper introduces chaos principle in ACO and proposes an adaptive chaoti...

Background: This paper presents parametric modelling of flexible plate structures using ant colony optimization (ACO). The global optimization technique of ACO is utilized to obtain a dynamic model of a flexible plate structure based on one-step-ahead (OSA) prediction. Objective: The structure is subjected to three different disturbance signal types, namely random, pseudo random binary sequence...

SI is a computational and collective behavioral metaphor that is used for solving problems. The problems can be solved by SI by taking ants, termites, bees and wasps as an example. The application of SI algorithm are ACO, PSO and ABC which have been already applied to solve real world optimization problems in engineering. ACO is a member of SI in which ACO is inspired by the behaviour of ant co...

The great uncertainty surrounding healthcare reform provides little incentive for action. However, as healthcare leaders wait for final rules and clarity about accountable care organizations (ACOs), inaction is the inappropriate response. Several central themes emerge from research about beginning the ACO process. Leaders should be able to understand and articulate ACO concepts. They should cha...

As a powerful formalism, Bayesian networks play an increasingly important role in the Uncertainty Field. This paper proposes a hybrid method to discover the knowledge represented in Bayesian networks. The hybridmethod combines dependency analysis, ant colony optimization (ACO), and the simulated annealing strategy. Firstly, the new method uses order-0 independence tests with a self-adjusting th...