856 research outputs found
An Investigation Into the use of Swarm Intelligence for an Evolutionary Algorithm Optimisation; The Optimisation Performance of Differential Evolution Algorithm Coupled with Stochastic Diffusion Search
The integration of Swarm Intelligence (SI) algorithms and Evolutionary algorithms (EAs) might be one of the future approaches in the Evolutionary Computation (EC). This work narrates the early research on using Stochastic Diffusion Search (SDS) -- a swarm intelligence algorithm -- to empower the Differential Evolution (DE) -- an evolutionary algorithm -- over a set of optimisation problems. The results reported herein suggest that the powerful resource allocation mechanism deployed in SDS has the potential to improve the optimisation capability of the classical evolutionary algorithm used in this experiment. Different performance measures and statistical analyses were utilised to monitor the behaviour of the final coupled algorithm
An Investigation into the Merger of Stochastic Diffusion Search and Particle Swarm Optimisation
This study reports early research aimed at applying the powerful resource allocation mechanism deployed in Stochastic Diffusion Search (SDS) to the Particle Swarm Optimiser (PSO) metaheuristic, effectively merging the two swarm intelligence algorithms. The results reported herein suggest that the hybrid algorithm, exploiting information sharing between particles, has the potential to improve the optimisation capability of conventional PSOs
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The association between sleep patterns and obesity in older adults.
BackgroundReduced sleep duration has been increasingly reported to predict obesity. However, timing and regularity of sleep may also be important. In this study, the cross-sectional association between objectively measured sleep patterns and obesity was assessed in two large cohorts of older individuals.MethodsWrist actigraphy was performed in 3053 men (mean age: 76.4 years) participating in the Osteoporotic Fractures in Men Study and 2985 women (mean age: 83.5 years) participating in the Study of Osteoporotic Fractures. Timing and regularity of sleep patterns were assessed across nights, as well as daytime napping.ResultsGreater night-to-night variability in sleep duration and daytime napping were associated with obesity independent of mean nocturnal sleep duration in both men and women. Each 1āh increase in the standard deviation of nocturnal sleep duration increased the odds of obesity 1.63-fold (95% confidence interval: 1.31-2.02) among men and 1.22-fold (95% confidence interval: 1.01-1.47) among women. Each 1āh increase in napping increased the odds of obesity 1.23-fold (95% confidence interval: 1.12-1.37) in men and 1.29-fold (95% confidence interval: 1.17-1.41) in women. In contrast, associations between later sleep timing and night-to-night variability in sleep timing with obesity were less consistent.ConclusionsIn both older men and women, variability in nightly sleep duration and daytime napping were associated with obesity, independent of mean sleep duration. These findings suggest that characteristics of sleep beyond mean sleep duration may have a role in weight homeostasis, highlighting the complex relationship between sleep and metabolism
Bare bones particle swarms with jumps
Bare Bones PSO was proposed by Kennedy as a model of PSO dynamics. Dependence on velocity is replaced by sampling from a Gaussian distribution. Although Kennedyās original formulation is not competitive to standard PSO, the addition of a component-wise jumping mechanism, and a tuning of the standard deviation, can produce a comparable optimisation algorithm. This algorithm, Bare Bones with Jumps, exists in a variety of formulations. Two particular models are empirically examined in this paper and comparisons are made to canonical PSO and standard Bare Bones
The effect of Staphylococcus aureus carriage in late pregnancy on antibody levels to staphylococcal toxins in cord blood and breast milk.
We investigated the effect of carriage of Staphylococcus aureus in the later stages of pregnancy on levels of antibody specific to the S. aureus toxins, staphylococcal enterotoxin B (SEB), staphylococcal enterotoxin C (SEC) and toxic shock syndrome toxin-1 (TSST-1), in cord blood and breast milk and also explored the relationship between levels of antibody in antenatal serum and cord blood. Nasopharyngeal swabs and stool samples were collected on two occasions, from 96 women, during the last 6 weeks of pregnancy. Samples were cultured and S. aureus isolates were identified. Antenatal and cord blood samples from the same women and their infants were analysed for IgG antibody to SEB, SEC and TSST-1 by enzyme-linked immunosorbent assay. Breast milk samples were analysed for IgA antibody to the same toxins. We found that S. aureus carriage in pregnancy is common and exposure to a toxin-producing isolate boosts immunity. Over 89% of women and infants have some protective antibody to the toxins, and antitoxin IgG levels are higher in cord blood samples compared with antenatal samples. Levels of cord blood IgG and breast milk IgA specific for the staphylococcal toxins vary. Some infants lack protection and could be at risk of toxin-induced disease
An Investigation Into the use of Swarm Intelligence for an Evolutionary Algorithm Optimisation
Straight-sided beer and cider glasses to reduce alcohol sales for on-site consumption:A randomised crossover trial in bars
Information gain measure for structural discrimination of cellular automata configurations
Cellular automata (CA) are known for their capability in exhibiting interesting emergent behaviour and capacity to generate complex and often aesthetically appealing patterns through the local interaction of rules. Mean information gain has been suggested as a measure of discriminating structurally different two-dimensional (2D) patterns. This paper addresses quantitative evaluation of the complexity of CA generated configurations. In particular, we examine information gain as a spatial complexity measure for discriminating multi-state 2D CA generated configurations. This information-theoretic quantity, also known as conditional entropy, takes into account conditional and joint probabilities of cell states in a 2D plane. The effectiveness of the measure is shown in a series of experiments for multi-state 2D patterns generated by CA. The results of the experiments show that the measure is capable of distinguishing the structural characteristics including symmetries and randomness of 2D CA patterns
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