265 resultados para Coupled-cluster methodology
Resumo:
Background The problem of silent multiple comparisons is one of the most difficult statistical problems faced by scientists. It is a particular problem for investigating a one-off cancer cluster reported to a health department because any one of hundreds, or possibly thousands, of neighbourhoods, schools, or workplaces could have reported a cluster, which could have been for any one of several types of cancer or any one of several time periods. Methods This paper contrasts the frequentist approach with a Bayesian approach for dealing with silent multiple comparisons in the context of a one-off cluster reported to a health department. Two published cluster investigations were re-analysed using the Dunn-Sidak method to adjust frequentist p-values and confidence intervals for silent multiple comparisons. Bayesian methods were based on the Gamma distribution. Results Bayesian analysis with non-informative priors produced results similar to the frequentist analysis, and suggested that both clusters represented a statistical excess. In the frequentist framework, the statistical significance of both clusters was extremely sensitive to the number of silent multiple comparisons, which can only ever be a subjective "guesstimate". The Bayesian approach is also subjective: whether there is an apparent statistical excess depends on the specified prior. Conclusion In cluster investigations, the frequentist approach is just as subjective as the Bayesian approach, but the Bayesian approach is less ambitious in that it treats the analysis as a synthesis of data and personal judgements (possibly poor ones), rather than objective reality. Bayesian analysis is (arguably) a useful tool to support complicated decision-making, because it makes the uncertainty associated with silent multiple comparisons explicit.
Resumo:
One of the main aims in artificial intelligent system is to develop robust and efficient optimisation methods for Multi-Objective (MO) and Multidisciplinary Design (MDO) design problems. The paper investigates two different optimisation techniques for multi-objective design optimisation problems. The first optimisation method is a Non-Dominated Sorting Genetic Algorithm II (NSGA-II). The second method combines the concepts of Nash-equilibrium and Pareto optimality with Multi-Objective Evolutionary Algorithms (MOEAs) which is denoted as Hybrid-Game. Numerical results from the two approaches are compared in terms of the quality of model and computational expense. The benefit of using the distributed hybrid game methodology for multi-objective design problems is demonstrated.
Resumo:
Baseline monitoring of groundwater quality aims to characterize the ambient condition of the resource and identify spatial or temporal trends. Sites comprising any baseline monitoring network must be selected to provide a representative perspective of groundwater quality across the aquifer(s) of interest. Hierarchical cluster analysis (HCA) has been used as a means of assessing the representativeness of a groundwater quality monitoring network, using example datasets from New Zealand. HCA allows New Zealand's national and regional monitoring networks to be compared in terms of the number of water-quality categories identified in each network, the hydrochemistry at the centroids of these water-quality categories, the proportions of monitoring sites assigned to each water-quality category, and the range of concentrations for each analyte within each water-quality category. Through the HCA approach, the National Groundwater Monitoring Programme (117 sites) is shown to provide a highly representative perspective of groundwater quality across New Zealand, relative to the amalgamated regional monitoring networks operated by 15 different regional authorities (680 sites have sufficient data for inclusion in HCA). This methodology can be applied to evaluate the representativeness of any subset of monitoring sites taken from a larger network.
Resumo:
What role can climatically appropriate subdivision design play in decreasing the use of energy required to cool premises by maximising access to natural ventilation? How can this design be achieved? The subdivision design stage is critical to urban and suburban sustainability outcomes, as significant changes after development are constrained by the configuration of the subdivision, and then by the construction of the dwellings. Existing Australian lot rating methodologies for energy efficiency, such as that by the Sustainable Energy Development Authority (SEDA), focus on reducing heating needs by increasing solar access, a key need in Australia’s temperate zone. A recent CRC CI project, Sustainable Subdivisions: Energy (Miller and Ambrose 2005) examined these guidelines to see if they could be adapted for use in subtropical South East Queensland (SEQ). Correlating the lot ratings with dwelling ratings, the project found that the SEDA guidelines would need to be modified for use to make allowance for natural ventilation. In SEQ, solar access for heating is less important than access to natural ventilation, and there is a need to reduce energy used to cool dwellings. In Queensland, the incidence of residential air-conditioning was predicted to reach 50 per cent by the end of 2005 (Mickel 2004). The CRC-CI, Sustainable Subdivisions: Ventilation Project (CRC-CI, in progress), aims to verify and quantify the role natural ventilation has in cooling residences in subtropical climates and develop a lot rating methodology for SEQ. This paper reviews results from an industry workshop that explored the current attitudes and methodologies used by a range of professionals involved in subdivision design and development in SEQ. Analysis of the workshop reveals that a key challenge for sustainability is that land development in subtropical SEQ is commonly a separate process from house design and siting. Finally, the paper highlights some of the issues that regulators and industry face in adopting a lot rating methodology for subdivisions offering improved ventilation access, including continuing disagreement between professionals over the desirability of rating tools.