21 resultados para Uncertainty in generation

em University of Queensland eSpace - Australia


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1. Management decisions regarding invasive plants often have to be made quickly and in the face of fragmentary knowledge of their population dynamics. However, recommendations are commonly made on the basis of only a restricted set of parameters. Without addressing uncertainty and variability in model parameters we risk ineffective management, resulting in wasted resources and an escalating problem if early chances to control spread are missed. 2. Using available data for Pinus nigra in ungrazed and grazed grassland and shrubland in New Zealand, we parameterized a stage-structured spread model to calculate invasion wave speed, population growth rate and their sensitivities and elasticities to population parameters. Uncertainty distributions of parameters were used with the model to generate confidence intervals (CI) about the model predictions. 3. Ungrazed grassland environments were most vulnerable to invasion and the highest elasticities and sensitivities of invasion speed were to long-distance dispersal parameters. However, there was overlap between the elasticity and sensitivity CI on juvenile survival, seedling establishment and long-distance dispersal parameters, indicating overlap in their effects on invasion speed. 4. While elasticity of invasion speed to long-distance dispersal was highest in shrubland environments, there was overlap with the CI of elasticity to juvenile survival. In shrubland invasion speed was most sensitive to the probability of establishment, especially when establishment was low. In the grazed environment elasticity and sensitivity of invasion speed to the severity of grazing were consistently highest. Management recommendations based on elasticities and sensitivities depend on the vulnerability of the habitat. 5. Synthesis and applications. Despite considerable uncertainty in demography and dispersal, robust management recommendations emerged from the model. Proportional or absolute reductions in long-distance dispersal, juvenile survival and seedling establishment parameters have the potential to reduce wave speed substantially. Plantations of wind-dispersed invasive conifers should not be sited on exposed sites vulnerable to long-distance dispersal events, and trees in these sites should be removed. Invasion speed can also be reduced by removing seedlings, establishing competitive shrubs and grazing. Incorporating uncertainty into the modelling process increases our confidence in the wide applicability of the management strategies recommended here.

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Ecosystems and the species and communities within them are highly complex systems that defy predictions with any degree of certainty. Managing and conserving these systems in the face of uncertainty remains a daunting challenge, particularly with respect to developing networks of marine reserves. Here we review several modelling frameworks that explicitly acknowledge and incorporate uncertainty, and then use these methods to evaluate reserve spacing rules given increasing levels of uncertainty about larval dispersal distances. Our approach finds similar spacing rules as have been proposed elsewhere - roughly 20-200 km - but highlights several advantages provided by uncertainty modelling over more traditional approaches to developing these estimates. In particular, we argue that uncertainty modelling can allow for (1) an evaluation of the risk associated with any decision based on the assumed uncertainty; (2) a method for quantifying the costs and benefits of reducing uncertainty; and (3) a useful tool for communicating to stakeholders the challenges in managing highly uncertain systems. We also argue that incorporating rather than avoiding uncertainty will increase the chances of successfully achieving conservation and management goals.

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Although uncertainty is a fundamental human experience, professionals in the career field have largely overlooked the role that it plays in people's careers. The changed nature of careers has resulted in people experiencing increased uncertainty in their career that is beyond the uncertainty experienced in their job. The author explores the role of uncertainty in people's experience of their careers and examines the implications for career counseling theory and practice. A review of the career theory and career counseling literature indicates that although contemporary approaches have been offered to respond to the changed nature of career, none of the approaches have identified uncertainty as a core part of individuals' experience of their career. The broader literature on uncertainty is then reviewed at the societal, organizational, and individual levels.

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Participants in contingent valuation studies may be uncertain about a number of aspects of the policy and survey context. The uncertainty management model of fairness judgments states that individuals will evaluate a policy in terms of its fairness when they do not know whether they can trust the relevant managing authority or experience uncertainty due to insufficient knowledge of the general issues surrounding the environmental policy. Similarly, some researchers have suggested that, not knowing how to answer WTP questions, participants convey their general attitudes toward the public good rather than report well-defined economic preferences. These contentions were investigated in a sample of 840 residents in four urban catchments across Australia who were interviewed about their WTP for stormwater pollution abatement. Four sources of uncertainty were measured: amount of prior issue-related thought, trustworthiness of the water authority, insufficient scenario information, and WTP response uncertainty. A logistic regression model was estimated in each subsample to test the main effects of the uncertainty sources on WTP as well as their interaction with fairness and proenvironmental attitudes. Results indicated support for the uncertainty management model in only one of the four samples. Similarly, proenvironmental attitudes interacted rarely with uncertainty to a significant level, and in ways that were more complex than hypothesised. It was concluded that uncertain individuals were generally not more likely than other participants to draw on either fairness evaluations or proenvironmental attitudes when making decisions about paying for stormwater pollution abatement.

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Stochastic simulation is a recognised tool for quantifying the spatial distribution of geological uncertainty and risk in earth science and engineering. Metals mining is an area where simulation technologies are extensively used; however, applications in the coal mining industry have been limited. This is particularly due to the lack of a systematic demonstration illustrating the capabilities these techniques have in problem solving in coal mining. This paper presents two broad and technically distinct areas of applications in coal mining. The first deals with the use of simulation in the quantification of uncertainty in coal seam attributes and risk assessment to assist coal resource classification, and drillhole spacing optimisation to meet pre-specified risk levels at a required confidence. The second application presents the use of stochastic simulation in the quantification of fault risk, an area of particular interest to underground coal mining, and documents the performance of the approach. The examples presented demonstrate the advantages and positive contribution stochastic simulation approaches bring to the coal mining industry

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A long-term planning method for the electricity market is to simulate market operation into the future. Outputs from market simulation include indicators for transmission augmentation and new generation investment. A key input to market simulations is demand forecasts. For market simulation purposes, regional demand forecasts for each half-hour interval of the forecasting horizon are required, and they must accurately represent realistic demand profiles and interregional demand relationships. In this paper, a demand model is developed to accurately model these relationships. The effects of uncertainty in weather patterns and inherent correlations between regional demands on market simulation results are presented. This work signifies the advantages of probabilistic modeling of demand levels when making market-based planning decisions.

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Pattern discovery in temporal event sequences is of great importance in many application domains, such as telecommunication network fault analysis. In reality, not every type of event has an accurate timestamp. Some of them, defined as inaccurate events may only have an interval as possible time of occurrence. The existence of inaccurate events may cause uncertainty in event ordering. The traditional support model cannot deal with this uncertainty, which would cause some interesting patterns to be missing. A new concept, precise support, is introduced to evaluate the probability of a pattern contained in a sequence. Based on this new metric, we define the uncertainty model and present an algorithm to discover interesting patterns in the sequence database that has one type of inaccurate event. In our model, the number of types of inaccurate events can be extended to k readily, however, at a cost of increasing computational complexity.

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Objective: To evaluate whether the introduction of a national, co-ordinated screening program using the faecal occult blood test represents 'value-for-money' from the perspective of the Australian Government as third-party funder. Methods: The annual equivalent costs and consequences of a biennial screening program in 'steady-state' operation were estimated for the Australian population using 1996 as the reference year. Disability-adjusted life years (DALYs) and the years of life lost (YLLs) averted, and the health service costs were modelled, based on the epidemiology and the costs of colorectal cancer in Australia together with the mortality reduction achieved in randomised controlled trials. Uncertainty in the model was examined using Monte Carlo simulation methods. Results: We estimate a minimum or 'base program' of screening those aged 55 to 69 years could avert 250 deaths per annum (95% uncertainty interval 99-400), at a gross cost of $A55 million (95% UI $A46 million to $A96 million) and a gross incremental cost-effectiveness ratio of $A17,000/DALY (95% UI $A13,000/DALY to $A52,000/DALY). Extending the program to include 70 to 74-year-olds is a more effective option (cheaper and higher health gain) than including the 50 to 54-year-olds. Conclusions: The findings of this study support the case for a national program directed at the 55 to 69-year-old age group with extension to 70 to 74-year-olds if there are sufficient resources. The pilot tests recently announced in Australia provide an important opportunity to consider the age range for screening and the sources of uncertainty, identified in the modelled evaluation, to assist decisions on implementing a full national program.

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The dependence of the magnetoresistance of quasi-one-dimensional metals on the direction of the magnetic field show dips when the field is tilted at the so-called magic angles determined by the structural dimensions of the materials. There is currently no accepted explanation for these magic-angle effects. We present a possible explanation. Our model is based on the assumption that, the intralayer transport in the second most conducting direction has a small contribution from incoherent electrons. This incoherence is modeled by a small uncertainty in momentum perpendicular to the most conducting (chain) direction. Our model predicts the magic angles seen in interlayer transport measurements for different orientations of the field. We compare our results to predictions by other models and to experiment.

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We present a definition of increasing uncertainty, in which an elementary increase in the uncertainty of any act corresponds to the addition of an 'elementary bet' that increases consumption by a fixed amount in (relatively) 'good' states and decreases consumption by a fixed (and possibly different) amount in (relatively) 'bad' states. This definition naturally gives rise to a dual definition of comparative aversion to uncertainty. We characterize this definition for a popular class of generalized models of choice under uncertainty.

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Adsorption of supercritical fluids is increasingly carried out to determine the micropore size distribution. This is largely motivated by the advances in the use of supercritical adsorption in high energy applications, such as hydrogen and methane storage in porous media. Experimental data are reported as mass excess versus pressure, and when these data are matched against the theoretical mass excess, significant errors could occur if the void volume used in the calculation of the experimental mass excess is incorrectly determined [Malbrunot, P.; Vidal, D.; Vermesse, J.; Chahine, R.; Bose, T. K. Langmuir 1997, 13, 539]. 1 The incorrect value for the void volume leads to a wrong description of the maximum in the plot of mass excess versus pressure as well as the part of the isotherm over the pressure region where the isotherm is decreasing. Because of this uncertainty in the maximum and the decreasing part of the isotherm, we propose a new method in which the problems associated with this are completely avoided. Our method involves only the relationship between the amount that is introduced into the adsorption cell and the equilibrium pressure. This information of direct experimental data has two distinct advantages. The first is that the data is the raw data without any manipulation (i.e., involving further calculations), and the second one is that this relationship always monotonically increases with pressure. We will illustrate this new method with the adsorption data of methane in a commercial sample of activated carbon.