933 resultados para Power Series Distribution


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The stochastic nature of oil price fluctuations is investigated over a twelve-year period, borrowing feedback from an existing database (USA Energy Information Administration database, available online). We evaluate the scaling exponents of the fluctuations by employing different statistical analysis methods, namely rescaled range analysis (R/S), scale windowed variance analysis (SWV) and the generalized Hurst exponent (GH) method. Relying on the scaling exponents obtained, we apply a rescaling procedure to investigate the complex characteristics of the probability density functions (PDFs) dominating oil price fluctuations. It is found that PDFs exhibit scale invariance, and in fact collapse onto a single curve when increments are measured over microscales (typically less than 30 days). The time evolution of the distributions is well fitted by a Levy-type stable distribution. The relevance of a Levy distribution is made plausible by a simple model of nonlinear transfer. Our results also exhibit a degree of multifractality as the PDFs change and converge toward to a Gaussian distribution at the macroscales.

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The validity of load estimates from intermittent, instantaneous grab sampling is dependent on adequate spatial coverage by monitoring networks and a sampling frequency that re?ects the variability in the system under study. Catchments with a ?ashy hydrology due to surface runoff pose a particular challenge as intense short duration rainfall events may account for a signi?cant portion of the total diffuse transfer of pollution from soil to water in any hydrological year. This can also be exacerbated by the presence of strong background pollution signals from point sources during low flows. In this paper, a range of sampling methodologies and load estimation techniques are applied to phosphorus data from such a surface water dominated river system, instrumented at three sub-catchments (ranging from 3 to 5 km2 in area) with near-continuous monitoring stations. Systematic and Monte Carlo approaches were applied to simulate grab sampling using multiple strategies and to calculate an estimated load, Le based on established load estimation methods. Comparison with the actual load, Lt, revealed signi?cant average underestimation, of up to 60%, and high variability for all feasible sampling approaches. Further analysis of the time series provides an insight into these observations; revealing peak frequencies and power-law scaling in the distributions of P concentration, discharge and load associated with surface runoff and background transfers. Results indicate that only near-continuous monitoring that re?ects the rapid temporal changes in these river systems is adequate for comparative monitoring and evaluation purposes. While the implications of this analysis may be more tenable to small scale ?ashy systems, this represents an appropriate scale in terms of evaluating catchment mitigation strategies such as agri-environmental policies for managing diffuse P transfers in complex landscapes.

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We present an updated cumulative size distribution (CSD) for Jupiter Family comet (JFC) nuclei, including a rigorous assessment of the uncertainty on the slope of the CSD. The CSD is expressed as a power law, N(>rN) ?r-qN, where rN is the radius of the nuclei and q is the slope. We include a large number of optical observations published by us and others since the comprehensive review in the Comets II book, and make use of an improved fitting method. We assess the uncertainty on the CSD due to all of the unknowns and uncertainties involved (photometric uncertainty, assumed phase function, albedo and shape of the nucleus) by means of Monte Carlo simulations. In order to do this we also briefly review the current measurements of these parameters for JFCs. Our final CSD has a slope q= 1.92 ± 0.20 for nuclei with radius rN= 1.25 km.

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A critical load x(c) is introduced into the fiber-bundle model with local load-sharing. The critical load is defined as the average load per fiber that causes the final complete failure. It is shown that x(c) --> 0 when the size of the system N --> infinity. A power law for the burst-size distribution, D(DELTA) is-proportional-to DELTA(-xi) is approximately correct. The exponent xi is not universal, since it depends on the strength distribution as well as the size of the system.

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We present the discovery of two ultraluminous supernovae (SNe) at z approximate to 0.9 with the Pan-STARRS1 Medium Deep Survey. These SNe, PS1-10ky and PS1-10awh, are among the most luminous SNe ever discovered, comparable to the unusual transients SN 2005ap and SCP 06F6. Like SN 2005ap and SCP 06F6, they show characteristic high luminosities (M-bol approximate to -22.5 mag), blue spectra with a few broad absorption lines, and no evidence for H or He. We have constructed a full multi-color light curve sensitive to the peak of the spectral energy distribution in the rest-frame ultraviolet, and we have obtained time series spectroscopy for these SNe. Given the similarities between the SNe, we combine their light curves to estimate a total radiated energy over the course of explosion of (0.9-1.4) x 10(51) erg. We find photospheric velocities of 12,000-19,000 km s(-1) with no evidence for deceleration measured across similar to 3 rest-frame weeks around light curve peak, consistent with the expansion of an optically thick massive shell of material. We show that, consistent with findings for other ultraluminous SNe in this class, radioactive decay is not sufficient to power PS1-10ky, and we discuss two plausible origins for these events: the initial spin-down of a newborn magnetar in a core-collapse SN, or SN shock breakout from the dense circumstellar wind surrounding a Wolf-Rayet star.

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The ideal free distribution model which relates the spatial distribution of mobile consumers to that of their resource is shown to be a limiting case of a more general model which we develop using simple concepts of diffusion. We show how the ideal free distribution model can be derived from a more general model and extended by incorporating simple models of social influences on predator spacing. First, a free distribution model based on patch switching rules, with a power-law interference term, which represents instantaneous biased diffusion is derived. A social bias term is then introduced to represent the effect of predator aggregation on predator fitness, separate from any effects which act through intake rate. The social bias term is expanded to express an optimum spacing for predators and example solutions of the resulting biased diffusion models are shown. The model demonstrates how an empirical interference coefficient, derived from measurements of predator and prey densities, may include factors expressing the impact of social spacing behaviour on fitness. We conclude that empirical values of log predator/log prey ratio may contain information about more than the relationship between consumer and resource densities. Unlike many previous models, the model shown here applies to conditions without continual input. (C) 1997 Academic Press Limited.</p>

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Here we present a series of six maps illustrating the distribution of end moraines in Far NE Russia. The maps are the first to systematically document the distribution of moraines across this region from the Verkhoyansk Mountains at the westernmost limit of our study area to the Chukchi Peninsula in the NE and to Kamchatka in the south, covering almost 4 million km2. Moraines were identified and mapped from analysis of satellite images and digital elevation model data. A total of 2173 moraines are identified, and we highlight some 197 more speculative features (perhaps moraines) that require further investigation. The distribution of moraines indicates that much of the region, now largely ice-free, was formerly occupied by glaciers centred upon the region’s uplands and that glacier outlets were typically < 200 km in length. The maps demonstrate the usefulness of remote sensing to derive an improved understanding of the glacial history of this vast and isolated region, and we present them to stimulate further work and act as a systematic framework for targeted geochronometric dating.

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The study of interrelationships between soil structure and its functional properties is complicated by the fact that the quantitative description of soil structure is challenging. Soil scientists have tackled this challenge by taking advantage of approaches such as fractal geometry, which describes soil architectural complexity through a scaling exponent (D) relating mass and numbers of particles/aggregates to particle/aggregate size. Typically, soil biologists use empirical indices such as mean weight diameters (MWD) and percent of water stable aggregates (WSA), or the entire size distribution, and they have successfully related these indices to key soil features such as C and N dynamics and biological promoters of soil structure. Here, we focused on D, WSA and MWD and we tested whether: D estimated by the exponent of the power law of number-size distributions is a good and consistent correlate of MWD and WSA; D carries information that differs from MWD and WSA; the fraction of variation in D that is uncorrelated with MWD and WSA is related to soil chemical and biological properties that are thought to establish interdependence with soil structure (e.g., organic C, N, arbuscular mycorrhizal fungi). We analysed observational data from a broad scale field study and results from a greenhouse experiment where arbuscular mycorrhizal fungi (AMF) and collembola altered soil structure. We were able to develop empirical models that account for a highly significant and large portion of the correlation observed between WSA and MWD but we did not uncover the mechanisms that underlie this correlation. We conclude that most of the covariance between D and soil biotic (AMF, plant roots) and abiotic (C. N) properties can be accounted for by WSA and MWD. This result implies that the ecological effects of the fragmentation properties described by D and generally discussed under the framework of fractal models can be interpreted under the intuitive perspective of simpler indices and we suggest that the biotic components mostly impacted the largest size fractions, which dominate MWD, WSA and the scaling exponent ruling number-size distributions. (C) 2010 Elsevier Ltd. All rights reserved.

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A micro-grid is an autonomous system which can be operated and connected to an external system or isolated with the help of energy storage systems (ESSs). While the daily output of distributed generators (DGs) strongly depends on the temporal distribution of natural resources such as wind and solar, unregulated electric vehicle (EV) charging demand will deteriorate the imbalance between the daily load and generation curves. In this paper, a statistical model is presented to describe daily EV charging/discharging behaviour. An optimisation problem is proposed to obtain economic operation for the micro-grid based on this model. In day-ahead scheduling, with estimated information of power generation and load demand, optimal charging/discharging of EVs during 24 hours is obtained. A series of numerical optimization solutions in different scenarios is achieved by serial quadratic programming. The results show that optimal charging/discharging of EVs, a daily load curve can better track the generation curve and the network loss and required ESS capacity are both decreased. The paper also demonstrates cost benefits for EVs and operators.

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This paper proposes a calculation method to determine power system response during small load perturbations or minor disturbances. The method establishes the initial value of active power transient using traditional reduction technique on admittance matrix, which incorporates voltage variations in the determination. The method examines active power distribution among generators when several loads simultaneously change, and verifies that the superposition principle is applicable for this scenario. The theoretical derivation provided in the paper is validated by numerical simulations using a 3-generator 9-bus benchmark model. The results indicate that the inclusion of voltage variation renders an independent and precise measure of active power response during transient conditions.