972 resultados para Forecast densities


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Many statistical forecast systems are available to interested users. In order to be useful for decision-making, these systems must be based on evidence of underlying mechanisms. Once causal connections between the mechanism and their statistical manifestation have been firmly established, the forecasts must also provide some quantitative evidence of `quality’. However, the quality of statistical climate forecast systems (forecast quality) is an ill-defined and frequently misunderstood property. Often, providers and users of such forecast systems are unclear about what ‘quality’ entails and how to measure it, leading to confusion and misinformation. Here we present a generic framework to quantify aspects of forecast quality using an inferential approach to calculate nominal significance levels (p-values) that can be obtained either by directly applying non-parametric statistical tests such as Kruskal-Wallis (KW) or Kolmogorov-Smirnov (KS) or by using Monte-Carlo methods (in the case of forecast skill scores). Once converted to p-values, these forecast quality measures provide a means to objectively evaluate and compare temporal and spatial patterns of forecast quality across datasets and forecast systems. Our analysis demonstrates the importance of providing p-values rather than adopting some arbitrarily chosen significance levels such as p < 0.05 or p < 0.01, which is still common practice. This is illustrated by applying non-parametric tests (such as KW and KS) and skill scoring methods (LEPS and RPSS) to the 5-phase Southern Oscillation Index classification system using historical rainfall data from Australia, The Republic of South Africa and India. The selection of quality measures is solely based on their common use and does not constitute endorsement. We found that non-parametric statistical tests can be adequate proxies for skill measures such as LEPS or RPSS. The framework can be implemented anywhere, regardless of dataset, forecast system or quality measure. Eventually such inferential evidence should be complimented by descriptive statistical methods in order to fully assist in operational risk management.

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Conducting and semiconducting polymers are important materials in the development of printed, flexible, large-area electronics such as flat-panel displays and photovoltaic cells. There has been rapid progress in developing conjugated polymers with high transport mobility required for high-performance field-effect transistors (FETs), beginning(1) with mobilities around 10(-4) cm(2) V-1 s(-1) to a recent report(2) of 1 cm(2) V-1 s(-1) for poly(2,5-bis(3-tetradecylthiophen-2-yl) thieno[3,2-b] thiophene) (PBTTT). Here, the electrical properties of PBTTT are studied at high charge densities both as the semiconductor layer in FETs and in electrochemically doped films to determine the transport mechanism. We show that data obtained using a wide range of parameters (temperature, gate-induced carrier density, source-drain voltage and doping level) scale onto the universal curve predicted for transport in the Luttinger liquid description of the one-dimensional `metal'.

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Field studies were conducted at two locations in southern Queensland, Australia during the 2003-2004 and 2004-2005 growing seasons to determine the differential competitiveness of sorghum (Sorghum bicolor L. Moench) cultivars and crop densities against weeds and the sorghum yield loss due to weeds. Weed competition was investigated by growing sorghum in the presence or absence of a model grass weed, Japanese millet (Echinochloa esculenta). The correlation analyses showed that the early growth traits (height, shoot biomass, and daily growth rate of the shoot biomass) of sorghum adversely affected the height, biomass, and seed production of millet, as measured at maturity. "MR Goldrush" and "Bonus MR" were the most competitive cultivars, resulting in reduced weed biomass, weed density, and weed seed production. The density of sorghum also had a significant effect on the crop's ability to compete with millet. When compared to the density of 4.5 plants per m2, sorghum that was planted at 7.5 plants per m2 suppressed the density, biomass, and seed production of millet by 22%, 27% and 38%, respectively. Millet caused a significant yield loss in comparison with the weed-free plots. The combined weed-suppressive effects of the competitive cultivars, such as MR Goldrush, and high crop densities minimized the yield losses from the weeds. These results indicate that sorghum competition against grass weeds can be improved by choosing competitive cultivars and by using a high crop density of > 7.5 plants per m2. These non-chemical options should be included in an integrated weed management program for better weed management, particularly where the control options are limited by the evolution of herbicide resistance.

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To experimentally investigate the effect of vertical artificial substrate and different densities of the banana prawn Penaeus (Fenneropenaeus) merguiensis on nutrient levels in prawn pond effluent, a time series experiment was conducted in a replicated tank system supplied periodically with discharge from a prawn production pond. Few differences (P>0.05) were detected between tanks without prawns, and tanks with low densities (5 prawns in 1700 litres) of prawns (10-12 g), in terms of nitrogen and phosphorus in the water column over the 28-day experimental period. Higher densities of prawns (starting at 25 or 50 per tank) caused an elevation of these macronutrients in the water column. This was partly due to prawn biomass losses from mortalities and weight reductions in the tank system. The survival and condition of prawns was significantly (P<0.05) reduced in tanks at these higher densities. The presence of artificial substrate (2 m2 tank-1) did not affect (P>0.05) the levels of nutrients in tank water columns, but significantly (P<0.05) increased the amount of nitrogen in tank residues left at the end of the trial when no prawns were present. The prawns had obviously been grazing on surfaces inside the tanks, and their swimming actions appeared to keep light particulate matter in suspension. Higher prawn densities increased microalgal blooms, which presumably kept ammonia levels low, and it is suggested that this association may provide the means for improved remediation of prawn farm effluent in the future.

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Context. Irregular plagues of house mice cause high production losses in grain crops in Australia. If plagues can be forecast through broad-scale monitoring or model-based prediction, then mice can be proactively controlled by poison baiting. Aims. To predict mouse plagues in grain crops in Queensland and assess the value of broad-scale monitoring. Methods. Regular trapping of mice at the same sites on the Darling Downs in southern Queensland has been undertaken since 1974. This provides an index of abundance over time that can be related to rainfall, crop yield, winter temperature and past mouse abundance. Other sites have been trapped over a shorter time period elsewhere on the Darling Downs and in central Queensland, allowing a comparison of mouse population dynamics and cross-validation of models predicting mouse abundance. Key results. On the regularly trapped 32-km transect on the Darling Downs, damaging mouse densities occur in 50% of years and a plague in 25% of years, with no detectable increase in mean monthly mouse abundance over the past 35 years. High mouse abundance on this transect is not consistently matched by high abundance in the broader area. Annual maximum mouse abundance in autumn–winter can be predicted (R2 = 57%) from spring mouse abundance and autumn–winter rainfall in the previous year. In central Queensland, mouse dynamics contrast with those on the Darling Downs and lack the distinct annual cycle, with peak abundance occurring in any month outside early spring.Onaverage, damaging mouse densities occur in 1 in 3 years and a plague occurs in 1 in 7 years. The dynamics of mouse populations on two transects ~70 km apart were rarely synchronous. Autumn–winter rainfall can indicate mouse abundance in some seasons (R2 = ~52%). Conclusion. Early warning of mouse plague formation in Queensland grain crops from regional models should trigger farm-based monitoring. This can be incorporated with rainfall into a simple model predicting future abundance that will determine any need for mouse control. Implications. A model-based warning of a possible mouse plague can highlight the need for local monitoring of mouse activity, which in turn could trigger poison baiting to prevent further mouse build-up.

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We have evaluated techniques of estimating animal density through direct counts using line transects during 1988-92 in the tropical deciduous forests of Mudumalai Sanctuary in southern India for four species of large herbivorous mammals, namely, chital (Axis axis), sambar (Cervus unicolor), Asian elephant (Elephas maximus) and gaur (Bos gauras). Density estimates derived from the Fourier Series and the Half-Normal models consistently had the lowest coefficient of variation. These two models also generated similar mean density estimates. For the Fourier Series estimator, appropriate cut-off widths for analysing line transect data for the four species are suggested. Grouping data into various distance classes did not produce any appreciable differences in estimates of mean density or their variances, although model fit is generally better when data are placed in fewer groups. The sampling effort needed to achieve a desired precision (coefficient of variation) in the density estimate is derived. A sampling effort of 800 km of transects returned a 10% coefficient of variation on estimate for chital; for the other species a higher effort was needed to achieve this level of precision. There was no statistically significant relationship between detectability of a group and the size of the group for any species. Density estimates along roads were generally significantly different from those in the interior af the forest, indicating that road-side counts may not be appropriate for most species.

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Ruthenium dioxide is deposited on stainless steel (SS) substrate by galvanostatic oxidation of Ru3+. At high current densities employed for this purpose, there is oxidation of water to oxygen, which occurs in parallel with Ru3+ oxidation. The oxygen evolution consumes a major portion of the charge. The oxygen evolution generates a high porosity to RuO2 films, which is evident from scanning electron microscopy studies. RuO2 is identified by X-ray photoelectron spectroscopy. Cyclic voltammetry and galvanostatic charge–discharge cycling studies indicate that RuO2/SS electrodes possess good capacitance properties. Specific capacitance of 276 F g−1 is obtained at current densities as high as 20 mA cm−2 (13.33 A g−1). Porous nature of RuO2 facilitates passing of high currents during charge–discharge cycling. RuO2/SS electrodes are thus useful for high power supercapacitor applications.

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The saturated liquid density, varrholr, data along the liquid vapour coexistence curve published in the literature for several cryogenic liquids, hydrocarbons and halocarbon refrigerants are fitted to a generalized equation of the following form varrholr = 1 + A(1 − Tr + B(1 − Tr)β The values of β, the index in phase density differences power law, have been obtained by means of two approaches namely statistical treatment of saturated fluid phase density difference data and the existence of a maximum in T(varrho1 − varrhov) along the saturation curve. Values of the constants A and B are determined utilizing the fact that Tvarrho1 has a maximum at a characteristic temperature T. Values of A, B and β are tabulated for Ne, Ar, Kr, Xe, N2, O2, methane, ethane, propane, iso-butane, n-butane, propylene, ethylene, CO2, water, ammonia, refrigerants-11, 12, 12B1, 13, 13B1, 14, 21, 22, 23, 32, 40, 113, 114, 115, 142b, 152a, 216, 245 and azeotropes R-500, 502, 503, 504. The average error of prediction is less than 2%.

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We use the Density Matrix Renormalization Group and the Abelian bosonization method to study the effect of density on quantum phases of one-dimensional extended Bose-Hubbard model. We predict the existence of supersolid phase and also other quantum phases for this system. We have analyzed the role of extended range interaction parameters on solitonic phase near half-filling. We discuss the effects of dimerization in nearest neighbor hopping and interaction as well as next nearest neighbor interaction on the plateau phase at half-filling.

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The principle of the conservation of bond orders during radical-exchange reactions is examined using Mayer's definition of bond orders. This simple intuitive approximation is not valid in a quantitative sense. Ab initio results reveal that free valences (or spin densities) develop on the migrating atom during reactions. For several examples of hydrogen-transfer reactions, the sum of the reaction coordinate bond orders in the transition state was found to be 0.92 +/- 0.04 instead of the theoretical 1.00 because free valences (or spin densities) develop on the migrating atom during reactions. It is shown that free valence is almost equal to the square of the spin density on the migrating hydrogen atom and the maxima in the free valence (or spin density) profiles coincide (or nearly coincide) with the saddle points in the corresponding energy profiles.

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This paper proposes a method of short term load forecasting with limited data, applicable even at 11 kV substation levels where total power demand is relatively low and somewhat random and weather data are usually not available as in most developing countries. Kalman filtering technique has been modified and used to forecast daily and hourly load. Planning generation and interstate energy exchange schedule at load dispatch centre and decentralized Demand Side Management at substation level are intended to be carried out with the help of this short term load forecasting technique especially to achieve peak power control without enforcing load-shedding.

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In order to meet the ever growing demand for the prediction of oceanographic parametres in the Indian Ocean for a variety of applications, the Indian National Centre for Ocean Information Services (INCOIS) has recently set-up an operational ocean forecast system, viz. the Indian Ocean Forecast System (INDOFOS). This fully automated system, based on a state-of-the-art ocean general circulation model issues six-hourly forecasts of the sea-surface temperature, surface currents and depths of the mixed layer and the thermocline up to five-days of lead time. A brief account of INDOFOS and a statistical validation of the forecasts of these parametres using in situ and remote sensing data are presented in this article. The accuracy of the sea-surface temperature forecasts by the system is high in the Bay of Bengal and the Arabian Sea, whereas it is moderate in the equatorial Indian Ocean. On the other hand, the accuracy of the depth of the thermocline and the isothermal layers and surface current forecasts are higher near the equatorial region, while it is relatively lower in the Bay of Bengal.

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Published also as: Documento de Trabajo Banco de España 0504/2005.