167 research outputs found
Forecasting Electrical Load Using a Multi-time-scale Approach
This paper describes the application of a multi-time-scale
technique to the modelling and forecasting of short-term
electrical load. The multi-time-scale technique is based on
adjusting the underlying short sampling period forecast time
series with specific target points and possible aggregated
demand. This allows not only improvement of the short
sampling period forecast, but also focuses on weighting the
accuracy of the forecast at certain critical points e.g. the
overnight minimum and daily peaks. Various model types may be utilised at the upper level (forecating the aggregated
consumption and target points at daily level), including
intelligent models such as neural and fuzzy models, but the
base model is currently restricted to a linear form. Results
for the Irish national electrical grid demonstrate the
effectiveness of the technique
Forecasting of Weekly Electricity Consumption Using Neural Networks
Neural networks have been shown to be effective in modelling time series, with applications in the forecasting of electricity consumption. In applying neural networks to weekly electricity consumption data, several issues, such as selection of network architecture, network structure and input structure need to be addressed. This paper addresses these issues in relation to the current application and also demonstrates that considerable value is to be gained from incorporating the lessons learned from linear time series modelling into the current nonlinear analysis. Results for national Irish weekly electricity data demonstrate the potential improvements which can be obtained using the neural network approach
Forecasting Electricity Demand on Short, Medium and Long Time Scales Using Neural Networks
This paper examines the application of artificial neural networks (ANNs) to the modelling and forecasting of electricity demand experienced by an electricity supplier. The data used in the application examples relates to the national electricity demand in the Republic of Ireland, generously supplied by the Electricity Supply Board (ESB). The paper focusses on three different time scales of interest to power boards: yearly (up to fifteen years in advance), weekly (up to three years in advance) and hourly (up to 24 h ahead). Electricity demand exhibits considerably different characteristics on these different time scales, both in terms of the underlying autoregressive processes and the causal inputs appropriate to each time scale. Where possible, the ANN-based models draw on the applications experience gained with linear modelling techniques and in one particular case, manual forecasting methods
Evolution of the electronic structure with size in II-VI semiconductor nanocrystals
In order to provide a quantitatively accurate description of the band gap
variation with sizes in various II-VI semiconductor nanocrystals, we make use
of the recently reported tight-binding parametrization of the corresponding
bulk systems. Using the same tight-binding scheme and parameters, we calculate
the electronic structure of II-VI nanocrystals in real space with sizes ranging
between 5 and 80 {\AA} in diameter. A comparison with available experimental
results from the literature shows an excellent agreement over the entire range
of sizes.Comment: 17 pages, 4 figures, accepted in Phys. Rev.
Effect of the Surface on the Electron Quantum Size Levels and Electron g-Factor in Spherical Semiconductor Nanocrystals
The structure of the electron quantum size levels in spherical nanocrystals
is studied in the framework of an eight--band effective mass model at zero and
weak magnetic fields. The effect of the nanocrystal surface is modeled through
the boundary condition imposed on the envelope wave function at the surface. We
show that the spin--orbit splitting of the valence band leads to the
surface--induced spin--orbit splitting of the excited conduction band states
and to the additional surface--induced magnetic moment for electrons in bare
nanocrystals. This additional magnetic moment manifests itself in a nonzero
surface contribution to the linear Zeeman splitting of all quantum size energy
levels including the ground 1S electron state. The fitting of the size
dependence of the ground state electron g factor in CdSe nanocrystals has
allowed us to determine the appropriate surface parameter of the boundary
conditions. The structure of the excited electron states is considered in the
limits of weak and strong magnetic fields.Comment: 11 pages, 4 figures, submitted to Phys. Rev.
History of clinical transplantation
How transplantation came to be a clinical discipline can be pieced together by perusing two volumes of reminiscences collected by Paul I. Terasaki in 1991-1992 from many of the persons who were directly involved. One volume was devoted to the discovery of the major histocompatibility complex (MHC), with particular reference to the human leukocyte antigens (HLAs) that are widely used today for tissue matching.1 The other focused on milestones in the development of clinical transplantation.2 All the contributions described in both volumes can be traced back in one way or other to the demonstration in the mid-1940s by Peter Brian Medawar that the rejection of allografts is an immunological phenomenon.3,4 © 2008 Springer New York
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