Short-term electricity demand and gas price forecasts using wavelet transforms and adaptive models

This paper presents some forecasting techniques for energy demand and price prediction, one day ahead. These techniques combine wavelet transform (WT) with fixed and adaptive machine learning/time series models (multi-layer perceptron (MLP), radial basis functions, linear regression, or GARCH). To create an adaptive model, we use an extended Kalman filter or particle filter to update the parameters continuously on the test set. The adaptive GARCH model is a new contribution, broadening the applicability of GARCH methods. We empirically compared two approaches of combining the WT with prediction models: multicomponent forecasts and direct forecasts. These techniques are applied to large sets of real data (both stationary and non-stationary) from the UK energy markets, so as to provide comparative results that are statistically stronger than those previously reported. The results showed that the forecasting accuracy is significantly improved by using the WT and adaptive models. The best models on the electricity demand/gas price forecast are the adaptive MLP/GARCH with the multicomponent forecast; their MSEs are 0.02314 and 0.15384 respectively.

Simultaneous measurement of strain and temperature using the first- and second-order diffraction wavelengths of Bragg gratings

A method of discriminating between temperature and strain effects in fibre sensing using a conventionally written, in-fibre Bragg grating is presented. The technique uses wavelength information from the first and second diffraction orders of the grating element to determine the wavelength dependent strain and temperature coefficients, from which independent temperature and strain measurements can be made. The authors present results that validate this matrix inversion technique and quantify the strain and temperature errors which can arise for a given uncertainty in the measurement of the reflected wavelength.

Lithological mapping of Northwest Argentina with remote sensing data using tonal, textural and contextual features

Tonal, textural and contextual properties are used in manual photointerpretation of remotely sensed data. This study has used these three attributes to produce a lithological map of semi arid northwest Argentina by semi automatic computer classification procedures of remotely sensed data. Three different types of satellite data were investigated, these were LANDSAT MSS, TM and SIR-A imagery. Supervised classification procedures using tonal features only produced poor classification results. LANDSAT MSS produced classification accuracies in the range of 40 to 60%, while accuracies of 50 to 70% were achieved using LANDSAT TM data. The addition of SIR-A data produced increases in the classification accuracy. The increased classification accuracy of TM over the MSS is because of the better discrimination of geological materials afforded by the middle infra red bands of the TM sensor. The maximum likelihood classifier consistently produced classification accuracies 10 to 15% higher than either the minimum distance to means or decision tree classifier, this improved accuracy was obtained at the cost of greatly increased processing time. A new type of classifier the spectral shape classifier, which is computationally as fast as a minimum distance to means classifier is described. However, the results for this classifier were disappointing, being lower in most cases than the minimum distance or decision tree procedures. The classification results using only tonal features were felt to be unacceptably poor, therefore textural attributes were investigated. Texture is an important attribute used by photogeologists to discriminate lithology. In the case of TM data, texture measures were found to increase the classification accuracy by up to 15%. However, in the case of the LANDSAT MSS data the use of texture measures did not provide any significant increase in the accuracy of classification. For TM data, it was found that second order texture, especially the SGLDM based measures, produced highest classification accuracy. Contextual post processing was found to increase classification accuracy and improve the visual appearance of classified output by removing isolated misclassified pixels which tend to clutter classified images. Simple contextual features, such as mode filters were found to out perform more complex features such as gravitational filter or minimal area replacement methods. Generally the larger the size of the filter, the greater the increase in the accuracy. Production rules were used to build a knowledge based system which used tonal and textural features to identify sedimentary lithologies in each of the two test sites. The knowledge based system was able to identify six out of ten lithologies correctly.

OTDM network processing using all-optical and electro-optical devices

The current optical communications network consists of point-to-point optical transmission paths interconnected with relatively low-speed electronic switching and routing devices. As the demand for capacity increases, then higher speed electronic devices will become necessary. It is however hard to realise electronic chip-sets above 10 Gbit/s, and therefore to increase the achievable performance of the network, electro-optic and all-optic switching and routing architectures are being investigated. This thesis aims to provide a detailed experimental analysis of high-speed optical processing within an optical time division multiplexed (OTDM) network node. This includes the functions of demultiplexing, 'drop and insert' multiplexing, data regeneration, and clock recovery. It examines the possibilities of combining these tasks using a single device. Two optical switching technologies are explored. The first is an all-optical device known as 'semiconductor optical amplifier-based nonlinear optical loop mirror' (SOA-NOLM). Switching is achieved by using an intense 'control' pulse to induce a phase shift in a low-intensity signal propagating through an interferometer. Simultaneous demultiplexing, data regeneration and clock recovery are demonstrated for the first time using a single SOA-NOLM. The second device is an electroabsorption (EA) modulator, which until this thesis had been used in a uni-directional configuration to achieve picosecond pulse generation, data encoding, demultiplexing, and 'drop and insert' multiplexing. This thesis presents results on the use of an EA modulator in a novel bi-directional configuration. Two independent channels are demultiplexed from a high-speed OTDM data stream using a single device. Simultaneous demultiplexing with stable, ultra-low jitter clock recovery is demonstrated, and then used in a self-contained 40 Gbit/s 'drop and insert' node. Finally, a 10 GHz source is analysed that exploits the EA modulator bi-directionality to increase the pulse extinction ratio to a level where it could be used in an 80 Gbit/s OTDM network.

A structural investigation of the alkali metal site distribution within bioactive glass using neutron diffraction and multinuclear solid state NMR

The atomic-scale structure of Bioglass and the effect of substituting lithium for sodium within these glasses have been investigated using neutron diffraction and solid state magic angle spinning (MAS) NMR. Applying an effective isomorphic substitution difference function to the neutron diffraction data has enabled the Na-O and Li-O nearest-neighbour correlations to be isolated from the overlapping Ca-O, O-(P)-O and O-(Si)-O correlations. These results reveal that Na and Li behave in a similar manner within the glassy matrix and do not disrupt the short range order of the network former. Residual differences are attributed solely to the variation in ionic radius between the two species. Successful simplification of the 2 and an analogous splitting of the Li-O correlations. The observed correlations are attributed to the metal ions bonded either to bridging or to non-bridging oxygen atoms. 23Na triple quantum MAS (3QMAS) NMR data corroborates the split Na-O correlations. The structural sites present will be intimately related to the release properties of the glass system in physiological fluids such as plasma and saliva, and hence to the bioactivity of the material. Detailed structural knowledge is therefore a prerequisite for optimizing material design.

All-optical passive regeneration of 40 Gbit/s soliton data stream using dispersion management and in-line NOLMs

It is numerically demonstrated, for the first time, that dispersion management and in-line nonlinear optical loop mirrors can achieve all-optical passive regeneration and distance-unlimited transmission of a soliton data stream at 40 Gbit/s over standard fibre.

All-optical passive regeneration of 40 Gbit/s soliton data stream using dispersion-management and in-line nonlinear optical loop mirrors

We numerically demonstrate for the first time that dispersion management and in-line nonlinear optical loop mirrors can achieve all-optical passive regeneration and distance-unlimited transmission of a soliton data stream at 40 Gbit/s over standard fibre.

Cost-effective upgrade of WDM all-optical networks using overlay fibres and hop reduction links

Fibre overlay is a cost-effective technique to alleviate wavelength blocking in some links of a wavelength-routed optical network by increasing the number of wavelengths in those links. In this letter, we investigate the effects of overlaying fibre in an all-optical network (AON) based on GÉANT2 topology. The constraint-based routing and wavelength assignment (CB-RWA) algorithm locates where cost-efficient upgrades should be implemented. Through numerical examples, we demonstrate that the network capacity improves by 25 per cent by overlaying fibre on 10 per cent of the links, and by 12 per cent by providing hop reduction links comprising 2 per cent of the links. For the upgraded network, we also show the impact of dynamic traffic allocation on the blocking probability. Copyright © 2010 John Wiley & Sons, Ltd.

Productivity change using growth accounting and frontier-based approaches:evidence from a Monte Carlo analysis

This study presents some quantitative evidence from a number of simulation experiments on the accuracy of the productivitygrowth estimates derived from growthaccounting (GA) and frontier-based methods (namely data envelopment analysis-, corrected ordinary least squares-, and stochastic frontier analysis-based malmquist indices) under various conditions. These include the presence of technical inefficiency, measurement error, misspecification of the production function (for the GA and parametric approaches) and increased input and price volatility from one period to the next. The study finds that the frontier-based methods usually outperform GA, but the overall performance varies by experiment. Parametric approaches generally perform best when there is no functional form misspecification, but their accuracy greatly diminishes otherwise. The results also show that the deterministic approaches perform adequately even under conditions of (modest) measurement error and when measurement error becomes larger, the accuracy of all approaches (including stochastic approaches) deteriorates rapidly, to the point that their estimates could be considered unreliable for policy purposes.

Simultaneous measurement of strain and temperature using the first- and second-order diffraction wavelengths of Bragg gratings

A method of discriminating between temperature and strain effects in fibre sensing using a conventionally written, in-fibre Bragg grating is presented. The technique uses wavelength information from the first and second diffraction orders of the grating element to determine the wavelength dependent strain and temperature coefficients, from which independent temperature and strain measurements can be made. The authors present results that validate this matrix inversion technique and quantify the strain and temperature errors which can arise for a given uncertainty in the measurement of the reflected wavelength.

All-optical passive regeneration of 40 Gbit/s soliton data stream using dispersion management and in-line NOLMs

The feasibility of stable soliton transmission system was demonstrated using a practical dispersion map in conjunction with in-line nonlinear optical loop mirrors (NOLMs). The system's performance was examined at 40 Gbit/s data rate in terms of maximum propagation distance corresponding to a bit error rate of more than 10-9. The bit error rate was estimated by means of the standard Q-factor.

Cost-effective upgrade of WDM all-optical networks using overlay fibres and hop reduction links

Fibre overlay is a cost-effective technique to alleviate wavelength blocking in some links of a wavelength-routed optical network by increasing the number of wavelengths in those links. In this letter, we investigate the effects of overlaying fibre in an all-optical network (AON) based on GÉANT2 topology. The constraint-based routing and wavelength assignment (CB-RWA) algorithm locates where cost-efficient upgrades should be implemented. Through numerical examples, we demonstrate that the network capacity improves by 25 per cent by overlaying fibre on 10 per cent of the links, and by 12 per cent by providing hop reduction links comprising 2 per cent of the links. For the upgraded network, we also show the impact of dynamic traffic allocation on the blocking probability. Copyright © 2010 John Wiley & Sons, Ltd.

Density forecasts of crude-oil prices using option-implied and ARCH-type models

The predictive accuracy of competing crude-oil price forecast densities is investigated for the 1994–2006 period. Moving beyond standard ARCH type models that rely exclusively on past returns, we examine the benefits of utilizing the forward-looking information that is embedded in the prices of derivative contracts. Risk-neutral densities, obtained from panels of crude-oil option prices, are adjusted to reflect real-world risks using either a parametric or a non-parametric calibration approach. The relative performance of the models is evaluated for the entire support of the density, as well as for regions and intervals that are of special interest for the economic agent. We find that non-parametric adjustments of risk-neutral density forecasts perform significantly better than their parametric counterparts. Goodness-of-fit tests and out-of-sample likelihood comparisons favor forecast densities obtained by option prices and non-parametric calibration methods over those constructed using historical returns and simulated ARCH processes. © 2010 Wiley Periodicals, Inc. Jrl Fut Mark 31:727–754, 2011