The paper proposes a simple hybrid model to forecast the electrical load data based on the wavelet transform technique and double exponential smoothing. The historical noisy load series data is decomposed into deterministic and fluctuation components using suitable wavelet coefficient thresholds and wavelet reconstruction method. The variation characteristics of the resulting series are analyzed to arrive at reasonable thresholds that yield good denoising results. The constitutive series are then forecasted using appropriate exponential adaptive smoothing models. A case study performed on California energy market data demonstrates that the proposed method can offer high forecasting precision for very short-term forecasts, considering a time horizon of two weeks.

Abstract. This paper deals with the vibration of tapered column which is affected by gravity using a pseudospectral formulation. The formulation is simple and easy-to-implement and is capable of dealing with different end conditions. Numerical examples of the effects of taper, cross section shapes and gravity on the vibration of columns are illustrated. The effectiveness of the pseudospectral method for vibration analysis of tapered heavy columns is validated by comparing the results with numerical techniques such as the numerical initial value method and differential quadrature method.

Load forecasts of short lead times ranging from an hour to a day ahead are essential for improving the economic efficiency and reliability of power systems. This paper proposes a hybrid model based on the wavelet transform (WT) and the weighted nearest neighbor (WNN) techniques to predict the day ahead electrical load. The WT is used to decompose the load series into deterministic series and fluctuation series that reflect the changing dynamics of data. The two subseries are then separately forecast using appropriately fitted WNN models. The final forecast is obtained by composing the predicted results of each subseries. The hourly electrical load of California and Spanish energy markets are taken as experimental data and the mean absolute percentage error (MAPE), Weekly MAPE (WMAPE) and Monthly MAPE (MMAPE) are computed to evaluate the forecasting performance of the next-day load forecasts. The forecasting efficiency of the proposed model is evaluated using db2, db4, db5 and bior 3.1 wavelets. The results demonstrate the forecasting accuracy of the proposed hybrid model.

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In an attempt to include the effects of natural porosity of lung parenchyma into the mathematical study of lung diagnostics, a model describing the propagation of low-frequency Rayleigh waves in relation to the porous architecture of the lung parenchyma is presented. The wave motion is analyzed by assuming that the lung parenchyma behaves as an isotropic elastic half-space containing a distribution of vacuous pores with the visceral pleura as a taut elastic membrane in smooth contact with the half-space. The thinness of the pleural membrane in comparison with the large surface area of contact enables it to be modeled as a material surface in contact with the parenchyma. Utilizing the perturbation technique, an approximate formula for the Rayleigh wave velocity in the parenchyma with allowance for surface tension, mass density, and porosity is derived. In addition, the effect of the tension in the pleural membrane and the porosity in the parenchyma on the propagation of the low-frequency Rayleigh waves is brought out through the dispersion spectrum. It is hoped that the results of this paper would enable a better understanding of the porosity and surface-tension effects on lung parenchyma.