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Traditional method about forecast of energy demand, Trend Extrapolation, can’t study the information supplied with date effectively, and BP neural network has the great power of goal learning, which can dig potential function in the date. The article design the GDP and other factors as input variables, and use steepest descent back propagation to(More)
In order to evaluate the effect of dropping parts of coefficients in H.264 bit-stream, the distortion aroused by coefficient dropping has to be estimated accurately. In this paper, an efficient method is presented to estimate the distortion of a frame during the error propagation caused by single frame coefficient dropping of H.264 bit-stream. At first,(More)
– This paper reports new contributions to the advancement of wind power uncertainty forecasting beyond the current state-of-the-art. A new kernel density forecast (KDF) method applied to the wind power problem is described. The method is based on the Nadaraya-Watson estimator, and a time-adaptive version of the algorithm is also proposed. Results are(More)
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