A. S. 1974 The use of 500 mb anomalies in long-range forecasting . Quart. J. R. Met. Soc. , 100 , p. 245 .Ratcliffe, R. A. S. 1974 The use of 500 mb anomalies in long-range forecasting . Quart. J. R. Met. Soc. , 100 , pp. 234 – 244 ....
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Experimentally, we have observed that deaths fall somewhere in the range of estimates produced by these CFR models (eg. model 4 tends to overestimate, and model 5 tends to underestimate.) To refine our estimates, since 2020-07-26 we also produce a best guess forecast: We assume the rate ...
Empirical orthogonal function (EOF) and singular value decomposition (SVD) analyses are applied to the Dynamical Extended Range Forecasting 90 (DERF90) dataset to find the most predictable areas and patterns in the nonwinter Northern Hemisphere 500mb height fields. Global 500mb height forecast and ...
Skillful Long-Lead Seasonal Predictions in the Summertime Northern Hemisphere Midlatitudes Although a large part of the forecast skill for the surface air temperature and 500-hPa geopotential height is attributable to the linear trend associated ... H Lin,R Muncaster,J Derome,... - 《Journal of...
Long range energy forecasts suggest that world demand for LNG would double by 2020. While much of this demand will be met by baseload LNG liquefaction plants, this growth trend is also leading to the evolution of new LNG market structure... JT Verghese - Offshore Technology Conference 被引量...
T7415014 ANNEARLY: MATLAB function to forecast univariate time series by Shapour Mohammadi S458891 MRSPREP: Stata module to estimate marginal relative survival models by Paul Lambert S458890 ARHOMME: Stata module to estimate Arellano and Bonhomme quantile selection model ...
It is desirable also to know how confidently one can forecast snow or rain when the thickness is a certain amount above or below the equal probability value. To this end, the data were combined for stations having approximately the same value of equal probability thickness. The probability of ...
A Bidirectional Long Short-Term Memory Autoencoder Transformer for Remaining Useful Life Estimation. Mathematics 2023, 11, 4972. [Google Scholar] [CrossRef] Hinchi, A.Z.; Tkiouat, M. Rolling element bearing remaining useful life estimation based on a convolutional long-short-term memory network...
Liu et al. [22] proposed an approach for forecast machinery’s RUL based on deep LSTM network. Luo et al. [23] suggested a convolutional bi-directional long- and short-term memory (BiLSTM) network with attention mechanism to predict bearings’ RUL. These deep learning methods do not rely...