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Short-Term Forecasting of Internal Migration
Environment and Planning A: Economy and Space, 1993Models for short-range forecasts differ from those for intermediate and long-range forecasts because of the possibility of introducing lagged exogenous factors as explanatory variables. It is widely believed that certain exogenous variables, in particular estimates of state income, are useful leading indicators of migration rates. In this paper, panel-
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2019
Although assigned a range of tasks, Godley quickly gains a reputation for assembling data and preparing the one-year forecast, which has become a central Treasury function and the anchor of its other activities. His data analysis skills are the Launchpad for some life-changing intellectual alliances, especially with Cambridge economist Nicholas Kaldor (
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Although assigned a range of tasks, Godley quickly gains a reputation for assembling data and preparing the one-year forecast, which has become a central Treasury function and the anchor of its other activities. His data analysis skills are the Launchpad for some life-changing intellectual alliances, especially with Cambridge economist Nicholas Kaldor (
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Monitoring Schemes in Short-term Forecasting
Journal of the Operational Research Society, 1976A necessary ingredient of a practical short-term forecasting system in which the parameters of the demand model are not adaptive is some form of monitoring to detect changes in the demand pattern for which the model is inadequate. There are two major automatic methods currently in use for accomplishing this aim.
E. R. Golder, J. G. Settle
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A Bayesian Approach to Short-Term Forecasting
Operational Research Quarterly (1970-1977), 1971A new approach to short-term forecasting is described, based on Bayesian principles. The performance of conventional systems is often upset by the occurrence of changes in trend and slope, or transients. In this approach events of this nature are modelled explicitly, and successive data points are used to calculate the posterior probabilities of such ...
Harrison, P. J., Stevens, C. F.
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Short-term forecasting in electronics
International Journal of Electronics, 2011Short time series are characterised by a lack of the following: trend information, randomness and periodicity. This makes prediction based on them very difficult or even impossible. This unfortunately is frequently the case in modern electronic developments.
Jelena Milojković, Vančo Litovski
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The Short-Term Forecasting Model
1970The short-term forecasting model is the first of a series of types of models, to be discussed in some of the following chapters. In fact the term ‘tiannual macro-economic model’ would be more appropriate. The one essentially different feature of quarterly models, seasonal adjustment, is not discussed in this book.
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Short-Term Forecasting Methods
1976Forecasting is a vital ingredient in the making of both long-term and short-term plans. For example, in the control and management of working capital we are attempting to optimise the future profitability-risk profile of the firm and this will require, amongst other things, forecasts of the future demand for inventory, the level of future interest ...
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Short-Term Seasonal Energy Forecasting
2018 IEEE International Conference on Electro/Information Technology (EIT), 2018Load Forecasting is an important tool used to predict future electrical utility data in a Smart Grid. Forecasting uses past data to predict trends for future energy usage. This paper investigates the application of exponential smoothing, ARIMA and recursive neural networks in TensorFlow on utility data taken from 20 different US Utility zones over four
Reilly Kedrowski +3 more
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Short-term electricity price forecasting
2013 IEEE Power & Energy Society General Meeting, 2013Price forecasting has become an important tool in the planning and operation of restructured power systems. This paper develops a new short-term electricity price forecasting scheme based on a state space model of the power market. A Gauss-Markov process is used to represent the stochastic dynamics of the electricity market.
A. Arabali +3 more
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Forecasting Short-Term Exchange Rates
2011Movements in foreign exchange rates are the results of collective human decisions, which are the results of the dynamics of their neurons. In this chapter, we demonstrate how to model these types of market behaviors by recurrent neural networks (RNN). The RNN approach can help us to forecast the short-term trend of foreign exchange rates.
Leong-Kwan Li +3 more
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