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Fuzzy Sets and Systems, 1997
Abstract In this paper, a fuzzy forecasting technique for seasonality in the time-series data is presented using the following procedure. First, with the fuzzy regression analysis the fuzzy trend of a time-series is analyzed. Then the fuzzy seasonality is defined by realizing the membership grades of the seasons to the fuzzy regression model.
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Abstract In this paper, a fuzzy forecasting technique for seasonality in the time-series data is presented using the following procedure. First, with the fuzzy regression analysis the fuzzy trend of a time-series is analyzed. Then the fuzzy seasonality is defined by realizing the membership grades of the seasons to the fuzzy regression model.
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Quarterly Journal of the Royal Meteorological Society, 1998
Abstract Examples are used to provide an appreciation of the most recent developments in real‐time experimental and operational seasonal forecasting and also of some of the wide issues surrounding the provision and use of such forecasts.
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Abstract Examples are used to provide an appreciation of the most recent developments in real‐time experimental and operational seasonal forecasting and also of some of the wide issues surrounding the provision and use of such forecasts.
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Seasonal cointegration, common seasonals, and forecasting seasonal series
Empirical Economics, 1993Seasonal cointegration generalizes the idea of cointegration to processes with unit roots at frequencies different from 0. Here, “common seasonals,” also a dual notion of common trends, is adopted for the seasonal case. The features are demonstrated in exemplary models for German and U.K. data.
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Forecasting of Seasonal Apparel Products
2015Demand forecasting of fashion apparel products has to cope with serious difficulties in order to get more accurate forecasts early enough to influence production decisions. Demand has to be anticipated at an early date due to long production lead times.
Michael Teucke +4 more
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1999
Abstract Forecasting is about making predictions of future events consistent with one’s best judgments. Consequently, it is desirable to allow for consistent revisions of those judgments as more data become available. Statistical models are efficient means of logically understanding the data and should be used as a guide to ...
James B Elsner, A Birol Kara
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Abstract Forecasting is about making predictions of future events consistent with one’s best judgments. Consequently, it is desirable to allow for consistent revisions of those judgments as more data become available. Statistical models are efficient means of logically understanding the data and should be used as a guide to ...
James B Elsner, A Birol Kara
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Forecasting time-series with correlated seasonality [PDF]
, 2004 A new approach to forecasting seasonal data is proposed where seasonal terms can be updated using the most recent relevant information. It was developed to handle features encountered in hourly electricity load data and daily hospital admissions data.
Phillip Gould +5 more
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The economic value of seasonal forecast
1998The probabilistic nature of seasonal forecasts is utilized to quantify its economic value. This depends on the end user - for some an ability to forecast probability that are only marginally different from climatology might be useful, for others such probabilities might be worthless.
Palmer, T.N. +2 more
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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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Through this dissertation, we contributed to the advancement and applicability of seasonal climate forecasts in agriculture and water management sectors.
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