Some Statistical Results in the Combination of Forecasts

Dickinson, J. E.

doi:10.1057/jors.1973.42

Cited by 113 publications

(39 citation statements)

References 2 publications

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“…The concept of the model-output combination is certainly not new and it is quite commonly used in other branches of science, such as statistics, management, psychology, economics and meteorology (Bates & Granger, 1969;Thompson, 1977;Dickinson, 1973Dickinson, , 1975Newbold & Granger, 1974;Winkler, 1989;Armstrong, 1989;Clemen, 1989;Clemen et al, 1995;Batchelor & Dua, 1995). However, it is not yet used in the context of hydrological forecasting.…”

Section: Open For Discussion Until I June 2000mentioning

confidence: 99%

A real-time combination method for the outputs of different rainfall-runoff models

Shamseldin

O’Connor

1999

Hydrological Sciences Journal

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Application of the concept of combining the estimated forecast output of different rainfall-runoff models to yield an overall combined estimated output in the context of real-time river flow forecasting is explored. A Real-Time Model Output Combination Method (RTMOCM) is developed, based on the structure of the Linear Transfer Function Model (LTFM) and utilizing the concept of the Weighted Average Method (WAM) for model output combination. A multiple-input single-output form of the LTFM is utilized in the RTMOCM. This form of the LTFM model uses synchronously the daily simulation-mode model-estimated discharge time series of the rainfall-runoff models selected for combination, its inherent updating structure being used for providing updated combined discharge forecasts. The RTMOCM is applied to the daily data of five catchments, using the simulation-mode estimated discharges of three selected rainfall-runoff models, comprising one conceptual model (Soil Moisture Accounting and Routing Procedure-SMAR) and two black-box models (Linear Perturbation Model-LPM and Linearly-Varying Variable Gain Factor Model-LVGFM). In order to get an indication of the accuracy of the updated combined discharge forecasts relative to the updated discharge forecasts of the individual models, the LTFM is also used for updating the simulation-mode discharge time series of each of the three individual models. The results reveal that the updated combined discharge forecasts provided by the RTMOCM, with parameters obtained by linear regression, can improve on the updated discharge forecasts of the individual rainfall-runoff models. Un méthode de combinaison en temps réel des résultats de différents modèles pluie-débitRésumé Le but de cette communication est d'explorer l'application d'une technique de combinaison des estimations de différents modèles pluie-débit pour produire une estimation globale en temps réel. Une méthode de combinaison d'estimations en temps réel a été développée sur la base d'un modèle de Fonction de Transfert Linéaire utilisant une méthode de pondération pour la combinaison. Cette méthode utilise des entrées multiples et produit une sortie unique. Cette forme du modèle de fonction de transfert linéaire utilise simultanément les séries chronologiques de débits produites par les différents modèles sélectionnés, sa structure d'actualisation étant utilisée pour produire une combinaison globale des estimations. Nous avons appliqué cette méthode aux données de cinq régions en utilisant les estimations de trois modèles, un modèle conceptuel et deux modèles de type boite noire. Afin d'avoir une idée de la précision des prévisions de débit combinées relativement aux prévisions des modèles individuels, nous avons également utilisé le modèle de fonction de transfert linéaire afin de mettre à jour les simulations de chacun des trois modèles de base. Les résultats montrent que les prévisions mises à jour fournies par notre méthode, dont les paramètres ont été estimés par régression linéaire, peuvent apporter des amélioratio...

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Section: Open For Discussion Until I June 2000mentioning

confidence: 99%

A real-time combination method for the outputs of different rainfall-runoff models

Shamseldin

O’Connor

1999

Hydrological Sciences Journal

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“…Bates & Granger proposed that using a MV criterion can determine the weights to adequately apply the additional information hidden in the discarded forecast(s) (Bates & Granger, 1969), and Dickinson extended the method to the combinations of N forecasts (Dickinson, 1973). Assuming that the individual forecast errors are unbiased, we can calculate the vector of weights to minimize the error variance of the combination according to the formula…”

Section: Optimal Weights (Ow) Methodsmentioning

confidence: 99%

How to Provide Accurate and Robust Traffic Forecasts Practically?

Zhang¹

2012

Intelligent Transportation Systems

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“…This type of a specification is called an ARMAX model. Formally, an ARMAX model can be expressed as a structural equation and an equation to specify ARMA disturbances, respectively [11]: [7] are mathematical models which can approximate any (nonlinear) continuous function arbitrarily well. ANNs are modeled by using neurons resembling those of the human brain.…”

Section: Armax Modelmentioning

confidence: 99%

A Survey of Different Prediction Models & Role of Artificial Neural Networks for Natural Gas Consumption

2015

IJSR

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It is very important fact that natural gas is now a very significant element of human beings day to day life. Local Distribution Companies (LDCs) are forecasting their customers' natural gas demand with different traditional and advanced methodologies. However the forecasting needs to be accurate to mitigate the demand and supply. A significant error on a single day can cost a lot to the customers of the LDC. Different attempts have been made to predict the natural gas prediction accurately by different research paper. A better and more realistic energy forecast is essential for the policy makers and LDC owners/managers when futuristic decisions for the next epoch. As this upsurge in energy usage may posture a threat to economic development in the nation, Therefore, the policy makers need an accurate prediction of natural gas consumption to meet the demand and needs of the people. This paper looks at the brief description of each method and techniques described in different research papers.

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Some Statistical Results in the Combination of Forecasts

Cited by 113 publications

References 2 publications

A real-time combination method for the outputs of different rainfall-runoff models

A real-time combination method for the outputs of different rainfall-runoff models

How to Provide Accurate and Robust Traffic Forecasts Practically?

A Survey of Different Prediction Models & Role of Artificial Neural Networks for Natural Gas Consumption

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