Monthly Runoff Probabilistic Forecast Model Based on Similar Process Derivations

Cai Lin Lee; Dong Mei Wang

doi:10.4028/www.scientific.net/AMM.737.710

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vol. 737Monthly Runoff Probabilistic Forecast Model Based...

Monthly Runoff Probabilistic Forecast Model Based on Similar Process Derivations

Abstract:

In this paper, a runoff forecast model combining similar process derivation with probabilistic forecasts is proposed. Certain forecast result is computed by similar processes derivations, and on the basis of certain results, a confidence interval under given confidence coefficient is worked out by probabilistic forecast part. The model is simple in structure, easy in establishing and unnecessary to concern for predictor selections. Applying above model in simulation experiments, the results show the forecast model have excellent forecast accuracy and can be used in monthly runoff forecast effectively.

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Periodical:

Applied Mechanics and Materials (Volume 737)

Pages:

710-714

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.737.710

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Online since:

March 2015

Authors:

Cai Lin Lee, Dong Mei Wang*

Keywords:

Monthly Runoff Forecast, Probabilistic Forecasts, Similar Process Derivation

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References

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