A hydrological forecast correlation warning method based on multiple factors

By using multi-factor correlation sites in hydrological forecasting to obtain models and trained forecast models, the problem of insufficient consideration of impact factors is solved, and the accuracy and efficiency of hydrological forecasting are improved.

CN119293566BActive Publication Date: 2025-03-25ZHEJIANG KEEPSOFT INFORMATIONTECHNOLOGY CORP LTD
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Patent Information

Application Number
CN202411813106.3
Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
Filing Date
2024-12-11
Publication Date
2025-03-25
Estimated Expiration
2044-12-11

AI Technical Summary

Technical Problem

In the existing hydrological forecasting technology, insufficient consideration of impact factors leads to low forecast accuracy and low data processing efficiency.

Method used

A multi-factor correlation site acquisition model is used, including correlation coefficient, Copula entropy and histogram intersection value acquisition unit, to obtain the associated sites of the site to be forecasted, and to obtain forecast data through the trained forecast model, and to issue warning information.

Benefits of technology

It improves the accuracy and data processing efficiency of hydrological forecasts, and meets the early warning needs of hydrological forecasts.

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Abstract

The present invention relates to the technical field of hydrological forecasting, and in particular to a hydrological forecasting association warning method based on multiple factors, comprising: obtaining historical basic parameters of a site to be forecasted and historical basic parameters of other water conservancy projects in the same river basin, inputting the historical basic parameters of the site to be forecasted and the historical basic parameters of other water conservancy projects in the same river basin into a pre-set multiple factor association site acquisition model, and obtaining the associated sites of the site to be forecasted; obtaining the real-time basic parameters of the site to be forecasted and the real-time basic parameters of the associated sites of the site to be forecasted, and performing data preprocessing on them to obtain the preprocessed data; inputting the preprocessed data into a trained forecasting model to obtain forecast data of the site to be forecasted; comparing the forecast data of the site to be forecasted with a corresponding data threshold, and issuing warning information when the data threshold is exceeded; the present invention effectively improves the efficiency and accuracy of hydrological forecasting in the same river basin.
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