Hydrological sequence missing data complementation and trend prediction system and method

By constructing a hydrological sequence missing data completion and trend prediction system, and combining deep learning and blockchain technology, the robustness and reliability issues of hydrological sequence missing data under high missing rates are solved. It realizes physically reasonable completion and transparent decision-making process, and adapts to complex environmental changes.

CN121958786AActive Publication Date: 2026-05-01TIANJIN UNIV
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Patent Information

Application Number
CN202610405691.6
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2026-03-31
Publication Date
2026-05-01
Estimated Expiration
2046-03-31

AI Technical Summary

Technical Problem

Existing technologies for processing missing hydrological sequence data suffer from several drawbacks: data loss disrupts temporal continuity and statistical stationarity, lacks credibility and robustness, struggles to generate physically reasonable completion results in scenarios with high missing rates, and lacks transparent decision-making processes and data traceability capabilities.

Method used

A system for completing missing hydrological sequence data and predicting trends is constructed. Through data acquisition and preprocessing, spatiotemporal feature fusion, physical constraint completion, uncertainty prediction, and credible evidence storage and verification modules, combined with deep learning and blockchain technology, the system achieves efficient data completion and prediction, and provides full lifecycle visualization and traceability.

Benefits of technology

It significantly improves the robustness and accuracy of completion under high missing rates, ensures that the completion results conform to the physical consistency of natural hydrological processes, solves the data trust and traceability problems, enhances the interpretability and auditability of the system, and adapts to complex environmental changes.

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Abstract

The invention discloses a hydrological sequence missing data complementation and trend prediction system and method, and belongs to the technical field of water conservancy information. The system comprises a data acquisition and preprocessing module, a spatial-temporal feature fusion module, a physical constraint completion module, an uncertainty prediction module, a credible evidence storage and verification module and a visual tracing module which are connected in sequence. The method comprises the following steps: collecting and preprocessing multi-source hydrological data; combining the spatial-temporal features through a dual-channel network to generate joint representation; generating and checking a completion sequence based on joint representation and coupling physical constraints such as a unit line method and a Manning formula; performing uncertainty trend prediction by using an integrated predictor; the key data of the whole process are linked and stored, and are automatically verified through an intelligent contract; and full-life-cycle visual tracing is provided. According to the method, the complementation robustness and accuracy in a high-missing-rate scene are effectively improved, the physical consistency of a complementation result is ensured, and credible evidence storage and transparent decision of the whole process are realized.
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