一种区域性土壤干旱预警智能管理方法及系统
By using moving average processing based on historical grid data and finite state machine algorithm, the regional specificity and dynamic updating problems of regional soil drought early warning methods are solved, the stability and foresight of early warning signals are achieved, and the accuracy and decision support capabilities of the early warning system are improved.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- SICHUAN METEOROLOGICAL OBSERVATORY
- Filing Date
- 2026-05-27
- Publication Date
- 2026-07-17
AI Technical Summary
In existing technologies, regional soil drought early warning methods lack regional specificity, have poor stability of early warning signals, lack dynamic evolution and closed-loop management, and are insufficient in foresight and timeliness, resulting in inaccurate early warning thresholds, frequent changes in early warning levels, and a decline in the authority of information.
The system employs a moving average processing technique based on historical grid data to calculate region-specific thresholds. Combined with a finite state machine algorithm, it achieves dynamic updates and closed-loop management of early warning levels. Short-term fluctuations are suppressed through 7-day moving average smoothing, generating forward-looking early warning signals.
It has achieved smooth stability and accuracy of early warning signals, reduced administrative costs, enhanced the authority and credibility of early warning information, and provided forward-looking decision support for drought prevention and relief.
Smart Images
Figure CN122416635A_ABST