A natural reserve intelligent checking method and system based on multi-source data driving

CN121009324BActive Publication Date: 2026-08-28MINISTRY OF ECOLOGY & ENVIRONMENT CENT FOR SATELLITE APPL ON ECOLOGY ENVIRONMENT
View PDF 2 Cites 0 Cited by

Patent Information

Application Number
CN202511120533.8
Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
Filing Date
2025-08-12
Publication Date
2026-08-28
Estimated Expiration
2045-08-12

AI Technical Summary

Technical Problem

[0003]然而，现在技术仍存在一个核心缺陷：缺乏一种统一的多源数据智能关联与自动核查机制

Benefits of technology

[0057]该基于多源数据驱动的自然保护地智能核查方法及系统，通过自适应质量评估与对比学习驱动的跨模态嵌入融合，首次实现了对异构源数据的质量自评与动态加权，有效消除了不同数据格式、精度与时效差异带来的融合瓶颈；引入知识图谱推理补全隐含实体关系，实现对违规模式的深度解析，极大提高了系统对复杂生态异常事件的自动识别率和响应速度。

✦ Generated by Eureka AI based on patent content.

Smart Images

  • Figure CN121009324B_ABST
    Figure CN121009324B_ABST
Patent Text Reader

Abstract

The application provides a kind of natural reserve intelligent checking method and system based on multi-source data driving, it is related to environmental monitoring and information fusion technical field, including, data acquisition unit, for asynchronously obtaining and caching original monitoring data, adaptive preprocessing unit is connected with the data acquisition unit, for the original monitoring data Dynamic quality evaluation, weighted filtering based on quality score, unified space-time calibration and multi-modal tensor formatting are carried out, fusion engine unit is connected with the adaptive preprocessing unit.The natural reserve intelligent checking method and system based on multi-source data driving, through adaptive quality evaluation and cross-modal embedding fusion driven by contrast learning, for the first time realizes the quality self-evaluation of heterogeneous source data and dynamic weighting, effectively eliminates the fusion bottleneck caused by different data formats, precision and time difference.
Need to check novelty before this filing date? Find Prior Art

Citation Information

Patent Citations

  • Coal mining subsidence area identification and classification method based on multi-source data

    CN120032274A

  • Multi-modal large model federation training platform and heterogeneous data alignment algorithm

    CN120105464A