在智能灌区管理决策中应用知识图表
Shaonan Sun1, Yuqing Ding1, Guoyu Dong1
1School of Water Conservancy, North China University of Water Resources and Electric Power, Zhengzhou 450046, China.
Heliyon
|October 11, 2024
概括
本研究介绍了一种新的知识图和BERT+BiLSTM+CRF模型,以加强中国的智能灌区管理. 它整合了用于智能决策的数据,改善了信息共享和黄河转向灌区域的视觉管理.
科学领域:
- 农业工程 农业工程
- 水资源管理 水资源管理
- 人工智能在农业中的应用
背景情况:
- 中国的传统灌和排水管理面临诸多挑战,包括复杂的流程,分散的信息系统和有限的智能决策支持.
- 现有的系统在数据集成和资源共享方面扎,阻碍了智能灌区的高效管理.
- 黄河转向灌区,特别是河南省,需要改进管理策略.
研究的目的:
- 为智能灌区开发精细的智能管理决策系统.
- 解决传统灌管理中数据分散和辅助决策不足的问题.
- 提出一个新的概念,用于中国灌区的信息化建设.
主要方法:
- 使用河南省28个黄河转向灌区和州灌区项目报告的数据构建知识图.
- 在检查日志文本中应用BERT+BiLSTM+CRF模型用于智能实体识别 (灌项目,问题事件).
- 利用实体对齐技术将检查文本数据与知识图联系起来,并使用图形检索来生成决策解决方案.
主要成果:
- 成功构建了一个知识图,用于管理黄河转向灌区域的问题.
- 通过对特定灌区示例的验证和模型评估,证明了拟议的问题管理决策方案的可靠性.
- 简化了信息数据集成,并启用了智能灌区的视觉管理.
结论:
- 知识图和先进的人工智能模型的综合方法为智能灌区管理提供了可靠的解决方案.
- 开发的系统有效地解决了数据整合的挑战,并提高了决策能力.
- 这项研究为中国灌区的信息化和智能管理提供了一个新且有效的框架.
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