Research on Automation Compilation Technology of Hydrological and Water Resource Monitoring Data
This paper delves deeply into the automation compilation technology of hydrological and water resource monitoring data,aiming to emphasize the pivotal role of modern science and technology in processing,interpreting,and forecasting intricate hydrological data.Initially,the study revisits conventional data compilation methodologies and analyzes their limitations in handling large-scale and multi-source data.Subsequently,the paper elaborates on several modern automation technologies,including machine learning,deep learning,big data techniques,cloud computing,and edge computing,and extensively discusses their application in data compilation.These technologies not only enhance the efficiency and accuracy of data processing,but also offer viability for better decision-making support and real-time response.
hydrology and water resourcesmonitoring dataautomationinformation fusioncompilation techniques
NETL
NSTL
万方数据
维普
