Recently, the Ministry of Water Resources of China announced at the press conference for the "Water Conservancy Standard AI Large Model" that the model has been successfully put into use, marking a new stage of intelligent management in China's water conservancy standardization. Developed independently by the Chinese Academy of Water Sciences, this model integrates rich multi-source data, providing strong support for the formulation and management of standards in the water conservancy field.
This AI large model is based on the "SkyLIM" system and is equipped with a technical architecture that includes "massive knowledge base + DeepSeek/Qwen dual models + standard services." By applying cutting-edge technologies such as natural language processing, knowledge graphs, and multi-modal data fusion, it achieves digital management throughout the entire process of water conservancy standard formulation, implementation, and supervision. This innovation fills the gap in intelligent tools within China's water conservancy standardization field and demonstrates the application prospects of AI technology in water conservancy management.
Image Source Note: The image was generated by AI and licensed by MidJourney service provider.
It is understood that this model integrates over 1800 water conservancy and hydropower standards, more than 500 related laws, regulations, and policy documents. In addition, it also includes research results from the 13th Five-Year Plan and 14th Five-Year Plan periods, as well as papers from core journals such as the "Journal of Hydraulic Engineering" and "Advances in Water Sciences." It even covers nearly 10 years of water conservancy technology patents and directories of scientific and technological achievements promotion. These diverse data resources will provide abundant support for the formulation and management of standards.
In practical applications, the performance of the Water Conservancy Standard AI Large Model has been excellent. The accuracy rate of duplicate comparison exceeds 96.7%, the efficiency of standard compilation improves by 2.5 times, the efficiency of assessment and review increases by 3 times, and the accuracy rate of standard retrieval reaches over 99.5%, with efficiency increasing by 5 times. All of these effectively enhance the overall efficiency of water conservancy standard management, providing a solid guarantee for industry development.
Looking ahead, the Ministry of Water Resources will continue to increase its efforts in AI technology research and development, further expand resources and knowledge bases, and implement dynamic management. This will lay a more solid foundation for the intelligent management practice of water conservancy standards and inject new vitality into the modernization of China's water conservancy industry.