An Intelligent Method of Real-time Flood Forecasting Based on Face Recognition Algorithm

Abstract

The present invention discloses a real -time flood forecasting intelligent method based on face recognition algorithms. By extracting and identifying the characteristic factor that affects the evolution of the flood, it clearly affects the factors and indicators of the flooding process of the field, and establishes a characteristic factor combination and historical field floods.One -to -one correspondence; by establishing a static parameter library, the combination of different feature factor, the matching relationship between the flood process and hydrological forecasting model and parameter of the scene; when facing the current floods, the current hydrological meteorological conditions and history are achieved through the face recognition algorithmThe matching of the farming process corresponds to the combination of feature factor combinations, and then realize the real -time forecast of the flood process.

Description

technical field [0001] The invention relates to a flood forecasting method, in particular to an intelligent real-time flood forecasting method based on a face recognition algorithm, and belongs to the technical field of hydrological forecasting. Background technique [0002] Hydrological forecasting is not only an important technical support for flood and drought disaster prevention, but also an important means for reservoir scheduling and efficient resource utilization. In recent years, my country's water conservancy industry has developed rapidly, and a large number of large and giant water conservancy projects have sprung up and have been completed and put into operation one after another. The batch construction of water conservancy projects, while exerting huge comprehensive benefits such as flood control, power generation, shipping, irrigation, water supply, and ecology, has also significantly changed the natural river channel pattern and the change law of production an...

AI Technical Summary

Problems solved by technology

This calculation method is simple, practical, and easy to understand, but it faces some problems, mainly reflected in: ① There is a bottleneck in improving the forecast accuracy. Within the existing methods and application scope, it is not easy for the flood forecast accuracy to reach the Class A standard (above 85%) , the watersheds and sections with the best application effect are also difficult to guarantee a higher level of forecasting; ② There are great difficulties in model selection. In the calculation process, the historical flood process is usually divided into the rate period and the inspection period, and a better forecast can be obtained in the rate period Model approaches for performance and precision, often underperforming in the test period

The above problems limit the further development and application of conventional flood forecasting methods to a certain extent, especially the further improvement and promotion of real-time flood forecasting accuracy faces multiple difficulties and challenges

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