Neural Network Flood Early Warning Device and Its Method Based on Dynamic Optimization

Abstract

The invention provides a dynamic optimization based neural network flood warning device and a method. The device comprises an information processing unit, an information collection module, a GPS satellite positioning module, a GIS geographic information module, a wireless network module and a client, wherein the information collection module, the GPS satellite positioning module, the GIS geographic information module and the wireless network module are connected with the information processing unit, and the client is connected with the wireless network module. The information processing unit is used for carrying out data assimilation on matched information, assimilated data comprises historical information data and implementation information data, a network flood forecasting model is established by using the historical information data, the established network flood forecasting model is corrected by using implementation information so as to acquire a dynamic network flood forecasting model, and a disaster evaluation result is outputted by using the network flood forecasting model; and the wireless network module sends the disaster evaluation result to the client. According to the invention, mountain flood disaster analysis and judgment are carried out timely and accurately through the network flood forecasting model, thereby providing a reliable basis for making and selecting defense solutions in real time.

Description

technical field [0001] The invention relates to the technical field of geographic detection, in particular to a dynamic optimization-based neural network flood early warning device and method thereof. Background technique [0002] Flood forecasting and warning is based on the objective law of flood formation, using the hydrological and meteorological data that has been mastered, to predict the flow and water level process of a certain section of the river in a certain period of time in the future (that is, the forecast period). Flood disaster is one of the major natural disasters in the world today, and the prevention and control of flood disaster is a common concern of all countries in the world. In the 1970s, the United States first proposed the concept of non-structural measures (Non-structural measures), that is, non-structural measures such as flood forecasting, flood control dispatching, flood diversion, flood detention, legislation, flood insurance, floodplain managem...

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Problems solved by technology

(4) Difference

However, the results obtained from the application of remote sensing monitoring of flood disasters in my country are basically limited to the submerged range and the spatial distribution of land use types in the submerged area, which is still far from the actual needs of flood control and disaster reduction early warning.

[0007] However, the existing flood warning method mainly collects information such as the water level of reservoirs and rivers, landslides, etc., and then uses the collected information combined with GPS satellite positioning, and then transmits the alarm information through the 3G network, and basically judges directly based on the observed data. Whether the flood is dangerous to the embankment, or whether it will cause the risk of submersion along the river basin, the forecast information of this forecast method is not accurate enough, and the content of the alarm information obtained is not rich and diverse.

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