An Urban Flood Early Warning System and Its Method Based on Radial Basis Function Neural Network Model

Abstract

The invention discloses an urban flood early warning system based on a radial basis function neural network model and a method thereof, including measuring urban road water accumulation by using an ultrasonic range finder, measuring urban river water level information by using a water level sensor, and collecting relevant The information is aggregated to the data collection terminal for preprocessing, and the processed relevant data is sent to the monitoring center server through the network. The server uses the radial basis function neural network model to predict and warn the urban flood situation, and sends the results to the relevant user's mobile terminal. Users can also log in to the server through the network to inquire about the flood situation in relevant places. The invention realizes automatic monitoring of urban road water accumulation and urban river water level changes, and performs prediction and early warning of urban flood conditions. It has the advantages of small error, high real-time performance, low cost, accurate early warning information, etc., and has good market prospects and Value.

Description

technical field [0001] The invention relates to an intelligent monitoring and early warning system and a method thereof, in particular to an urban flood early warning system and a method based on a radial basis function neural network model, and belongs to the technical field of ultrasonic detection and intelligent forecasting. Background technique [0002] In terms of urban flood early warning, at present, it mainly relies on manual observation and analysis. However, relying on manual observation will have disadvantages such as large errors, low efficiency, high cost, and difficulty in real-time monitoring. With the continuous development of the city, the urban structure is becoming more and more complex. If only relying on manual monitoring, it is difficult to meet the needs of urban development. [0003] The traditional automatic monitoring method solves the defects of manual observation by installing video monitors on the main arterial roads of the city and water level...

AI Technical Summary

Problems solved by technology

If only relying on manual monitoring, it is difficult to meet the needs of urban development

[0003] The traditional automatic monitoring method solves the defects of manual observation by installing video monitors on the main arterial roads of the city and water level gauges in major rivers, but it is difficult to achieve independent detection and early warning.

In addition, personnel are required to observe the information of various videos and water level gauges in real time, which is labor-intensive and cannot monitor urban road water accumulation, which is not conducive to the timely detection and treatment of urban floods

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