Waterlogging modeling and analysis method based on FCM

Abstract

The invention discloses an FCM-based waterlogging modeling and analysis method, which constructs an FCM model of waterlogging through modeling, and analyzes the occurrence of waterlogging based on the urban rainfall variation trend and waterlogging depth of waterlogging-prone points obtained therefrom. The method proposed by the present invention combines the strong fuzzy information expression and reasoning ability of the fuzzy cognitive map, and the gene-level operation of the DNA-encoded genetic algorithm technology to construct the waterlogging FCM model; the constructed waterlogging FCM model carries out the historical waterlogging data Integrate analysis and utilization, so that the ability of analysis is enhanced. Theoretically, the construction of this model is not restricted by the geographical location of waterlogging occurrence, and only needs to combine the parameter changes of a single waterlogging point under actual conditions to obtain the dynamic change trend of each parameter; therefore, it has great reference value.

Description

technical field [0001] The invention relates to the technical field of weather prediction, in particular to an FCM-based waterlogging modeling analysis method. Background technique [0002] Flood disasters are the most threatening meteorological disasters among urban meteorological disasters. However, in recent years, many cities in my country have been frequently hit by heavy rains, which have caused serious waterlogging. In Shenzhen City alone, there are more than 260 waterlogging points, with an area of ​​more than 180 square kilometers. . Waterlogging brings huge harm: 1. Causes traffic paralysis, property loss, water and electricity communication failure; 2. Causes subway backflow, social order chaos, line leakage and sewer cover is lifted by the drainage pipe to form a coverless vortex, etc.; 3. Long-term waterlogging led to the collapse of the wall and the rampant disease and epidemics after the waterlogging. [0003] Because severe urban waterlogging will lead to th...

AI Technical Summary

Problems solved by technology

There is an unclear causal relationship between these many influencing factors, and there is a large amount of historical data for query. For this kind of system, when the expert experience cannot support the analysis, the water level monitoring data is used for waterlogging analysis, and the result is still disappointing. dissatisfied

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