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Urban rainstorm disaster risk assessment method and system based on GA optimization BP neural network

A BP neural network and risk assessment technology, applied in the field of urban rainstorm disaster risk assessment based on GA-optimized BP neural network, can solve the problems of credibility, lack of impact assessment results, and unintuitive evaluation mechanism, etc., and achieve powerful nonlinear mapping Capability, weight and threshold optimization, effects of overcoming local minima

Pending Publication Date: 2021-07-27
NANJING NRIET IND CORP
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  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0005] The losses caused by rainstorm and flood disasters are the result of the interaction of many disaster influencing factors, and these influencing factors cannot be described by precise mathematical models
There are many deficiencies in the evaluation methods currently used, such as the evaluation mechanism is not intuitive enough, and some evaluation methods affect the credibility of the evaluation results due to the mathematical foundation itself.
At the same time, real-time dynamic risk assessment is urgently needed to prevent rainstorm and flood disasters, and the current real-time disaster risk assessment work is relatively scarce

Method used

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  • Urban rainstorm disaster risk assessment method and system based on GA optimization BP neural network
  • Urban rainstorm disaster risk assessment method and system based on GA optimization BP neural network
  • Urban rainstorm disaster risk assessment method and system based on GA optimization BP neural network

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Embodiment 1

[0056] The invention discloses a method for evaluating the risk of urban rainstorm disasters based on GA (Genetic Algorithm, Genetic Algorithm) optimized BP (backpropagation, backpropagation) neural network, referring to figure 1 , including the following steps:

[0057] S1. Establish a rainstorm disaster risk assessment system that includes the risk of disaster-causing factors, the sensitivity of disaster-forming environments, the vulnerability of disaster-affected bodies, and the ability to prevent and resist disasters.

[0058] Establishing a complete rainstorm disaster risk assessment index system is very important for predicting and assessing the occurrence of disaster risks. If the index construction is not comprehensive, it will lead to a large deviation between the assessment results and the actual situation. If the natural disaster risk is understood from the perspective of the system, its composition should first include the source of risk. The source of risk not on...

Embodiment 2

[0093] The invention discloses an urban rainstorm disaster risk assessment system based on GA optimized BP neural network, comprising:

[0094] The rainstorm disaster risk assessment system building module is used to establish a rainstorm disaster risk assessment system including the risk of hazards, the sensitivity of disaster-forming environments, the vulnerability of disaster-affected bodies, and the ability to prevent and resist disasters;

[0095]The risk level label generation module is used to generate risk level labels including four labels of extremely high risk, high risk, medium risk and low risk based on k-means clustering historical disaster loss data;

[0096] The rainstorm disaster risk assessment model building module is used to construct a GA optimized neural network rainstorm disaster risk assessment model according to the rainstorm disaster risk assessment system and risk level labels;

[0097] The result output module is used to input the real-time rainfall...

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Abstract

The invention discloses an urban rainstorm disaster risk assessment method and system based on a GA optimized BP neural network, relates to the technical field of urban rainstorm disaster risk assessment, and aims to solve the problems that an assessment mechanism is not visual enough, the reliability of an assessment result is insufficient, and real-time dynamic risk assessment is lacked in an assessment method adopted at present. According to the technical scheme, the method includes: establishing a rainstorm disaster risk assessment system including disaster-inducing factor dangerousness, disaster-pregnancy environment sensitivity, disaster-bearing body vulnerability and disaster prevention and disaster resistance; generating a risk level label based on k-means clustering historical disaster damage data; according to the rainstorm disaster risk assessment system and the risk level label, constructing a GA optimization neural network rainstorm disaster risk assessment model; and inputting the real-time rainfall into the rainstorm disaster risk assessment model to obtain a risk level label in a specific time period. According to the method and system, the evaluation comprehensiveness and accuracy are improved.

Description

technical field [0001] The invention relates to the technical field of urban rainstorm disaster risk assessment, in particular to a method and system for urban rainstorm disaster risk assessment based on GA optimized BP neural network. Background technique [0002] At present, the number of casualties and economic losses caused by natural disasters in my country is huge every year, among which disasters caused by rainstorms and derivative disasters are very common in cities. Risk assessment can not only provide reference for the utilization of urban land resources, but also play an important role in urban disaster prevention and mitigation. [0003] The risk assessment of rainstorm and flood disasters is to quantitatively assess and estimate the intensity and form of the risk occurrence. To carry out risk assessment, there must first be a risk source, that is, a natural disaster; second, there must be a risk carrier (disaster-bearing body), that is, human society. Natural di...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06Q10/06G06Q50/26G06K9/62G06N3/08
CPCG06Q10/0635G06Q10/067G06Q50/265G06N3/084G06F18/23213
Inventor 任禹蒙高梦宇张兴海
Owner NANJING NRIET IND CORP
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