Method for reducing fire false alarm rate based on GA-BP neural network algorithm

Abstract

The invention discloses a method for reducing a fire false alarm rate based on a GA-BP neural network algorithm, and relates to the technical field of fire alarm; the method includes obtaining sensordata related to a fire; using the sensor data as input of a BP neural network, determining the structure of the BP neural network, determining the weight w and bias b of the BP neural network througha genetic algorithm, training the BP neural network according to the weight w and bias b, obtaining a GA-BP neural network model, and enabling the GA-BP neural network model to judge whether a fire disaster is early warned or not according to real-time sensor data. Through joint judgment of multiple sensors, the error probability is reduced; a BP neural network is adopted as a model trained by known sample data by performing classifier and fire sample data training, and the robustness is improved; a GA algorithm is adopted to initialize the weight w and the bias b of the BP neural network, sothat the BP neural network is prevented from falling into a local optimal solution.

Description

technical field [0001] The invention belongs to the field of fire alarm technology, and in particular relates to a method for reducing fire false alarm rate based on GA-BP neural network algorithm. Background technique [0002] With the increase of modern fire and electricity consumption, the frequency of fires is getting higher and higher. Once a fire breaks out, unfavorable factors such as untimely fighting, lack of fire extinguishing equipment, panic and slow escape of the people present are likely to occur, which will eventually lead to heavy loss of life and property. Discussing the characteristics of family fires and fire prevention countermeasures has practical significance for preventing family fires and reducing fire losses. [0003] At present, various fire alarm systems have the problem of high false alarm rate. Fire false alarms can easily make people nervous and panic, and frequent false alarms will make users lose trust in the fire alarm system and even shut d...

AI Technical Summary

Problems solved by technology

[0008] The purpose of the present invention is to provide a method based on the GA-BP neural network algorithm for reducing the false alarm rate of fire, thereby solving the shortcoming that the existing fire alarm system has a high false alarm rate

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