Fire risk and loss conversion system

Abstract

This invention provides a fire risk and loss conversion system, comprising a risk factor extraction module and a risk and loss conversion module. The risk factor extraction module extracts multiple fire risk factors from factory data. The risk and loss conversion module includes the following units: a parameter generation unit generates multiple basic risk parameters and multiple interactive risk parameters based on multiple historical fire risk data; a basic risk calculation unit performs weighted calculations on each fire risk factor using the basic risk parameters to generate a single risk value, which is then further integrated into a basic risk value; an interactive risk calculation unit calculates corresponding fire risk factors using the interactive risk parameters according to a simulated accident evolution mechanism to generate interactive risk coefficients; and a risk integration unit integrates the basic risk value and interactive risk coefficients to generate a comprehensive risk value.

Claims

1. A fire risk and loss conversion system, comprising: a risk factor extraction module for extracting a plurality of fire risk factors from factory data; and a risk and loss conversion module connected to the risk factor extraction module and comprising: a parameter generation unit for generating a plurality of basic risk parameters and a plurality of interactive risk parameters based on a plurality of historical fire risk data; and a basic risk calculation unit connected to the parameter generation unit for performing weighted calculations on the fire risk factors through the basic risk parameters to generate a single risk value for each of the fire risk factors, and integrating the single risk values ​​to generate a basic risk value; An interactive risk calculation unit, connected to the parameter generation unit, is used to calculate the corresponding fire risk factors through the interactive risk parameters according to a simulated accident evolution mechanism to generate at least one interactive risk coefficient, wherein the simulated accident evolution mechanism relates to the impact caused by the interaction between the fire risk factors; and a risk integration unit, connected to the basic risk calculation unit and the interactive risk calculation unit, is used to integrate the basic risk value and the at least one interactive risk coefficient to generate a comprehensive risk value.

2. The fire risk and loss conversion system as described in claim 1, wherein the parameter generation unit includes a parameter generation model, which is trained and updated by a machine learning algorithm based on the historical fire risk data to generate the basic risk parameters and the interactive risk parameters.

3. The fire risk and loss conversion system as described in claim 1, wherein the interactive risk calculation unit generates the at least one interactive risk coefficient according to the following formula:

3. Among them, Fn is an nth interaction risk coefficient; n is an nth interaction in the simulated accident evolution mechanism; Xa is the value of the first fire risk factor corresponding to the nth interaction among these fire risk factors; Xb is the value of the second fire risk factor corresponding to the nth interaction among these fire risk factors; Cn is the nth interaction risk parameter corresponding to the nth interaction among these interaction risk parameters.

4. The fire risk and loss conversion system as described in claim 1, wherein the interactive risk calculation unit generates the at least one interactive risk coefficient according to the following formula:

4. Among them, Fn is an nth interaction risk coefficient; n is an nth interaction in the simulated accident evolution mechanism; Xc is a fire risk factor among these fire risk factors that corresponds to the nth interaction; Cn is an nth interaction risk parameter among these interaction risk parameters that corresponds to the nth interaction.

5. The fire risk and loss conversion system as described in claim 1, wherein the risk integration unit includes a risk threshold, the risk threshold including an upper threshold and a lower threshold, and the overall risk value generated by the risk integration unit is between the upper threshold and the lower threshold.

6. The fire risk and loss conversion system as described in claim 1, wherein the risk and loss conversion module further includes a loss conversion unit connected to the risk integration unit, the loss conversion unit being used to convert the comprehensive risk value into a maximum possible loss index.

7. The fire risk and loss conversion system as described in claim 6, wherein the loss conversion unit includes a loss conversion model, which is trained and parameter-updated by a machine learning algorithm based on the historical fire risk data and corresponding multiple historical loss data, and is used to convert the comprehensive risk value into the maximum possible loss index.

8. The fire risk and loss conversion system as described in claim 1, further comprising a level conversion module connected to the risk integration unit in the risk and loss conversion module, the level conversion module being used to receive the comprehensive risk value and convert the comprehensive risk value into a fire risk level according to a fire risk level table.

9. The fire risk and loss conversion system as described in claim 7, further comprising a level conversion module connected to the loss conversion unit in the risk and loss conversion module, the level conversion module being used to receive the maximum possible loss index and convert the maximum possible loss index into a maximum possible loss level according to a maximum possible loss level table.

10. The fire risk and loss conversion system as described in claim 1, wherein the fire risk factors include a building structure, a combustible material, a factory process, a fire protection system, maintenance management, security measures, and an external risk.

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