Fire-fighting disaster situation data checking method based on correlation principle

Abstract

The invention relates to a fire-fighting disaster situation data checking method based on a correlation principle, and belongs to the technical field of data analysis. According to the technical scheme, a total fire suppression amount i, a total emergency rescue amount m, a total social rescue amount h and a total dispatching amount j serve as input sources, Pearson product-moment calculation is carried out, and the method specifically comprises the following steps that 1, standard sample data are selected to calculate linear correlation coefficients; 2, selecting standard sample data to calculate a partial correlation coefficient; 3, calculating a fire data quality-oriented weighted correlation coefficient; and 4, according to the basic principle of mathematical statistics, the correlation coefficient is extremely strong correlation within 0.8-1.0, is strong correlation within 0.6-0.8, is medium correlation within 0.4-0.6, is weak correlation within 0.2-0.4, and is extremely weak correlation or no correlation within 0.0-0.2. According to the fire-fighting disaster situation data checking method based on the correlation principle, effective checking of disaster situation data is achieved, the condition of regional fire-fighting safety work can be objectively and truly reflected, and many beneficial influences are generated on healthy development of the fire-fighting career.

Description

technical field [0001] The invention relates to a method for checking fire disaster data based on the principle of correlation, and belongs to the technical field of data analysis. Background technique [0002] With the development of society and economy, various new business forms and new economic types are constantly emerging. After a fire occurs in a relevant place, how to more accurately describe, define and classify the fire attributes under the new situation, and apply cloud computing and big data technology for more accurate analysis and mining The mechanism and trend behind the fire has become a practical problem to be solved urgently, and how to verify the authenticity of fire statistics is the basis of various data analysis. The current fire authenticity verification faces the following problems: firefighting work has a strong social nature, and the government, departments, units and citizens are all responsible for firefighting work and assume different fire safet...

AI Technical Summary

Problems solved by technology

The current fire authenticity verification faces the following problems: firefighting work has a strong social nature, and the government, departments, units and citizens are all responsible for firefighting work and assume different fire safety responsibilities; It does not depend on people's will, especially some dead fire accidents have strong randomness and sporadic nature in time and space

Using four fire data to assess and evaluate fire protection work, the query accuracy is not high, once there is a problem of concealment and omission, it will lead to deviations in statistical data

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