Safety risk prediction method

Abstract

The invention discloses a security risk prediction method. The method comprises the steps of S1, preprocessing data; S2, obtaining high-frequency associated data in the data by using an Apriori algorithm; S3, establishing a risk prediction model for the associated data by using fuzzy logistic regression, and testing the risk prediction model; and S4, obtaining a prediction risk by using the prediction model. According to the method, the existing security risk early warning system can be upgraded; a mathematical model can be constructed by combining an information technology and data mining; six safety management comprehensive indexes are provided to correspondingly make up the existing six defects. The risk problems are prompted, warned and precisely warned in time, and mechanisms of pre-event monitoring management, event interruption cause loss stopping, after-event traceability responsibility investigation and system assessment and evaluation are perfected, so that accident loss is effectively reduced, accidents are blocked, and finally, safe production of the transportation industry is guaranteed.

Description

technical field [0001] The invention relates to the field of transportation safety risk assessment management and the technical field of data mining and analysis, in particular to a risk prediction method. Background technique [0002] As a key strategic industry of the national economy, the transportation industry is an important infrastructure of the national economy and an important factor restricting economic and social development. Transportation and related departments, including railway transportation, air transportation, sea transportation, etc. and manufacturing management departments involved in these industries, must well plan, build, control, operate and manage transportation, and conduct comprehensive analysis of safety risks that affect transportation. Efficient management and control, blocking accidents, reducing losses, and ensuring safety. Among them, advanced prevention is the key to safety management, and safety early warning is an important means and spe...

AI Technical Summary

Problems solved by technology

[0005] The depth and breadth of the early warning are not enough, the inspection is weak and the level is small, it is difficult to analyze the actual hidden dangers in the unit link in multiple dimensions, and the accuracy of the early warning still needs to be improved;

[0006] It mainly depends on the actual security situation, the manager's subjective awareness and experience judgment. The early warning area is too single and targeted, and lacks the necessary data support and theoretical basis;

[0007] Safety analysis is not highly intelligent, the results of safety analysis are not intuitive, the analysis results are fragmented, and there is no effective display of the impact of the exposure of issues such as integrity, criticality, impressionability, and imagery on the actual effect of early warning;

[0008] Without a clear management system and operating mechanism, it is difficult to form a scientific and continuous safety early warning system, the early warning time is low, the effect is slow, and there is no data support for the pre-assessment and post-event accountability mechanism;

[0009] Lack of effective tracking of early warning implementation, it is difficult to grasp the early warning implementation and management behavior of relevant early warning units, and it is impossible to clarify the degree of rectification of problems afterwards;

[0010] The relative isolation among the various systems makes a lot of useful information buried in massive data, and comprehensive analysis and early warning cannot be obtained, resulting in insufficient utilization of security big data

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