Warning situation prediction method and warning situation prediction system based on Apriori algorithm

A police situation prediction and police situation technology, applied in the field of police situation prediction, can solve the problems of reducing regional security and stability, and not being able to achieve good prevention, so as to achieve the effect of strengthening patrol prevention and control and reducing the occurrence of police situations
CN105488588AInactive Publication Date: 2016-04-13ANHUI RUIXIN SOFTWARE CO LTD
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
ANHUI RUIXIN SOFTWARE CO LTD
Publication Date
2016-04-13
Estimated Expiration
Not applicable · inactive patent

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Abstract

The invention discloses a warning situation prediction method and a warning situation prediction system based on an Apriori algorithm. The method comprises the following steps of: performing hidden data mining for warning situation happening data through the Apriori algorithm, obtaining an association rule among the data, and modeling for the association rule to obtain a sequence model and a function expression; step 2, obtaining a predicted case occurrence rate for the happened warning situation according to the sequence model, and substituting into the function expression to obtain a function model. The warning situation prediction method and the warning situation prediction system based on the Apriori algorithm overcome a mode of often analyzing, studying and judging after the warning situation happens and passively disposing the warning situation in the past, and realize prediction of the warning situation.
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Description

technical field

[0001] The present invention relates to the field of police forecasting, in particular to a police forecasting method based on the Apriori algorithm and a system for forecasting polices using the method. Background technique

[0002] Data mining is a new technology that discovers and extracts hidden information from large databases or data warehouses, and has received extensive attention in the fields of artificial intelligence and databases. The discovery of association rules is an important research branch of data mining. The goal of association rule discovery is to determine the relationship between item sets (attributes) in the database. These association rules discovered from a large number of transaction records can help people make decisions.

[0003] Among all association rule mining algorithms, the famous algorithm is the Apriori algorithm proposed by R.Agrawal (Agrawal) et al. in 1993. This algorithm is the most influential algorithm for mining Bo...

Claims

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