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Local node mining method based on distributed data stream processing

A data flow, distributed technology, applied in data processing applications, electrical digital data processing, special data processing applications, etc., can solve the problems of timeliness and classification accuracy that cannot meet actual application scenarios.

Pending Publication Date: 2019-10-08
NORTHEAST DIANLI UNIVERSITY
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AI Technical Summary

Problems solved by technology

At present, time series, Markov model, genetic programming algorithm, etc. are mainly used in equipment anomaly identification, and this kind of research is in the exploratory stage, and its timeliness and classification accuracy cannot meet the needs of actual application scenarios

Method used

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  • Local node mining method based on distributed data stream processing
  • Local node mining method based on distributed data stream processing
  • Local node mining method based on distributed data stream processing

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Embodiment Construction

[0096] In order to make the object, technical solution and advantages of the present invention clearer, the present invention will be further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described here are only used to explain the present invention, not to limit the present invention.

[0097] refer to figure 1 ,Such as figure 1 As shown, a local node mining method based on distributed data stream processing includes the following steps:

[0098] S1, data sequence selection;

[0099] S2, establishment of big data flow classification model;

[0100] S3, the mining method of local nodes;

[0101] S4, Central node mining method based on unbalanced data flow.

[0102] The step S1 includes selection of static data sequence and selection of gradient data sequence;

[0103] Selection of static data sequences:

[0104] In order to ensure the accurate identification of the operating...

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Abstract

The invention discloses a local node mining method based on distributed data stream processing. The local node mining method comprises the following steps: S1, selecting a data sequence; S2, establishing a big data stream classification model; S3, a local node mining method; and S4, a center node mining method based on the unbalanced data stream. According to the local node mining method, the problem of local node mining in power grid equipment online monitoring data stream distributed processing is solved based on the data stream cleaning method for the power grid equipment from the perspective of large data stream distributed processing.

Description

technical field [0001] The invention relates to data processing of power grid equipment, in particular to a local node mining method based on distributed data flow processing. Background technique [0002] At present, as the entire power grid is moving towards the direction of intelligence, informatization and network, various sensors and various automatic monitoring equipment are widely used in the power grid, which makes the automatic monitoring system in the power grid form a huge amount of monitoring in real time. data. According to statistics from relevant departments, as of 2013, the State Grid has installed a total of 182 million smart meters and completed the collection of electricity consumption data for 191 million users, making the automation system for electricity consumption data collection the largest in the world for electric energy. The metering automation system requires real-time acquisition of grid equipment monitoring data, so that the amount of data col...

Claims

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Application Information

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IPC IPC(8): G06F16/2458G06F16/28G06Q10/06G06Q50/06
CPCG06F16/2465G06F16/2474G06F16/285G06Q10/0635G06Q50/06
Inventor 娄建楼王磊时丹丹曲朝阳张鹏梁丰
Owner NORTHEAST DIANLI UNIVERSITY
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