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Big data-based user power consumption behavior analysis method

An analysis method and big data technology, applied in data processing applications, instruments, character and pattern recognition, etc., can solve the problem of not being able to identify whether a given data has a cluster structure, etc., and achieve the effect of accurate and rapid self-analysis

Inactive Publication Date: 2020-12-08
NORTHEAST DIANLI UNIVERSITY
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

However, the fuzzy C-means clustering algorithm cannot be directly processed. This algorithm cannot identify whether the given data has a cluster structure, and it also has a strong dependence on the selection of initial values.

Method used

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  • Big data-based user power consumption behavior analysis method
  • Big data-based user power consumption behavior analysis method
  • Big data-based user power consumption behavior analysis method

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0025] like figure 1 As shown, an analysis method of user electricity consumption behavior based on big data includes the following steps:

[0026] S1. Use the data mining module to mine the corresponding characteristic parameter set of user electricity consumption behavior in the large electric power database based on the preset electricity consumption behavior parameter model;

[0027] S2. The attribute reduction algorithm based on the class discrimination degree realizes the preprocessing of the user's electricity consumption behavior characteristic parameter set, and obtains the target user's electricity consumption behavior characteristic parameter set;

[0028] S3. Parallelized k-means algorithm based on SparkR to realize the characteristic parameter set of electricity consumption behavior of target users

[0029] analysis and output the corresponding analysis results.

[0030] In this embodiment, in the step S1, the electricity consumption behavior parameter model is ...

Embodiment 2

[0033] like figure 2 As shown, an analysis method of user electricity consumption behavior based on big data includes the following steps:

[0034] S1. Use the data mining module to mine the corresponding characteristic parameter set of user electricity consumption behavior in the large electric power database based on the preset electricity consumption behavior parameter model;

[0035] S2. The attribute reduction algorithm based on the class discrimination degree realizes the preprocessing of the user's electricity consumption behavior characteristic parameter set, and obtains the target user's electricity consumption behavior characteristic parameter set;

[0036] S3. Parallelized k-means algorithm based on SparkR to realize the characteristic parameter set of electricity consumption behavior of target users

[0037] analysis, and output the corresponding analysis results;

[0038] S4. Based on Hadoop running preset fuzzy neural network algorithm, realize prediction anal...

Embodiment 3

[0042] like image 3 As shown, an analysis method of user electricity consumption behavior based on big data includes the following steps:

[0043] S1. Use the data mining module to mine the corresponding characteristic parameter set of user electricity consumption behavior in the large electric power database based on the preset electricity consumption behavior parameter model;

[0044] S2. The attribute reduction algorithm based on the class discrimination degree realizes the preprocessing of the user's electricity consumption behavior characteristic parameter set, and obtains the target user's electricity consumption behavior characteristic parameter set;

[0045] S3. Parallelized k-means algorithm based on SparkR to realize the characteristic parameter set of electricity consumption behavior of target users

[0046] analysis, and output the corresponding analysis results;

[0047] S4. Draw a dynamic graph based on the analysis results of the characteristic parameter set ...

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Abstract

The invention relates to the field of electric power big data analysis, particularly to a big data-based user electricity consumption behavior analysis method, which comprises the following steps of S1, mining a corresponding user electricity consumption behavior characteristic parameter set in an electric power big database by adopting a data mining module based on a preset electricity consumption behavior parameter model; S2, preprocessing the user power consumption behavior characteristic parameter set based on an attribute reduction algorithm of inter-class discrimination to obtain a target user power consumption behavior characteristic parameter set; and S3, realizing analysis of the power consumption behavior characteristic parameter set of the target user based on a SparkR parallelization kmeans algorithm, and outputting a corresponding analysis result. According to the invention, autonomous analysis of power consumption behaviors of users can be realized accurately and rapidly,so that numerous and diverse power mass data can be converted into available data with information and commercial values.

Description

technical field [0001] The invention relates to the field of electric power big data analysis, in particular to a method for analyzing user electricity consumption behavior based on big data. Background technique [0002] With the continuous and in-depth application of computer and network technology in electric power enterprises, the data of electric power enterprises has accumulated more and more, and this part of data reflects the long-term operation status of power supply enterprises to a certain extent. The use of new technologies such as big data and cloud computing to explore the behavior and characteristics of large users of electricity, and to provide customized power services for large users has gradually become a key issue in the power market, and it can also bring new development and progress to the power industry. direction. [0003] The cluster analysis method is currently a commonly used method for analyzing user electricity consumption behavior, and the clus...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06Q10/06G06Q50/06G06K9/62
CPCG06Q10/063G06Q10/0635G06Q50/06G06F18/23213Y02P90/82
Inventor 毕楠沈学强滕志军李红彪田洪亮张秋实
Owner NORTHEAST DIANLI UNIVERSITY
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