Looking for breakthrough ideas for innovation challenges? Try Patsnap Eureka!

Electric power big data visualization oriented data mining method

A data mining and big data technology, applied in data processing applications, market data collection, instruments, etc.

Inactive Publication Date: 2016-04-13
STATE GRID TIANJIN ELECTRIC POWER +1
View PDF0 Cites 13 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, there is still a lack of effective data mining methods for power big data visualization.

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Electric power big data visualization oriented data mining method
  • Electric power big data visualization oriented data mining method
  • Electric power big data visualization oriented data mining method

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0044] The data mining method for electric power big data visualization provided by the present invention will be described in detail below with reference to the accompanying drawings and specific embodiments.

[0045] Such as figure 1 As shown, the data mining method for electric power big data visualization provided by the present invention includes the following steps executed in sequence:

[0046] Step 1) Get the collected data from a 1 ,a 2 ,...,A n Electricity marketing data set A composed of n data samples, of which data sample a i Is a multi-dimensional vector, divide the data clusters in the above n data samples into k categories, respectively C 1 ,C 2 ,...,C k , And then use the kernel function to map the divided data into the kernel space, and determine the center m of each cluster 1 ,m 2 ,...,M k ;

[0047] Step 2) Construct the kernel matrix corresponding to data set A: When calculating the dot product in the high-dimensional space, the kernel function is not calculated...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

PUM

No PUM Login to View More

Abstract

The invention discloses an electric power big data visualization oriented data mining method, comprising obtaining an electric power marketing data set A composed of n collected data samples: a1, a2, and the like, an; classifying the data clusters in the n data samples into K classes; mapping the classified data to a kernel space through a kernel function; determining the center of every cluster; constructing a kernel matrix corresponding to the data set A; reducing the scale of the kernel matrix; constructing class vectors for all data samples aj; rapidly calculating distances according to the reduced kernel matrix K * obtained in the previous step; updating the class vectors so as to redetermine the class attributions of the data samples aj. According to the electric power big data visualization oriented data mining method provided by the invention, effective clustering and classifying analysis is carried out to the marketing data; the user group is identified well; the classified user power consumption features are obtained; therefore, the foundation is laid for electric power marketing intelligence.

Description

Technical field [0001] The invention belongs to the technical field of electric power big data data fusion and processing, and particularly relates to a data mining method oriented to electric power big data visualization. Background technique [0002] Electricity is related to economic development, social stability, and people's lives. Changes in electricity demand are the "barometer" and "weathervane" of economic operation, which can truly and objectively reflect the development and trend of the national economy. According to McKinsey's "Big Data: The Next New Frontier in Innovation, Competition, and Productivity" report released in May 2011, data has penetrated into every industry and business functional area, and has gradually become an important production factor. For the power industry, real-time production data such as operating conditions, parameters, and equipment operating status involved in power production, equipment monitoring data collected by fieldbus systems, and ...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

Application Information

Patent Timeline
no application Login to View More
IPC IPC(8): G06Q10/06G06Q30/02G06Q50/06
CPCG06Q10/0637G06Q30/0201G06Q50/06
Inventor 章斌赵文清王扬何金赵长伟郭晓艳崔柏刘晨
Owner STATE GRID TIANJIN ELECTRIC POWER
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Patsnap Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Patsnap Eureka Blog
Learn More
PatSnap group products

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic, Popular Technical Reports.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap|About US| Contact US: help@patsnap.com