Unlock instant, AI-driven research and patent intelligence for your innovation.

Linear classification model defect occurrence prediction method

A linear classification and prediction method technology, applied in the field of machine learning, can solve problems such as uneven data quality, large data volume of capacitive equipment, complex data characteristics, etc., and achieve the effect of improving performance

Inactive Publication Date: 2019-10-18
UNIV OF ELECTRONICS SCI & TECH OF CHINA
View PDF0 Cites 1 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Due to the explosive growth of current power grid data and the emergence of various sensors, the data volume of capacitive equipment is huge, the data characteristics are complex, and the data quality is uneven. It is difficult to directly apply traditional statistical methods to obtain ideal results.

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
  • Linear classification model defect occurrence prediction method

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0019] The technical solution of the present invention will be further described in detail below in conjunction with the accompanying drawings, but the protection scope of the present invention is not limited to the following description.

[0020] Such as figure 1 As shown, first, data cleaning is performed on missing values, duplicate values, wrong values, and dirty data in wrong format on the basis of the original data. Secondly, the scorecard model method in the financial field is applied to the capacitive data in this paper to improve feature encoding and construct a WOE feature encoding dataset based on the scorecard model. Then the data balance method solves the problem of sample data imbalance. Finally, the linear classification machine learning algorithm is applied to the defect level prediction, and the supervised learning method is used to train the model and optimize the parameters. The optimal defect level prediction model is obtained. Specifically, this method ...

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 a linear classification model defect occurrence prediction method. The method comprises the following steps: 1, loading a defect data set; 2, selecting training sample data; 3,constructing a linear classification defect occurrence prediction model; 4, based on a linear discriminant analysis algorithm, inputting the training sample data into a linear classification defect generation prediction model for supervised training; and 5, inputting the test sample set to the defect occurrence prediction model, and outputting a prediction result. According to the invention, a linear classification model defect occurrence prediction method can be realized.

Description

technical field [0001] The invention relates to the field of machine learning, in particular to a method for predicting the occurrence of defects in a linear classification model. Background technique [0002] In the power system, capacitive equipment belongs to power transmission and transformation equipment, and its quantity is large, accounting for about 40% to 50% of the total substation equipment, including current transformers, bushings, coupling capacitors, capacitive voltage transformers, etc. It occupies an extremely important position in power system equipment. The healthy operation of capacitive equipment and the safety of electrical equipment are crucial to substations. If a defect occurs, it will have a great impact on the entire substation. Some accidents may even endanger the personal safety of personnel and the safety of other surrounding equipment, causing great Loss. Therefore, a good prediction method that can accurately identify the defect level of capa...

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): G06Q10/04G06K9/62
CPCG06Q10/04G06F18/2155G06F18/2451
Inventor 郑泽忠谢乐牟范侯安锴江邵斌马鹏程
Owner UNIV OF ELECTRONICS SCI & TECH OF CHINA