Default electricity risk model characteristic selection method and device and equipment

A feature selection method and a technology of default electricity consumption, applied in data processing applications, instruments, predictions, etc., can solve problems such as low accuracy of prediction models, increased calculation amount, and collinearity of independent variables

Active Publication Date: 2017-06-20
CHINA SOUTHERN POWER GRID COMPANY +1
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  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

This may lead to problems such as the selection of independent variables that have little or no influence on the dependent variable, and the collinearity of independent variables, which will lead to an increase in the amount of calculation in the modeling process
On the other hand,

Method used

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  • Default electricity risk model characteristic selection method and device and equipment
  • Default electricity risk model characteristic selection method and device and equipment
  • Default electricity risk model characteristic selection method and device and equipment

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Embodiment Construction

[0025] 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, but not to limit the present invention. In addition, it should be noted that, for the convenience of description, only some structures related to the present invention are shown in the drawings but not all structures.

[0026] figure 1 It is a flow chart of a feature selection method for a power default risk model provided in an embodiment of the present invention. The method of this embodiment can be executed by the device for selecting features of the risk model of electricity default, which can be realized by means of software, and can be loaded into the terminal device. refer to figure 1 , the feature selection method for the risk model of electricity default provided by this embodiment may include the following steps:

[...

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Abstract

The embodiment of the invention discloses a default electricity risk model characteristic selection method and device and equipment. The method comprises the steps that S101 the default electricity tag of a user and the characteristic factor of the user are acquired; S102 an LASSO penalty function is constructed according to the default electricity tag and the characteristic factor; S103 the LASSO penalty function is solved through modified LARS to acquire the valid set of arguments of the LASSO penalty function; and S104 the arguments are filtered according to a set filtering rule and the valid set, so as to acquire a selected characteristic factor. According to the technical scheme provided by the embodiment of the invention, the selection efficiency and the effectiveness of the characteristic factor are improved.

Description

technical field [0001] The embodiments of the present invention relate to a feature factor selection method, and in particular to a feature selection method, device and equipment for a power default risk model. Background technique [0002] The customer information of electric power enterprises involves massive data such as real-time power data of the metering automation system, GIS (Geographic Information System, geographic information system) data, power grid trend information, and 95598 customer service recordings. These data come from a wide range of sources, including internal data and external data, and there are many types of data. With the improvement of the informatization level of power grid enterprises, the in-depth development of mobile Internet and big data technology, the data related to customers has shown explosive growth. As technology advances. On the one hand, the application of electric power big data is to integrate information such as macroeconomics, p...

Claims

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Application Information

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IPC IPC(8): G06Q10/04G06Q10/06G06Q50/06
CPCG06Q10/04G06Q10/0635G06Q50/06
Inventor 陈丰王志英林火华张诗军李远宁杨漾黄聪朱杏传
Owner CHINA SOUTHERN POWER GRID COMPANY
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