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Power grid evaluation index weight determining method

A technology for evaluating indicators and determining methods, applied in the fields of instruments, data processing applications, resources, etc.

Inactive Publication Date: 2017-04-19
STATE GRID CORP OF CHINA +3
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  • Description
  • Claims
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Problems solved by technology

[0006] In order to be able to solve the problem of accurate, objective and reasonable determination of the power grid evaluation index weight, the present invention provides a system based on the Spark platform and multivariable L 2 -A method for determining the weight of power grid evaluation indicators combined with the Boosting regression model

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Embodiment Construction

[0052] Embodiments of the present invention will be described in detail below in conjunction with the accompanying drawings.

[0053] A Spark platform and multivariable L 2 -The method for determining the weight of the power grid evaluation index combined with the Boosting model, such as figure 1 , Figure 2-3 shown, including:

[0054] After the data related to the power grid evaluation index is collected, it is stored in the memory space through RDD conversion, and the data is divided into blocks through the clustermanager, and then each block task is assigned to N working nodes (workers) for parallel processing. In the assigned data processing tasks, the present invention uses Neville method to process missing data, uses improved subtraction clustering to classify bad data, and calculates inconsistency rate to perform feature selection.

[0055] (1) Missing data processing based on Neville method

[0056] Let Z={z 1 ,z 2 ,…,z n} is the index weight sample data set, n...

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Abstract

The invention discloses a power grid evaluation index weight determining method which is very important to objectively and rationally determine the power grid evaluation index weight under the background of large data. The method provided by the invention comprises the steps that a Spark platform divides all data into a number of sub-data models; the efficiency of data processing is improved by parallel calculation; a data feature extraction method is used to derive valid data information; the acquired valid data information is input into a multivariable L2-Boosting regression model for training and learning, so as to acquire the trained multivariable L2-Boosting regression model; and test data are input into the multivariable L2-Boosting regression model for predicting to determine the power grid evaluation index weight. According to the invention, the L2-Boosting model is combined with a Spark data analysis framework; the power grid evaluation index weight is objectively and accurately determined; and the objectivity of the index weight value can be ensured.

Description

technical field [0001] The invention belongs to the field of power grid evaluation index weights, in particular, a system based on the Spark platform and multivariable L 2 -A method for determining the weight of the power grid evaluation index combined with the Boosting regression model. Background technique [0002] At present, my country is still in the period of economic development, and the construction of power system infrastructure is still facing enormous pressure. Grid planning and decision-making play a vital role in building the power system infrastructure. Although there have been some research results in the comprehensive optimization and decision-making methods of power projects in recent years, it is necessary to clarify candidate projects when using these optimization methods for analysis and decision-making. At present, in the proposal of my country's power grid construction projects and the determination of project priorities, subjective factors play a lea...

Claims

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Application Information

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IPC IPC(8): G06Q10/06G06Q50/06
CPCG06Q10/06393G06Q50/06
Inventor 杜振东李付林刘卫东牛东晓黄雅莉张笑弟何英静郁丹沈舒仪钱啸李春姚艳裴传逊周林
Owner STATE GRID CORP OF CHINA
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