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Power grid investment capability prediction method based on PLS-SVM-GA algorithm

A PLS-SVM-GA, forecasting method technology, applied in forecasting, computing, energy industry and other directions, can solve problems such as affecting accuracy, and achieve the effect of improving accuracy, eliminating noise interference, and solving regression modeling problems

Pending Publication Date: 2022-04-12
STATE GRID ELECTRIC POWER ECONOMIC RES INST IN NORTHERN HEBEI TECH CO LTD +1
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Problems solved by technology

However, the comprehensive evaluation method has a lot of subjectivity in the judgment of the importance of indicators, and the factors affecting the investment of power grid enterprises are usually nonlinear, which greatly affects the accuracy of prediction

Method used

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  • Power grid investment capability prediction method based on PLS-SVM-GA algorithm
  • Power grid investment capability prediction method based on PLS-SVM-GA algorithm
  • Power grid investment capability prediction method based on PLS-SVM-GA algorithm

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Embodiment Construction

[0028] The present invention will be further described below in conjunction with the accompanying drawings and embodiments.

[0029] See figure 1, the method for predicting power grid investment capacity based on the PLS-SVM-GA algorithm provided by the present invention includes: obtaining influencing factors of power grid investment capacity; performing preliminary selection of variables according to the degree of gray correlation; extracting principal components according to the characteristics of the partial least square method; Input the principal components into the support vector machine to construct the training sample set; optimize the parameters according to the genetic algorithm; fit the evaluation effect; predict the investment capacity of the power grid. The present invention can analyze from the inside and outside angles of the industry, and use the GA-PLS-SVM model to measure and calculate each index and the investment capacity of the grid.

[0030] In order to...

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Abstract

The invention discloses a power grid investment capability prediction method based on a PLS-SVM-GA algorithm. The method comprises the following steps: S101, determining initial influence factors of the investment capability of a power grid enterprise; s102, performing preliminary selection of variables according to grey correlation degree analysis; s103, extracting the initial influence factors by using principal component analysis in a partial least square method; s104, using the extracted components to construct a training sample set through a support vector machine model; s105, optimizing parameters of the support vector machine by using a genetic algorithm; s106, evaluating the fitting effect of the power grid investment capability; and S107, predicting the investment capacity of the power grid by using the optimized support vector machine and outputting an evaluation index. The method gives consideration to the advantages of the support vector machine and the genetic algorithm, can better consider the influence of nonlinear factors, enables the model to have better robustness and prediction stability, and greatly improves the accuracy of a prediction result.

Description

technical field [0001] The invention relates to a method for predicting the investment capacity of a power grid, in particular to a method for predicting the investment capacity of a power grid based on a PLS-SVM-GA algorithm. Background technique [0002] Under the background of reforming and standardizing the operation mode of power grid enterprises, the research on the investment capacity of power grid enterprises is becoming more and more urgent. Reasonably and objectively grasping the investment ability of enterprises is one of the core contents of enterprise management strategy research. Moreover, with the gradual deepening of electricity marketization and system reform of power grid enterprises, the economic benefit factors of power grid enterprises account for an increasing proportion in investment decisions. Therefore, in order to meet the needs of power grid companies for capital project planning and budget management, it is necessary to adopt scientific methods t...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/62G06N3/12G06Q10/04G06Q40/06G06Q50/06
CPCY02P80/10
Inventor 张晓曼程序李红建耿鹏云陈太平安磊齐霞张妍刘宣路妍董海鹏曾凡梅相静张萌萌谢品杰
Owner STATE GRID ELECTRIC POWER ECONOMIC RES INST IN NORTHERN HEBEI TECH CO LTD
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