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Power grid investment prediction method and system

A forecasting method and power grid technology, applied in the field of investment forecasting, can solve problems such as difficulty in meeting forecast accuracy

Inactive Publication Date: 2018-03-30
STATE GRID CORP OF CHINA +3
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Problems solved by technology

Due to the many factors affecting power grid investment, simple linear regression and time series are difficult to meet the requirements of prediction accuracy

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  • Power grid investment prediction method and system
  • Power grid investment prediction method and system
  • Power grid investment prediction method and system

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Embodiment Construction

[0028] In order to make the purpose, technical solutions and advantages of the embodiments of the present invention more clear, the present invention will be further described in detail below in conjunction with the embodiments and the accompanying drawings. Here, the exemplary embodiments and descriptions of the present invention are used to explain the present invention, but not to limit the present invention.

[0029] Empirical mode decomposition, that is, EMD is a new adaptive signal time-frequency processing method proposed by Huang in 1998, which is mainly used to solve nonlinear and non-stationary problems; since the EMD theory was proposed, it has been used in transportation, earthquake, medical , Mechanical fault diagnosis and other fields have been widely used; in solving the prediction problem, EMD shows advantages different from ordinary prediction methods.

[0030] Please refer to Figure 1A As shown, the present invention specifically provides a grid investment f...

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Abstract

The invention provides a power grid investment prediction method and system. The prediction method includes the following steps: acquiring a power grid investment time sequence signal, and decomposingthe power grid investment time sequence signal into a plurality of IMF signals and a reminder through an EMD method; comparing the characteristic time scales of the IMF signals to obtain high-frequency component IMF signals and low-frequency component IMF signals; analyzing the high-frequency component IMF signals through a neural network prediction method to obtain a first prediction result; analyzing the low-frequency component IMF signals through a time sequence prediction method to obtain a second prediction result; analyzing the reminder through a regression model to obtain a third prediction result; and obtaining a power grid investment prediction result according to the first prediction result, the second prediction result and the third prediction result.

Description

technical field [0001] The invention relates to the field of investment forecasting, in particular to a grid investment forecasting method and system. Background technique [0002] Existing research on power grid investment forecasting mainly predicts power grid investment from two ideas. Part of the research is to directly predict the future grid investment by analyzing the change trend of grid investment over the years. This forecasting method is simple and requires less data, but it does not take into account that the change of grid investment is the joint action of many factors in the forecasting process, so there is an obvious deficiency in the forecasting accuracy. Another part of research is based on considering the impact of different factors on the amount of grid investment, and then predicting grid investment by studying the dependence between grid investment and factors. Since it is easier to grasp the changing trend of various influencing factors in the future,...

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Application Information

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IPC IPC(8): G06Q10/04G06Q10/06G06Q50/06
CPCG06Q10/04G06Q10/0639G06Q50/06
Inventor 刘开俊韩丰李晖彭冬薛雅玮张鹏飞龙望成赵朗李金颖李金超朱少闻向宇伟徐谦
Owner STATE GRID CORP OF CHINA