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Method for predicating GDP (Gross Domestic Product) by applying electric power big data based on backward regression equation

A regression equation and big data technology, applied in forecasting, data processing applications, instruments, etc., can solve problems such as large errors, inability to provide time-sensitive forecast data, and low real-time performance

Inactive Publication Date: 2016-11-23
NANJING UNIV +1
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Problems solved by technology

[0002] The traditional method of forecasting GDP has low real-time performance and large errors, and cannot provide time-sensitive and high-precision forecast data, resulting in the inability to provide effective decision-making reference to the power and economic authorities

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  • Method for predicating GDP (Gross Domestic Product) by applying electric power big data based on backward regression equation
  • Method for predicating GDP (Gross Domestic Product) by applying electric power big data based on backward regression equation
  • Method for predicating GDP (Gross Domestic Product) by applying electric power big data based on backward regression equation

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Embodiment Construction

[0042] The technical scheme of the present invention will be described in further detail below in conjunction with the accompanying drawings and specific embodiments, so that those skilled in the art can better understand the present invention and implement it, but the examples given are not intended to limit the present invention.

[0043] A method for forecasting GDP based on the application of power big data based on the backward regression equation, comprising the following steps:

[0044] Step 1. Collect historical data:

[0045] A) Collect historical power consumption data of industrial enterprises in the area to be predicted, and the frequency of the data is quarterly;

[0046] B) Calculate the median of the average temperature in each season;

[0047] C) Calculate the number of days of holidays in each quarter;

[0048] D) Calculate the ex-factory price index of industrial products in each quarter to be predicted;

[0049] Step 2. Set variables:

[0050] A) Set the...

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Abstract

The invention discloses a method for predicating GDP (Gross Domestic Product) by applying electric power big data based on a backward regression equation. The method comprises the following steps: step 1, acquiring historical data; step 2, carrying out variable setting; step 3, carrying out logarithmic differential processing on variables on power utilization amount and the GDP of industrial enterprises; step 4, setting a forward regression equation and carrying out parameter estimation; and step 5, deducing a backward regression equation model by utilizing estimated parameter, wherein a calculation formula of a predicated value GDPt+1 of the GDP of the next period is as follows: GDPt+1= GDPt.exp(gdpt+1). The backward regression equation is deduced by utilizing a parameter estimated value of the forward regression equation, electric power data is deconstructed and an economic development condition of a region is predicated; and an effective modeling method and decision-making reference are provided for electric power and economy competent departments.

Description

technical field [0001] The invention relates to a method for forecasting GDP based on a backward regression equation using big data of electric power. Background technique [0002] The traditional method of forecasting GDP has low real-time performance and large errors, and cannot provide time-sensitive and high-precision forecast data, resulting in the inability to provide effective decision-making reference to the power and economic authorities. Contents of the invention [0003] In view of the above problems, the present invention provides a method for forecasting GDP based on the reverse regression equation using electric power big data, using the estimated value of the parameters of the forward regression equation to derive the backward regression equation, deconstructing the power data and using it to predict the regional economic development , to provide effective modeling methods and decision-making references for power and economic authorities. [0004] Taking Ji...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06Q10/04G06Q50/06
CPCG06Q10/04G06Q50/06
Inventor 胡广伟林辉柏凌杨旸杨金龙郑海雁金农
Owner NANJING UNIV
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