Carbon emission price combination prediction method

A combined forecasting and price forecasting technology, applied in special data processing applications, instruments, electrical digital data processing, etc., can solve the problem of low accuracy of forecasting results, achieve good noise robustness and improve accuracy.

Inactive Publication Date: 2015-12-16
HOHAI UNIV
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Problems solved by technology

[0004] Purpose of the invention: The present invention aims at the problem that the accuracy of prediction results in the existing carbon emission price prediction technology is not high, and provides a carbon emission price combination prediction method based on VMD and SNN (Spiking Neural Network, SNN)

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Embodiment Construction

[0025] Below in conjunction with specific embodiment, further illustrate the present invention, should be understood that these embodiments are only used to illustrate the present invention and are not intended to limit the scope of the present invention, after having read the present invention, those skilled in the art will understand various equivalent forms of the present invention All modifications fall within the scope defined by the appended claims of the present application.

[0026] The idea of ​​the present invention is as follows: first, the VMD algorithm is used to decompose the original carbon emission price sequence to obtain a series of IMF components, which can accurately capture the inherent complex characteristics of the carbon price. Secondly, SNN is introduced into the prediction of each component, and its good nonlinear function approximation ability and powerful computing power are used to improve the prediction accuracy of each component carbon price seque...

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Abstract

The invention discloses a carbon emission price combination prediction method. The method includes the steps that 1, an original carbon emission price sequence is decomposed into a series of intrinsic function components through a variation mode decomposition algorithm; 2, an output variable is given, the input variable of each IMF component is determined through statistical tools comprising a partial autocorrelation function and a corresponding partial autocorrelation diagram thereof; 3, each IMF component is predicted through a Spiking neural network; 4, prediction results of all the IMF components are superimposed to obtain a predicted value corresponding to an original carbon emission price. By means of the method, prediction precision is effectively improved, and carbon emission price prediction can be well achieved.

Description

technical field [0001] The invention relates to a carbon emission price combination forecasting method, for CO 2 Precise prediction of emission price belongs to the field of information analysis and prediction technology in power system technology. Background technique [0002] The global warming caused by the excessive consumption of fossil fuels has become a major challenge to the current social and economic development. It has become the consensus and goal of all countries in the world to achieve a clean, efficient and low-carbon energy system. In 2005, the "Kyoto Protocol" agreement came into effect, marking the beginning of the use of market mechanisms to reduce greenhouse gas emissions, and the carbon trading market has developed rapidly around the world. As one of the main sources of carbon dioxide emissions, the power industry has huge emission reduction potential and obvious room for optimization. At present, many researches on electricity in the market environmen...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F19/00
Inventor 孙国强陈通卫志农孙永辉臧海祥朱瑛黄蔓云陈霜
Owner HOHAI UNIV
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