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Method for measuring dynamic characteristic similarity of complex system

A technology with dynamic characteristics and complex systems, applied in instruments, electrical digital data processing, character and pattern recognition, etc., can solve problems such as changes in research results and unreliable research results, and achieve the effect of real-time monitoring

Pending Publication Date: 2020-04-10
HUAIHUA UNIV
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Problems solved by technology

[0004] The technical problem to be solved by the present invention is a method for measuring the similarity of the dynamic characteristics of complex systems. The use of the Heaviside step function will cause the recursive analysis results to have rigidity and binary value, resulting in unreliable research results and slight critical distances. Changes or changes in the length and location of the time series can lead to significant changes in the results of the study

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  • Method for measuring dynamic characteristic similarity of complex system
  • Method for measuring dynamic characteristic similarity of complex system
  • Method for measuring dynamic characteristic similarity of complex system

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Embodiment

[0051] The abnormal mutation of the dynamic characteristics of the stock market crash in China's Shanghai and Shenzhen A stock markets in 2015 was monitored, and the data were selected from the daily closing price data of the Shanghai Composite Index and the Shenzhen Composite Index from January 1, 1993 to September 21, 2018.

[0052] like figure 1As shown, it can be seen that: (1) the evolution behavior of the dynamic characteristics of the Shanghai and Shenzhen A-share markets has a large similarity; (2) around 2000, the dynamic characteristics of the Shanghai and Shenzhen A-share markets changed abnormally, At this stage, the country is officially preparing to launch the GEM and the way of issuing new shares has been changed from an approval system to an approval system, which has led to a high investment sentiment among investors. As the market environment changes, investors make adaptive responses, and the dynamics of the market also change accordingly; (3) From 2004 to 2...

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Abstract

The invention discloses a method for measuring dynamic characteristic similarity of a complex system. A recursive analysis result has rigidity and binary value property due to the fact that a Heaviside step function is used, so an unreliable research result is produced, the slight change of a critical distance or the change of the length and the position of a time sequence can cause the obvious change of a research result; a local binary model (LBP) and a texture similarity measurement Earth Mover's Distance model (EMD) are used to propose a new idea for texture analysis of a Gaussian recursive graph for complex system dynamics characteristic analysis, and on the basis, a method system for measuring the dynamic characteristic similarity of the complex system is constructed.

Description

technical field [0001] The invention relates to the field of monitoring and diagnosing abnormal states of complex dynamic systems, in particular to a method for measuring the similarity of dynamic features of complex systems. Background technique [0002] (1) With the development of computer technology, Eckmann (1987) and others constructed the recursive graph theory, which provides a highly operable method for phase space reconstruction and analysis of complex systems. The nonlinear time series analysis method based on recursive graph theory has been paid more and more attention by researchers in various fields, and has been successfully applied to many fields. It has been successfully applied to many fields, such as geology, ecology and biology, neuroscience, economic dynamics, industrial production, mechanical hazards and monitoring, medical fields, image processing and audio and video analysis. (2) However, the traditional recursive graph uses the Heavyside step functio...

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Application Information

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IPC IPC(8): G06F30/20G06F119/14G06K9/46G06K9/62
CPCG06V10/40G06V10/467G06F18/22
Inventor 李燕郝晓玲舒晓惠
Owner HUAIHUA UNIV
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