Complex network construction method based on combination of mapping and density peak clustering

A complex network and density peak technology, which is applied in the field of complex network construction based on the combination of mapping and density peak clustering, can solve the problems of lack of sequence pattern description, inability to rule out the interference of redundant fluctuations, and adverse effects on analysis results, etc.
CN109766945APending Publication Date: 2019-05-17OCEAN UNIV OF CHINA
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Patent Information

Authority / Receiving Office
CN · China
Current Assignee / Owner
OCEAN UNIV OF CHINA
Publication Date
2019-05-17

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Abstract

The embodiment of the invention provides a complex network construction method based on combination of mapping and density peak clustering. The method comprises the steps of preprocessing a time sequence through a preprocessing algorithm combining mapping and density peak clustering; Constructing complex networks. According to the method, a preprocessing algorithm combining mapping and density peak clustering is used for optimizing construction of a complex network, the fluctuation mode of a time sequence can be described more accurately, effective information in data can be mined more deeply,and higher robustness is achieved on noise.
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Description

technical field

[0001] This application relates to the technical field of complex network construction, in particular to a complex network construction method based on the combination of mapping and density peak clustering. Background technique

[0002] As a method widely used in recent years, complex network has made achievements in many fields, especially in the mining of time series features, which has wide applicability. More importantly, complex networks can accurately describe the fluctuation patterns of time segments while describing the overall fluctuations, which helps to understand the fluctuation patterns and laws of time series more clearly. However, since the actual data often contains a lot of noise, directly using the original time series to construct the network will greatly interfere with the analysis results, so it is necessary to preprocess the data so that the nodes can express the key fluctuations in the time series more accurately and effectively model...

Claims

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