Polychronic time sequence similarity analysis method based on weighting BORDA counting method

A multivariate time series and time series technology, applied in computing, biostatistics, electrical digital data processing, etc., can solve problems such as inaccurate sorting of similar sequences, inability to fully reflect similarity gaps, and influence on similarity analysis results, etc.

Inactive Publication Date: 2014-01-01
HOHAI UNIV
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Problems solved by technology

Li Shijin and others proposed a similarity analysis of multivariate time series based on BORDA counting method [Li Shijin, Zhu Yuelong, Zhang Xiaohua et al. Similarity analysis of multivariate hydrological time series based on BORDA counting method[J]. Journal of Water Resources, 2009,40(3):378 -384.], but when using the BORDA counting method to sort multiple candidate similar subsequences...

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  • Polychronic time sequence similarity analysis method based on weighting BORDA counting method
  • Polychronic time sequence similarity analysis method based on weighting BORDA counting method

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[0013] 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.

[0014] Such as figure 1 Shown is a model diagram of the multivariate time series similarity analysis method of the present invention. After the multivariate time series is processed by PCA, the p-dimensional principal component sequence is retained, and the similarity analysis method of the selected univariate time series is used to analyze the similarity of each dimensional univariate time series, and then the dimensional univariate time series are pruned to generate multivariate Candidate simil...

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Abstract

The invention discloses a polychronic time sequence similarity analysis method based on a weighting BORDA counting method. The method comprises the steps of conducting PCA processing on polychronic sequences to be inquired and inquired sequences, reserving front p-dimensional principal component sequences with the characteristic value contribution rate reaching a certain threshold value (such as 80% and 95%), forming the p-dimensional principal component sequences, selecting a unitary time sequence similarity analysis method from existing time sequence similarity analysis methods according to the specific analysis requirements (such as sequence form similarity and distorted time shafts), utilizing the selected time sequence similarity analysis method for conducting unitary time sequence similar analysis on each-dimensional sequences of the p-dimensional principal component sequences, obtaining unitary similar (sequences) subsequences of the each-dimensional sequences, trimming the unitary similar (sequences) subsequences, generating polychromic candidate similar (sequences) subsequences, and utilizing the weighting BORDA counting method for conducting voting ranking on the candidate similar (sequences) subsequences to obtain the final similar (sequences) subsequences. The method is suitable for k-neighbor similarity inquiry of the complete sequences and the subsequences.

Description

technical field [0001] The invention relates to a method capable of performing similarity analysis of multivariate time series, in particular to a multivariate time series k-nearest neighbor analysis method based on a weighted BORDA counting method, which belongs to the technical field of data mining. Background technique [0002] With the development of information acquisition, transmission and storage technologies, a large amount of time series data has been generated, such as hydrological information, including water level, flow, evaporation, etc., stock information in the financial field, including opening price, closing price, average price, etc. The brain wave data (EEG) used for diagnosis in the medical field includes the use of multiple sensor information, etc. These data contain several or even dozens or hundreds of variables, which contain rich domain knowledge and laws. Using artificial intelligence and data mining techniques to discover knowledge in time series f...

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Application Information

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IPC IPC(8): G06F17/30
CPCG16B40/00
Inventor 王继民朱跃龙李士进万定生冯钧
Owner HOHAI UNIV
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