Looking for breakthrough ideas for innovation challenges? Try Patsnap Eureka!

Time sequence classification method and time sequence classification system

A technology of time series and classification methods, applied in the fields of instruments, character and pattern recognition, computer components, etc.

Inactive Publication Date: 2017-01-04
SUZHOU UNIV
View PDF0 Cites 2 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, because the GDTW kernel function only uses DTW as a distance measure, it simply replaces the Euclidean distance in the Gaussian kernel function, and ignores the more important offset path information in DTW, so the classification effect of the time series is not good enough. needs further improvement

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Time sequence classification method and time sequence classification system
  • Time sequence classification method and time sequence classification system
  • Time sequence classification method and time sequence classification system

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0044] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only some, not all, embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without making creative efforts belong to the protection scope of the present invention.

[0045] The embodiment of the present invention discloses a time series classification method, see figure 1 As shown, the method includes:

[0046] Step S11: Optimizing the GDTW kernel function in advance to obtain an improved GDTW kernel function. Among them, the improved GDTW kernel function is:

[0047] K ( x , y ) = Σ s = 1 ...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

PUM

No PUM Login to View More

Abstract

The invention discloses a time sequence classification method which comprises the following steps of optimizing a GDTW kernel function in advance, and obtaining an improved GDTW kernel function; by means of the improved GDTW kernel function, performing kernel transformation on a preset time sequence training sample set and a time sequence testing sample; and performing classification on kernel transformation data of the testing sample by means of a preset classification algorithm and a time sequence kind label in the kernel transformation data of the training sample, thereby obtaining kind of the time sequence testing sample. According to the time sequence classification method, in calculating an Euclidean distance between two time sequence elements by the improved GDTW kernel function, the Euclidean distance between two time sequence elements which satisfy an optimal offset path is calculated so that the improved GDTW kernel function keeps the offset path information between the time sequences, thereby further improving a subsequent classification effect. Additionally, the invention correspondingly discloses a time sequence classification system.

Description

technical field [0001] The invention relates to the technical field of time series classification, in particular to a time series classification method and system. Background technique [0002] Time series is an ordered sequence of various values ​​of a certain phenomenon or statistical index at different time points, arranged in chronological order. The classification of time series has always been the focus of researchers in the field of time series data mining. With the advent of the era of big data, it is particularly important to quickly and efficiently classify messy time series. Currently, classification algorithms for classifying time series mainly include nearest neighbor classifiers, support vector machines, and sparse coding algorithms. [0003] At present, when using the nearest neighbor classifier, support vector machine or sparse coding algorithm to classify time series, it is necessary to perform kernel transformation processing on the time series in advance...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

Application Information

Patent Timeline
no application Login to View More
IPC IPC(8): G06K9/62
CPCG06F18/24147G06F18/2411G06F18/214
Inventor 张莉陶志伟张召李凡长王邦军
Owner SUZHOU UNIV
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Patsnap Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Patsnap Eureka Blog
Learn More
PatSnap group products