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Method for measuring the space-time multi-variant hydrological time series similarity

A hydrological time series and similarity measurement technology, applied in complex mathematical operations, instruments, climate change adaptation, etc., can solve the problem of lack of spatial dimension in the similarity measurement of hydrological multivariate time series

Active Publication Date: 2018-09-14
HOHAI UNIV
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Problems solved by technology

[0020] Purpose of the invention: In order to solve the problem that the existing similarity measure of hydrological multivariate time series lacks the spatial dimension, the present invention provides a method for measuring the similarity of spatiotemporal multivariate hydrological time series

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  • Method for measuring the space-time multi-variant hydrological time series similarity
  • Method for measuring the space-time multi-variant hydrological time series similarity
  • Method for measuring the space-time multi-variant hydrological time series similarity

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[0040] 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.

[0041] Such as Figure 7 As shown, the spatio-temporal multivariate hydrological time series similarity measurement method includes the following steps in turn:

[0042] (1) Rasterize the original rainfall data of the flood;

[0043] (2) The rasterized matrix data generated by step 1 utilizes the 2D-DTW algorithm to calculate the distance between the two rows of vectors in the two frames of each other in the two rainfall matrix sequences;

[0044] (3) Use the distance between the two-row row vec...

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Abstract

The invention discloses a method for measuring the space-time multi-variant hydrological time series similarity. The method comprises firstly rasterizing the original rainfall data of a flood to generate a rainwater distribution matrix map in each hour; and then calculating the 2D-DTW distance between two rainfall distribution matrix sequences. The method includes the similarity calculation methodof the two rainfall distribution matrices and the similarity measurement method for the rainfall distribution matrix sequence. By using the obtained distances between a standard template rainfall distribution matrix sequence and a test template rainfall distribution matrix sequence, it is determined that which one or more test floods are most similar to the standard template flood hydrological process. The test flood data most similar to the template flood hydrological process can be output.

Description

technical field [0001] The invention relates to a method for measuring similarity of spatio-temporal multivariate hydrological time series, and belongs to the technical field of hydrological data science. Background technique [0002] Mining of time-series data has attracted a great deal of attention in the research community over the past few decades. These studies have implications in many fields, from biology, physics, astronomy, medicine, nanotechnology and stock market analysis, among others. The earliest concept of sequence pattern was proposed by Agrawal and Srikant. Time sequence mining added time attributes to sequence pattern mining and association mining to mine the sequential connection between transactions in time. Discover some patterns that can reflect the connections and laws between transactions, and then predict the future development trend of transactions. Time series similar pattern mining mainly involves three issues: 1) feature representation; 2) simi...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/62G06F17/16
CPCG06F17/16G06F18/22Y02A10/40
Inventor 冯钧郭涛杭婷婷李晓东朱跃龙
Owner HOHAI UNIV
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