A Multivariate Time Series Similarity Measurement Method for Ocean Domain
A technology of multivariate time series and similarity measurement, applied in measurement devices, meteorology, complex mathematical operations, etc., can solve the problems of slow processing speed and increased data processing volume, and achieve the effect of reducing economic losses and casualties
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Embodiment 1
[0074] refer to figure 1 , the steps of a multivariate time series similarity measurement method oriented to the marine field of the present invention are as follows:
[0075] S1: Collect typhoon data;
[0076] S2: Preprocessing the typhoon data;
[0077] S3: describe the typhoon data;
[0078] S4: measure the similarity of typhoon data;
[0079] S5: Output similar to typhoon;
[0080] Wherein, said step S2 includes screening typhoon attributes and supplementary data, said step S3 includes moving direction representation, typhoon time series representation, and said step S4 includes typhoon attribute weight calculation, W-DTW distance calculation, W-DTW distance judgment.
Embodiment 2
[0082] The specific working steps of a multivariate time series similarity measurement method facing the ocean field of the present invention are as follows:
[0083] S1: Collect typhoon data
[0084] Collecting typhoon data includes collecting existing typhoon raw data and collecting typhoon data in the database.
[0085] S2: Preprocessing the typhoon raw data
[0086] S21: Screen typhoon attributes
[0087] Select the typhoon attributes that need to be considered. The typhoon attributes include intensity L, wind speed V, moving direction MD, moving speed MV, and pressure P;
[0088] S22: Supplementary data
[0089] The filtered typhoon attribute values are supplemented with null fields based on the before and after data.
[0090] S3: Describe typhoon data
[0091] S31: Indication of moving direction
[0092] Since the moving direction of the typhoon is represented by the sixteen-wind pattern, it is numericalized, referring to figure 2 , that is, there are 16 types ...
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