Thunderstorm kernel identification and tracing method based on hybrid clustering algorithm

A clustering algorithm and thunderstorm technology, applied in character and pattern recognition, computing, computer components, etc., can solve the problems of indistinguishable and far-distant noise points, and achieve good thunderstorm nucleus identification and good thunderstorm nucleus movement tracking Effect

Active Publication Date: 2018-09-11
安徽佳讯信息科技有限公司
View PDF7 Cites 18 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, when applied to the clustering of lightning data, the result is a cluster, not a "center", and the existing noise points cannot be distinguished
The key to the KMEANS algorithm is the selectio

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
  • Thunderstorm kernel identification and tracing method based on hybrid clustering algorithm
  • Thunderstorm kernel identification and tracing method based on hybrid clustering algorithm
  • Thunderstorm kernel identification and tracing method based on hybrid clustering algorithm

Examples

Experimental program
Comparison scheme
Effect test

Embodiment

[0052] The embodiment of the present invention selects the thunderstorm weather example data that occurred from 11:00 to 11:30 on July 14, 2017. On the spatial scale, the longitude variation range is 117°09'-119°13', and the latitude variation range is 31°51'-33°99'. A total of 521 lightning strikes occurred during this period. Divide the above data into equal intervals of 3 minutes on the time scale to divide the data set, as shown in Table 1.

[0053] Table 1 Statistical information of equal interval lightning data

[0054]

[0055]

[0056] distributed on the map as Figure 5 shown. The data displayed on the picture is the instantaneous picture of the 6-minute data during the time period from 11:15 to 11:21. The lightning location data is presented in a disorderly manner on the map, and the location and direction of movement of the thunderstorm nucleus cannot be seen. These positioning data are used as data sets and input into the DBSCAN algorithm for clustering. ...

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 thunderstorm kernel identification and tracing method based on a hybrid clustering algorithm. The method specifically includes the following steps of utilizing deployed thunder and lightning monitoring points to conduct exploration and record cloud-to-ground lightning data, conducting preprocessing on the recorded cloud-to-ground lightning data and dividing the data intolightning data sets of each equal time interval; adopting a GPS clock synchronization technology and an algorithm of time differences of arrival for figuring out spatial positioning coordinates of lightning according to the time differences of arrival of changeable radiation pulses of an electric field generated by the lightning to each station; on the basis of thunder and lightning positioning data figured out by means of the procedures above, utilizing a DBSCAN algorithm and a KMEANS algorithm to figure out the relevance of the thunder and lightning positioning data among a thunderstorm kernel center-of-mass coordinate position, the lightning frequency and a thunderstorm kernel. An experimental result indicates that the method can accurately reflect the change tendency of thunder and lightning on thunderstorm days, and great effects of identifying the thunderstorm kernel and movably tracing a thunderstorm are achieved.

Description

technical field [0001] The invention belongs to the field of lightning monitoring and relates to a thunderstorm nucleus identification and tracking method based on a hybrid clustering algorithm. Background technique [0002] With the development of electronic technology and computer technology, thunderstorm lightning activity monitoring has developed from traditional lightning location observation to complete recording of the detailed characteristics of lightning activity during the entire thunderstorm life history. On this basis, various lightning data based on the evolution of thunderstorm life history can be developed product. Lightning activity is an indicator of the strength of thunderstorm convective activity. Compared with meteorological radar detection of thunderstorm cloud precipitation particles, the potential of diagnosing the timeliness and accuracy of strong convective activity has attracted more and more attention. Monitoring of thunderstorm convective activit...

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): G06F17/30G06K9/62
CPCG06F18/23G06F18/23213
Inventor 张淑萍华德梅周松柏
Owner 安徽佳讯信息科技有限公司
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap