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Multi-target correlation degree division processing method for buoy data

A processing method and multi-objective technology, which is applied in the field of marine data division and processing, can solve problems such as unreported and inability to apply marine forecasting for disaster prevention and mitigation, and achieve the effect of promoting quality and improving forecasting accuracy.

Active Publication Date: 2017-07-04
SHANGHAI OCEAN UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, this system cannot be applied to scenarios such as ocean forecasting and disaster prevention and mitigation.
[0010] Therefore, there is an urgent need for a processing method in which buoys are stored in a micro-area manner and have high retrieval efficiency, but there is no report on this processing method at present

Method used

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  • Multi-target correlation degree division processing method for buoy data
  • Multi-target correlation degree division processing method for buoy data
  • Multi-target correlation degree division processing method for buoy data

Examples

Experimental program
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Embodiment 1

[0069] Such as figure 1 As shown, the steps of a multi-target relevance division processing method of buoy data of the present invention are as follows:

[0070] S01: Obtain typhoon and buoy data over the years;

[0071] S02: Build a buoy relationship diagram;

[0072] S03: Formulation of multi-objective problems;

[0073] S04: Build a customized NSGA-II algorithm for buoy data (non-dominated sorting genetic algorithm);

[0074] S05: Output a multi-target layout method suitable for buoy data.

Embodiment 2

[0076] The steps of constructing a buoy relationship graph of a method for dividing and processing buoy data by a multi-object correlation degree of the present invention are as follows:

[0077] A01: Calculation of the relationship between typhoon and buoy;

[0078] A02: Establish a threshold;

[0079] A03: Compare the Eros value of the two buoys with the threshold;

[0080] A04: Get the buoy relationship diagram.

[0081] In step A01, the specific steps are as follows:

[0082] A011: Calculation of the influence coefficient of typhoon wind direction on the buoy;

[0083] Let the longitude of the typhoon be LoT, the latitude as LaT, the longitude of the buoy as LoF, and the latitude as LaF; take the position of the typhoon at a certain moment as a circle, and the line of the typhoon and the typhoon, the angle with the direction of true north is Az; The angle in the 0 degree direction is At; the angle between the typhoon wind direction and the buoy is P;

[0084] First calculate Az, such ...

Embodiment 3

[0104] The steps of formulating the multi-object problem in the method for dividing and processing multi-object relevance degrees of buoy data of the present invention are as follows:

[0105] The buoy relationship graph is an undirected graph G, G=(V,E), where V={v i ;V i =1,2,...,|V|} is the set of |V| vertices in graph G, vi is the centroid coordinates of a given coordinate system in two-dimensional space; E={e ij ;I,j=1,2,...,|V|;i≠j;e ij =e ji } Is the set of |E| edges in graph G, e ij Connect fixed point v i With v j .

[0106] Each vertex vi and edge eij usually involves a combination of "weights", which are with

[0107] Partitioning graph G is to assemble all vertices into MN non-empty and disjoint partitions, that is, the number of partitions is {M 1 ,M 2 ,...,M MN },Here Represents the set of a part of the vertices in the k-th micro area in the graph G. In addition to the specified goals and constraints, the partition graph G also satisfies some other general con...

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Abstract

The invention relates to a multi-target correlation degree division processing method for buoy data. The multi-target correlation degree division processing method for the buoy data comprises the following steps of obtaining typhoon and buoy data over the years; constructing a buoy relation graph; performing multi-target problem formulation; constructing an NSGA-II algorithm (a non-dominated sorting genetic algorithm with an elite-preservation strategy) customized for the buoy data; and outputting a multi-target layout method suitable for the buoy data. The method has the advantages that all buoys in a sea area form the graph, and buoy distribution is partitioned into regions for storage; the buoy data correlation in micro-areas is maximized, the correlation between the micro-areas is minimized, the cross-micro-area communication time is minimized, and micro-area loads are balanced; an efficient retrieval mode is provided for ocean emergency early warning, forecast and typhoon data analysis, and the forecast precision is improved; and the quality of operational conventional forecast, the numerical model assimilation effect, correct making of disaster prevention and reduction and emergency forecast decisions, and guarantee capabilities of maritime activities such as rights safeguarding, law enforcement and the like are facilitated.

Description

Technical field [0001] The invention relates to the technical field of marine data division processing, in particular, to a division processing method for multi-object correlation degree of buoy data. Background technique [0002] The existing buoys can not be stored in a single point in the sea area in time to respond to the data acquisition of cross-sea disasters, and cannot provide fast and efficient data access services when marine disasters occur. The buoy's dependent disaster impact degree is constructed into a map, and the map division method is used to divide After application, the buoy data can be used more efficiently. The graph partition method is a method of clustering relevant and complex edge relationships according to the closeness between vertices. A good graph partition algorithm can provide a basis for the layout of data associations. [0003] In the unstructured graph multi-level division method METIS, the coarse graph method (Coarsening Phase) is used to gradua...

Claims

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Application Information

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IPC IPC(8): G06F19/00G06N3/12
CPCG06N3/126G16Z99/00Y02A90/10
Inventor 黄冬梅赵丹枫徐宸弋轩王建梅海彬王丽琳
Owner SHANGHAI OCEAN UNIV
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