Marine front intelligent tracking method, equipment, medium and product

Abstract

The invention discloses an intelligent ocean front tracking method and device, a medium and a product, and relates to the field of ocean front tracking, and the method comprises the steps: obtaining a target frontal surface of a previous time node and a plurality of frontal surfaces to be judged of a later time node; determining a to-be-judged frontal surface which is most similar to the target frontal surface and marking the to-be-judged frontal surface as the most similar frontal surface in combination with a double maximum and minimum value method and a point-to-point, point-to-surface and surface-to-surface distance calculation sequence; determining a frontal surface tracking result based on the width of the most similar frontal surface, the width of the target frontal surface and the distance between the target frontal surface and the most similar frontal surface; the frontal surface tracking result is that the target frontal surface and the most similar frontal surface are the same ocean frontal surface, or the target frontal surface and the most similar frontal surface are different ocean frontal surfaces. According to the invention, more accurate ocean frontal surface tracking can be realized.

Description

Technical Field

[0001] The present application relates to the field of ocean front tracking, and particularly to an intelligent ocean front tracking method, device, medium and product. Background Art

[0002] In recent years, the huge energy carried by mesoscale phenomena in the ocean has been recognized as the main energy form in the ocean, which has generated a great demand for the tracking of one of its main manifestations: ocean fronts. Existing intelligent ocean front tracking algorithms, such as Lagrangian indicators and Long Short-term Memory Networks (LSTM), etc., have disadvantages such as using less information, small research scales, artificially setting threshold parameters, and poor continuity. Summary of the Invention

[0003] The purpose of the present application is to provide an intelligent ocean front tracking method, device, medium and product, which can achieve more accurate ocean front tracking.

[0004] To achieve the above purpose, the present application provides the following solutions: In the first aspect, the present application provides an intelligent ocean front tracking method, including: Obtain the target front at the previous time node and multiple fronts to be judged at the next time node; Combining the double maximum value method and the distance calculation order from point to point, point to surface, and surface to surface, determine one front to be judged that is most similar to the target front, and mark it as the most similar front; Based on the width of the most similar front, the width of the target front, and the distance between the target front and the most similar front, determine the front tracking result; the front tracking result is that the target front and the most similar front are the same ocean front, or the target front and the most similar front are different ocean fronts.

[0005] In the second aspect, the present application provides a computer device, including: a memory, a processor, and a computer program stored on the memory and executable on the processor, and the processor executes the computer program to implement the intelligent ocean front tracking method.

[0006] In the third aspect, the present application provides a computer-readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, the intelligent ocean front tracking method is implemented.

[0007] In the fourth aspect, the present application provides a computer program product, including a computer program, and when the computer program is executed by a processor, the intelligent ocean front tracking method is implemented.

[0008] According to the specific embodiments provided by the present application, the present application has the following technical effects: The present application provides a method, device, medium and product for intelligent tracking of ocean fronts, defining three distances (point-to-point, point-to-plane, and plane-to-plane distances), that is, the distances in the metric space in functional analysis. The most similar fronts between two time nodes before and after are determined through double maximum and minimum judgments, and then decisions are made based on the widths of the most similar front, the width of the target front, and the distance between the target front and the most similar front to determine whether they are the same front. Through the above steps, the present application realizes the integration of double maximum and minimum values and three-distance decision-making, solves problems such as the traditional ocean front tracking algorithm using less information, and can obtain better front tracking results. Moreover, since the two minimum values are accurately realized, optimization can be achieved, and more accurate front tracking results can be obtained. BRIEF DESCRIPTION OF THE DRAWINGS

[0009] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the following will briefly introduce the drawings required in the embodiments. Obviously, the drawings in the following description are only some embodiments of the present application. For those of ordinary skill in the art, without creative efforts, other drawings can also be obtained based on these drawings.

[0010] Figure 1 It is an application environment diagram of the method for intelligent tracking of ocean fronts in an embodiment of the present application.

[0011] Figure 2 It is a flowchart of the method for intelligent tracking of ocean fronts provided in an embodiment of the present application.

[0012] Figure 3 It is a schematic diagram for calculating the first distance and the second distance provided in an embodiment of the present application.

[0013] Figure 4 It is a schematic diagram for calculating the third distance and the front tracking result provided in an embodiment of the present application.

[0014] Figure 5 It is a schematic diagram of the structure of a computer device provided in an embodiment of the present application. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0015] The following will clearly and completely describe the technical solutions in the embodiments of the present application with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only some embodiments of the present application, rather than all embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative efforts belong to the scope of protection of the present application.

[0016] To make the objectives, features, and advantages of this application more obvious and understandable, the following provides a more detailed description of this application in combination with the accompanying drawings and specific embodiments.

[0017] The ocean front intelligent tracking method provided by the embodiments of this application can be applied to an application environment as Figure 1 shown. Among them, the terminal 102 communicates with the server 104 through a network. The data storage system can store the data that the server 104 needs to process. The data storage system can be set up separately, integrated on the server 104, placed on the cloud, or on other servers. The terminal 102 can send the front information of multiple time nodes to the server 104. After receiving it, the server 104 first determines the target front of the previous time node and multiple fronts to be judged of the next time node; then, in combination with the double maximum value method and the distance calculation order from point to point, point to surface, and surface to surface, it determines the front to be judged that is most similar to the target front and marks it as the most similar front; finally, based on the width of the most similar front, the width of the target front, and the distance between the target front and the most similar front, it determines the front tracking result. The server 104 can feedback the front tracking result to the terminal 102. In addition, in some embodiments, the ocean front intelligent tracking method can also be implemented separately by the server 104 or the terminal 102.

[0018] Among them, the terminal 102 can be, but is not limited to, various desktop computers, laptop computers, smartphones, tablet computers, Internet of Things devices, and portable wearable devices. The server 104 can be implemented by an independent server or a server cluster composed of multiple servers, and can also be a cloud server.

[0019] In an exemplary embodiment, as Figure 2 shown, an ocean front intelligent tracking method is provided. This method is executed by a computer device, and specifically can be executed separately by a computer device such as a terminal or a server, or jointly executed by a terminal and a server. In the embodiments of this application, taking this method applied to Figure 1 the server 104 as an example for description, it includes the following steps 201 to step 203.

[0020] Step 201, obtain the target front of the previous time node and multiple fronts to be judged of the next time node; among them, the time node can be every day, that is, it is necessary to obtain the front information of two adjacent days, or it can obtain the front information of multiple days within a certain time length, and then extract the front information of any two adjacent days as the data basis for subsequent processing, so as to realize the tracking and comparison of all fronts of two adjacent days, and further realize the front tracking of multiple days in the time series.

[0021] In addition, when obtaining the frontal information, it can be recorded and stored in the form of an EXCEL sheet. For example, in the EXCEL sheet, the first column is the serial number (such as 1, 2, 3, 4, 5...), the second column is the ID of the front, the third column is the width information of the front, the fourth column is the intensity information of the front, the fifth column is the length information of the front, and the sixth column and subsequent columns are the longitude and latitude information of each frontal point on the front. In subsequent calculations, the information in this EXCEL sheet can be directly called for calculation.

[0022] Step 202: Combine the double extreme value method and the distance calculation order from point to point, point to plane, and plane to plane to determine a frontal surface to be judged that is most similar to the target frontal surface, and mark it as the most similar frontal surface. In an application example, step 202 includes the following steps (21)-(25).

[0023] (21) Select any frontal surface to be judged as the current judged frontal surface.

[0024] (22) For any frontal point on the target frontal surface, calculate the distance between this frontal point and any frontal point on the current judged frontal surface, and mark it as the first distance; that is, the distance calculation from a point on one frontal surface to a point on another frontal surface is realized. Specifically, as Figure 3 shown, the calculation formula for the first distance is: .

[0025] Among them, represents the distance between the th frontal point of the target frontal surface j and the th frontal point of the current judged frontal surface , referring to the first distance; represents the resolution after converting longitude and latitude into distance; represents the longitude of the th frontal point of the target frontal surface j , represents the latitude of the th frontal point of the target frontal surface j ; represents the longitude of the th frontal point of the current judged frontal surface , represents the latitude of the th frontal point of the current judged frontal surface , M represents the number of frontal points of the current judged frontal surface , ; N represents the number of frontal points of the target frontal surface , .

[0026] Taking the target frontal surface Taking the first frontal point of as an example, the corresponding first distance is calculated by the formula: 1 represents the longitude of the first frontal point of the target frontal surface , 1 represents the latitude of the first frontal point of the target frontal surface .

[0027] (23) Take the minimum value among all the first distances as the distance between the frontal point and the current judged frontal surface, and label it as the second distance; that is, the process of determining the first minimum value is realized, and the distance calculation between a point and a surface is also realized. Specifically, the calculation formula of the second distance is: .

[0028] Among them, represents the distance between the th j frontal point of the target frontal surface and the current judged frontal surface , referring to the second distance; refers to the first distance.

[0029] Taking the first frontal point of the target frontal surface as an example, the corresponding second distance is calculated by the formula: .

[0030] Among them, represents the distance between the first frontal point of the target frontal surface and the current judged frontal surface , referring to the second distance; refers to the first distance corresponding to the first frontal point of the target frontal surface .

[0031] (24) Average the second distances corresponding to all the frontal points on the target frontal surface to obtain the distance between the target frontal surface and the current judged frontal surface, and label it as the third distance; that is, the distance calculation process between the frontal surface at the previous time node and the frontal surface at the next time node is realized. Specifically, as Figure 4 shown, the calculation formula of the third distance is: .

[0032] Among them, represents the distance between the target frontal surface and the current judged frontal surface , referring to the third distance; represents the j ​​The distance between a frontal point and the current judged frontal surface The distance between them

[0033] (25)According to the third distance corresponding to any one of the to-be-judged frontal surfaces, select the to-be-judged frontal surface with the smallest third distance as the to-be-judged frontal surface most similar to the target frontal surface, and mark it as the most similar frontal surface. That is, the determination process of the second minimum value is realized. Specifically, the calculation formula of the most similar frontal surface is: .

[0034] Among them, represents the most similar frontal surface; represents the target frontal surface and the to-be-judged frontal surface The distance between them, P represents the number of to-be-judged frontal surfaces, ; argmin () represents the value of the independent variable when finding the minimum value of the function value

[0035] In addition, the distances obtained in the above calculations all refer to geographical distances (km).

[0036] Step 203, based on the width of the most similar frontal surface, the width of the target frontal surface, and the distance between the target frontal surface and the most similar frontal surface, determine the frontal surface tracking result; the frontal surface tracking result is that the target frontal surface and the most similar frontal surface are the same ocean frontal surface, or the target frontal surface and the most similar frontal surface are different ocean frontal surfaces

[0037] When the target frontal surface and the most similar frontal surface are different ocean frontal surfaces, it indicates that the target frontal surface does not appear at the later time node and has disappeared. In practical applications, the target frontal surface can be marked at the previous time node and marked as the last time node of this frontal surface

[0038] In a specific application, perform an average calculation based on the width of the most similar frontal surface, that is, the width of the target frontal surface, and then compare the obtained average value with the distance between the target frontal surface and the most similar frontal surface. If the distance between the target frontal surface and the most similar frontal surface is less than or equal to the obtained average value, it indicates that the target frontal surface and the most similar frontal surface are the same ocean frontal surface; if the distance between the target frontal surface and the most similar frontal surface is greater than the obtained average value, it indicates that the target frontal surface and the most similar frontal surface are different ocean frontal surfaces. Specifically, the function formula of the frontal surface tracking result is: : indicates that the target frontal surface and the most similar frontal surface are the same ocean frontal surface; : indicates that the target frontal surface and the most similar frontal surface are different ocean frontal surfaces; among them, represents the target frontal surface The distance to the most similar frontal surface is denoted as the width of the target frontal surface and the width of the most similar frontal surface is denoted as

[0039] In another exemplary embodiment of the present application, there are five frontal points for the target frontal surface at the previous time node and four frontal points for the frontal surface to be judged at the later time node. The corresponding intelligent tracking process of the oceanic front is as follows: As Figure 3 shown, for the first frontal point on the target frontal surface , calculate its first distance from each point on the current judged frontal surface : , it can be seen from Figure 3 that the minimum value appears at . Therefore, the second distance from the first frontal point on the target frontal surface to the current judged frontal surface is . As Figure 4 shown, the average of the second distances of the five frontal points on the target frontal surface can be used to obtain the third distance between the two frontal surfaces: .

[0040] If the current judged frontal surface is already the frontal surface closest to the target frontal surface among the frontal surfaces at the later time node (such as the next day), then subsequent decisions can be made. It can be clearly seen from Figure 4 that , so they are different oceanic frontal surfaces

[0041] In an application example, the tracking results of multiple frontal surfaces for two adjacent days with a longitude and latitude range of 105 - 118°E, 4 - 21°N can be collected. Numbers are marked on the frontal surfaces to represent their IDs, and the same ID represents the same oceanic frontal surface. When tracking for consecutive days, the tracking can be displayed through the IDs of the frontal surfaces. If the ID of a certain frontal surface disappears at the later time node, it can indicate that the frontal surface has disappeared

[0042] In summary, the present application relates to the fields of functional analysis, optimization methods, and intelligent identification of mesoscale phenomena in the ocean. It provides an optimized tracking algorithm that does not require setting thresholds, has strong robustness, and combines physical oceanography knowledge, meeting actual requirements. In addition, three distances, namely point-to-point, point-to-surface, and surface-to-surface, are defined, which progress step by step. Mathematically, it can be strictly verified that these distances satisfy the three properties of distance in a metric space: positive definiteness, symmetry, and triangle inequality. Therefore, they can be incorporated into the framework of functional analysis and used for other tracking problems, with a wide range of applications

[0043] In an exemplary embodiment, a computer device is provided. The computer device can be a server or a terminal, and its internal structure diagram can be as shown in Figure 5 . The computer device includes a processor, a memory, an input / output interface (Input / Output, abbreviated as I / O), and a communication interface. Among them, the processor, the memory, and the input / output interface are connected through a system bus, and the communication interface is connected to the system bus through the input / output interface. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program, and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The input / output interface of the computer device is used to exchange information between the processor and external devices. The communication interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, it realizes the method for intelligent tracking of ocean fronts.

[0044] Those skilled in the art can understand that Figure 5 the structure shown in is only a block diagram of some structures related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine some components, or have different component arrangements. In an exemplary embodiment, a computer device is provided, including a memory and a processor. A computer program is stored in the memory, and when the processor executes the computer program, it realizes the steps in the above method embodiments.

[0045] In an exemplary embodiment, a computer-readable storage medium is provided, storing a computer program, and when the computer program is executed by a processor, it realizes the steps in the above method embodiments.

[0046] In an exemplary embodiment, a computer program product is provided, including a computer program, and when the computer program is executed by a processor, it realizes the steps in the above method embodiments.

[0047] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data for analysis, stored data, displayed data, etc.) involved in the present application are all information and data authorized by the user or fully authorized by all parties, and the collection, use, and processing of relevant data need to comply with relevant regulations.

[0048] Those of ordinary skill in the art can understand that all or part of the processes in the methods of the above embodiments can be completed by instructing relevant hardware through a computer program. The computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above methods. Among them, any reference to a memory, database, or other medium used in the embodiments provided in the present application can include at least one of non-volatile and volatile memories. Non-volatile memories can include read-only memory (ROM), magnetic tapes, floppy disks, flash memories, optical memories, high-density embedded non-volatile memories, resistive random access memories (ReRAM), magnetoresistive random access memories (MRAM), ferroelectric random access memories (FRAM), phase change memories (PCM), graphene memories, etc. Volatile memories can include random access memory (RAM) or external cache memories, etc. By way of illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM), etc.

[0049] The databases involved in the embodiments provided in the present application can include at least one of relational databases and non-relational databases. Non-relational databases can include distributed databases based on blockchain, etc., without limitation. The processors involved in the embodiments provided in the present application can be general-purpose processors, central processors, graphics processors, digital signal processors, programmable logics, data processing logics based on quantum computing, etc., without limitation.

[0050] The technical features of the above embodiments can be combined arbitrarily. For the sake of concise description, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, it should be considered as the scope described in this specification.

[0051] Specific examples are used in this article to elaborate on the principles and implementation manners of the present application. The description of the above embodiments is only used to help understand the method and its core idea of the present application; at the same time, for those of ordinary skill in the art, according to the idea of the present application, there will be changes in the specific implementation manners and application scopes. In summary, the content of this specification should not be construed as a limitation to the present application.

Claims

1. A method for intelligent tracking of ocean fronts, characterized in that: The ocean front intelligent tracking method comprises: Obtaining a target front at a previous time node and multiple fronts to be judged at a next time node; Combining the double extremum method and the order of calculating the distances from point to point, point to surface, and surface to surface, a front to be judged that is most similar to the target front is determined and marked as the most similar front; Based on the width of the most similar front, the width of the target front and the distance between the target front and the most similar front, the front tracking result is determined; the front tracking result is that the target front and the most similar front are the same ocean front, or the target front and the most similar front are different ocean fronts.

2. The method for intelligent tracking of ocean fronts according to claim 1, characterized in that: Combining the double extremum method and the point-to-point, point-to-surface, and surface-to-surface distance calculation sequence, a front to be judged that is most similar to the target front is determined and marked as the most similar front, including: Select any front to be judged as the current judging front; For any front point on the target front, calculate the distance between the front point and any front point on the current evaluation front, and mark it as a first distance; The minimum value among all the first distances is used as the distance between the front point and the current evaluation front, and is marked as the second distance; The second distances corresponding to all front points on the target front are averaged to obtain the distance between the target front and the current evaluation front, and marked as the third distance; According to the third distance corresponding to any of the fronts to be judged, the front to be judged with the smallest third distance is selected as the front to be judged that is most similar to the target front and is marked as the most similar front.

3. The method for intelligently tracking ocean fronts according to claim 2, characterized in that: The calculation formula of the first distance is: ； in, Indicates the target front No. j Front points and current judgment front No. The distance between the front points refers to the first distance; Indicates the resolution of distance converted from longitude and latitude; Indicates the target front No. j The longitude of the front point, Indicates the target front No. j The latitude of the front; Indicates the current evaluation front No. The longitude of the front point, Indicates the current evaluation front No. The latitude of the front point, M represents the current frontal point The number of front points, ; N Indicates the target front The number of front points, .

4. The method for intelligently tracking ocean fronts according to claim 2, characterized in that: The calculation formula of the second distance is: ； in, Indicates the target front No. j Front points and current judgment front The distance between refers to the second distance; Refers to the first distance, M represents the current judging front The number of front points.

5. The method for intelligent tracking of ocean fronts according to claim 2, characterized in that: The calculation formula of the third distance is: ； in, Indicates the target front With the current judging front The distance between refers to the third distance; Indicates the target front Previous j Front points and current judgment front The distance between N Indicates the target front The number of front points.

6. The method for intelligent tracking of ocean fronts according to claim 2, characterized in that: The calculation formula of the most similar front is: ； in, Indicates the most similar front; Indicates the target front And the front to be judged The distance between P represents the number of fronts to be judged, ; argmin () represents the value of the independent variable when seeking the minimum value of the function.

7. The method for intelligently tracking ocean fronts according to claim 1, characterized in that: The function formula of the front tracking result is: : Characterizes that the target front and the most similar front are the same ocean front; : Characterize the target front and the most similar front as different ocean fronts; in, Indicates the target front Most similar front The distance between Indicates the target front The width of Indicates the most similar front Width.

8. A computer device comprising: A memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the ocean front intelligent tracking method described in any one of claims 1 to 7.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, it implements the ocean front intelligent tracking method described in any one of claims 1-7.

10. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, it implements the ocean front intelligent tracking method described in any one of claims 1-7.

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