Marine organism outbreak early warning method and device

Abstract

The invention provides a marine organism outbreak early warning method and device, and relates to the technical field of marine organism monitoring and early warning, and the method comprises the steps: obtaining the marine environment data of a preset sea area; obtaining a first weight coefficient of each feature index based on a pre-configured feature concerned by each scene; calculating a comprehensive feature index according to the first weight coefficient and the feature index; obtaining a second weight coefficient corresponding to each comprehensive feature index; calculating an early warning index of the preset sea area based on the second weight coefficient and the comprehensive characteristic index; and inputting the early warning index to an early warning model, and outputting an early warning index corresponding to the early warning index to generate an early warning prompt. According to the marine organism outbreak early warning method and device provided by the invention, accurate early warning and efficient field response can be realized, and the early warning model is a model constructed based on a comprehensive evaluation function, can effectively cover diversified marine organism monitoring requirements, and has important application value and technical significance.

Description

Technical Field

[0001] The present invention relates to the technical field of marine biological monitoring and early warning, and in particular to a marine biological outbreak early warning method and device. Background Art

[0002] Currently, the research and application of marine biological monitoring and early warning are still in the initial stage. Although the relevant technology can use the evaluation method based on echo integration method to monitor marine organisms, this method is usually only used to estimate biomass or assess the degree of biological invasion, and cannot directly establish an early warning indicator system.

[0003] Moreover, the traditional single indicator early warning model based on instantaneous impact quantity can no longer fully meet the complex and ever-changing field application needs. In addition, the traditional early warning model based on instantaneous impact quantity is also difficult to effectively respond to various marine biological outbreak scenarios.

[0004] Therefore, the relevant technologies lack a comprehensive early warning indicator system for various marine biological outbreak scenarios, resulting in problems such as monitoring blind spots and delayed early warning responses in practical applications. Summary of the invention

[0005] In view of this, an object of the present invention is to provide a marine biological outbreak early warning method and device to alleviate the above technical problems.

[0006] In the first aspect, an embodiment of the present invention provides a method for early warning of marine biological outbreaks, the method comprising: obtaining marine environmental data of at least one scene included in a preset sea area; wherein the marine environmental data comprises characteristic indicators for characterizing the marine environment in each of the scenes; based on a pre-configured feature of concern for each of the scenes, obtaining a first weight coefficient for each of the characteristic indicators under the feature; calculating a comprehensive characteristic indicator of the feature of concern in each of the scenes according to the first weight coefficient and the characteristic indicator; obtaining a second weight coefficient corresponding to the comprehensive characteristic indicator in each of the scenes pre-configured; calculating the early warning indicator of the preset sea area based on the second weight coefficient and the comprehensive characteristic indicator in each of the scenes; inputting the early warning indicator into a pre-constructed early warning model, outputting an early warning index corresponding to the early warning indicator through the early warning model, so as to generate an early warning prompt based on the early warning index; wherein the early warning model is a model constructed based on a comprehensive evaluation function.

[0007] In combination with the first aspect, an embodiment of the present invention provides a first possible implementation method of the first aspect, wherein the step of calculating the comprehensive feature index of the feature of concern in each of the scenarios based on the first weight coefficient and the feature index includes: performing weighted calculation on the feature index according to the first weight coefficient to obtain the comprehensive feature index of the feature of concern in each of the scenarios.

[0008] In combination with the first aspect, an embodiment of the present invention provides a second possible implementation method of the first aspect, wherein the step of calculating the early warning index of the preset sea area based on the second weight coefficient and the comprehensive characteristic index under each of the scenarios includes: performing weighted calculation on the comprehensive characteristic index under each of the scenarios based on the second weight coefficient to obtain the early warning index of the preset sea area.

[0009] In combination with the first aspect, an embodiment of the present invention provides a third possible implementation scheme of the first aspect, wherein the step of generating a warning prompt based on the warning index includes: searching for the warning index range to which the warning index belongs in a pre-configured warning level correspondence relationship; wherein the warning level correspondence relationship includes a plurality of pre-configured warning index ranges, and a warning level corresponding to each warning index range; determining the warning level corresponding to the warning index range to which the warning index belongs as the warning level of the preset sea area; and generating warning information based on the warning level of the preset sea area.

[0010] In combination with the first aspect, an embodiment of the present invention provides a fourth possible implementation of the first aspect, wherein the above-mentioned marine environment data includes: at least one of the following data: temperature data, dissolved oxygen concentration data, sonar data, pressure data, and time parameters; the method also includes: extracting the sonar data included in the marine environment data; processing the sonar data to obtain the volume scattering intensity of cold source organisms; and monitoring the cold source organisms in a preset sea area based on the volume scattering intensity of the cold source organisms.

[0011] In combination with the fourth possible implementation of the first aspect, an embodiment of the present invention provides a fifth possible implementation of the first aspect, wherein the above-mentioned step of monitoring the cold source organisms in a preset sea area based on the volume scattering intensity of the cold source organisms includes: calculating the change rate of the number of cold source organisms based on the volume scattering intensity of the cold source organisms; wherein the change rate is the change in the volume scattering intensity of the cold source organisms per unit time; and issuing an early warning of the instantaneous impact of the cold source organisms based on the change rate.

[0012] In combination with the fourth possible implementation of the first aspect, an embodiment of the present invention provides a sixth possible implementation of the first aspect, wherein the above-mentioned step of monitoring the cold source organisms in a preset sea area based on the volume scattering intensity of the cold source organisms also includes: counting the cumulative amount of the volume scattering intensity of the cold source organisms within a preset time period; comparing the difference between the cumulative amount and a preset cumulative characteristic value; and issuing an early warning for the continuous increase of the cold source organisms based on the difference.

[0013] In combination with the fourth possible implementation of the first aspect, an embodiment of the present invention provides a seventh possible implementation of the first aspect, wherein the above-mentioned step of monitoring the cold source organisms in a preset sea area based on the volume scattering intensity of the cold source organisms also includes: calculating the average flux value of the cold source organisms according to the volume scattering intensity of the cold source organisms; and calculating the total amount of organisms according to the average flux value; and issuing an early warning of the total weight of the invasion of cold source organisms based on the total amount of organisms.

[0014] In a second aspect, an embodiment of the present invention further provides a marine biological outbreak warning device, the device comprising: an acquisition module, used to acquire marine environmental data of at least one scene included in a preset sea area; wherein the marine environmental data includes characteristic indicators for characterizing the marine environment in each of the scenes; a first module, used to acquire a first weight coefficient for each of the characteristic indicators under the feature based on a pre-configured feature of each of the scenes concerned; a first calculation module, used to calculate a comprehensive characteristic indicator of the feature concerned in each of the scenes according to the first weight coefficient and the characteristic indicator; a second module, used to acquire a second weight coefficient corresponding to the comprehensive characteristic indicator in each of the scenes pre-configured; a second calculation module, used to calculate the warning indicator of the preset sea area based on the second weight coefficient and the comprehensive characteristic indicator in each of the scenes; an early warning module, used to input the early warning indicator into a pre-constructed early warning model, and output a warning index corresponding to the early warning indicator through the early warning model, so as to generate an early warning prompt based on the early warning index; wherein the early warning model is a model constructed based on a comprehensive evaluation function.

[0015] In a third aspect, an embodiment of the present invention further provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the steps of the method described in the first aspect are executed.

[0016] The embodiments of the present invention bring the following beneficial effects: A marine biological outbreak warning method and device provided by an embodiment of the present invention can obtain marine environmental data of at least one scene included in a preset sea area; based on the pre-configured features of concern for each scene, obtain the first weight coefficient of each feature indicator under the feature; calculate the comprehensive feature indicator of the feature of concern in each scene according to the first weight coefficient and the feature indicator; obtain the second weight coefficient corresponding to the comprehensive feature indicator in each pre-configured scene; calculate the warning indicator of the preset sea area based on the second weight coefficient and the comprehensive feature indicator in each scene; input the warning indicator into a pre-constructed warning model, and output the warning index corresponding to the warning indicator through the warning model to generate a warning prompt based on the warning index; and the above-mentioned first weight coefficient and second weight coefficient can be dynamically adjusted according to the actual marine conditions, so as to achieve accurate early warning and efficient on-site response, and the above-mentioned warning model is a model constructed based on a comprehensive evaluation function, which can effectively cover diverse marine biological monitoring needs and has important application value and technical significance.

[0017] Other features and advantages of the present invention will be described in the following description, and partly become apparent from the description, or understood by practicing the present invention. The purpose and other advantages of the present invention are realized and obtained by the structures particularly pointed out in the description, claims and drawings.

[0018] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, preferred embodiments are given below and described in detail with reference to the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] In order to more clearly illustrate the specific implementation methods of the present invention or the technical solutions in the prior art, the drawings required for use in the specific implementation methods or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are some implementation methods of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without paying any creative work.

[0020] Figure 1 A flow chart of a marine biological outbreak early warning method provided by an embodiment of the present invention; Figure 2 A flow chart of another marine biological outbreak early warning method provided by an embodiment of the present invention; Figure 3 A schematic diagram of the structure of a marine biological outbreak warning device provided by an embodiment of the present invention; Figure 4 A schematic diagram of the structure of an electronic device provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0021] In order to make the purpose, technical solution and advantages of the embodiments of the present invention clearer, the technical solution of the present invention will be clearly and completely described below in conjunction with the accompanying drawings. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative work are within the scope of protection of the present invention.

[0022] At present, most early warning indicators based on a single instantaneous value are used to monitor and warn marine life, which is difficult to cover the diverse and complex monitoring needs of marine life. In addition, the relevant technology lacks a comprehensive early warning model for a variety of marine life outbreak scenarios, resulting in monitoring blind spots and delayed early warning responses in practical applications.

[0023] Based on this, a marine biological outbreak warning method and device provided in an embodiment of the present invention can establish a comprehensive warning indicator system for multiple scenarios, covering multi-dimensional monitoring needs such as instantaneous impact warning of cold source biomass, continuous increment, and total weight of invasion.

[0024] To facilitate understanding of this embodiment, a marine biological outbreak warning method disclosed in an embodiment of the present invention is first introduced in detail.

[0025] In a possible implementation, the present invention provides a marine biological outbreak warning method, such as Figure 1 The flowchart of a marine biological outbreak early warning method shown in FIG. 1 comprises the following steps: Step S102, obtaining ocean environment data of at least one scene included in a preset sea area; The marine environment data in the embodiment of the present invention includes characteristic indicators used to characterize the marine environment in each scenario; For example, a monitoring system can be deployed in a preset sea area in advance. For example, sonar sensors can be deployed to monitor underwater topography and biological distribution; pressure sensors, temperature sensors, dissolved oxygen detectors, etc. can also be deployed. The marine environment information obtained by the monitoring system can be used as a data source, and further data preprocessing can be used to obtain the marine environment data in the embodiment of the present invention.

[0026] Specifically, the data preprocessing process includes noise removal, signal enhancement, and rationality check mechanisms to verify the accuracy and completeness of the data. At the same time, in order to facilitate analysis, the data can also be normalized. The formula for normalization can be expressed as:

[0027] Among them, Xi is a certain sensor data in the i-th scene, and Xmax and Xmin represent the maximum and minimum values ​​of the data respectively.

[0028] The specific data preprocessing process can be set according to actual usage conditions, and the embodiment of the present invention is not limited to this.

[0029] Furthermore, the marine environment data collected by different sensors or detectors is equivalent to a characteristic indicator of the marine environment. For example, the characteristic indicator collected by the temperature sensor is temperature data, the characteristic indicator collected by the sonar sensor is sonar data, etc. Therefore, the above-mentioned marine environment data in the embodiments of the present invention generally includes a variety of characteristic indicators that characterize the marine environment in each scenario.

[0030] Step S104, based on the pre-configured feature of each scene concerned, obtaining a first weight coefficient of each feature indicator under the feature; Step S106, calculating a comprehensive feature index of the feature of interest in each scenario according to the first weight coefficient and the feature index; In actual use, the above-mentioned scenes refer to different areas according to distribution in the preset sea area. For example, the preset sea area contains three different areas: the closest area A, the middle area B, and the farthest area C. At this time, there can be three scenes, namely, scene A, scene B and scene C. Different sea areas or different scenes have different features of concern. For example, scene A is the closest area, and it is necessary to focus on the distribution of organisms, that is, the feature of scene A is the distribution of organisms; scene B is the middle area, and it is usually necessary to pay attention to environmental changes and biological distribution, that is, the features of scene B are environmental changes and biological distribution; scene C is the farthest area, and it is usually necessary to pay attention to environmental changes, that is, the features of scene C are environmental changes.

[0031] Generally, the weight of each feature indicator corresponding to each scene is different according to the features concerned. Therefore, for each scene, the weight parameter of each feature indicator can be pre-configured according to the features concerned, so that the calculated comprehensive feature indicator can be more accurate.

[0032] Therefore, in the above step S104, the weight parameter of each feature index, that is, the above first weight parameter, can be obtained based on the pre-configured features of concern for each scenario, and then the comprehensive feature index in the scenario can be calculated.

[0033] Furthermore, considering that the preset sea area usually has multiple scenarios, it is necessary to further perform weighted calculation on the comprehensive characteristic indicators corresponding to each of the above scenarios, so as to obtain the early warning indicators for the entire preset sea area, that is, the process including the following steps S108~S112.

[0034] Step S108, obtaining a second weight coefficient corresponding to the pre-configured comprehensive feature index in each scenario; Step S110, calculating the early warning index of the preset sea area based on the second weight coefficient and the comprehensive characteristic index in each scenario; Step S112, inputting the early warning indicator into a pre-built early warning model, outputting the early warning index corresponding to the early warning indicator through the early warning model, and generating an early warning prompt based on the early warning index; Among them, the early warning model in the embodiment of the present invention is a model constructed based on a comprehensive evaluation function.

[0035] In actual use, the first weight parameter and the second weight parameter can be configured according to actual use and in combination with empirical values. Moreover, as the marine environment continues to change, for example, seasonality, climate, etc., the first weight parameter and the second weight parameter can also be dynamically adjusted so that the above-mentioned comprehensive characteristic indicators and early warning indicators can better reflect the outbreak trend of marine organisms.

[0036] A marine biological outbreak warning method provided by an embodiment of the present invention can obtain marine environmental data of at least one scene included in a preset sea area; based on the pre-configured features of concern for each scene, obtain the first weight coefficient of each feature indicator under the feature; calculate the comprehensive feature indicator of the feature of concern in each scene according to the first weight coefficient and the feature indicator; obtain the second weight coefficient corresponding to the comprehensive feature indicator in each pre-configured scene; calculate the warning indicator of the preset sea area based on the second weight coefficient and the comprehensive feature indicator in each scene; input the warning indicator into a pre-constructed warning model, and output the warning index corresponding to the warning indicator through the warning model to generate a warning prompt based on the warning index; and the above-mentioned first weight coefficient and second weight coefficient can be dynamically adjusted according to the actual marine conditions, so as to achieve accurate early warning and efficient on-site response, and the above-mentioned warning model is a model constructed based on a comprehensive evaluation function, which can effectively cover diverse marine biological monitoring needs and has important application value and technical significance.

[0037] In actual use, the above marine environmental data can usually be stored in a database, and the accuracy and completeness of the data can be verified through a rationality check mechanism. Among them, rationality checks include outlier detection, data consistency verification, etc., to ensure that the data in the database can be used for subsequent analysis and modeling.

[0038] Furthermore, the marine environment data in the embodiments of the present invention generally include at least one of the following data: temperature data, dissolved oxygen concentration data, sonar data, pressure data, and time parameters; among them, the pressure data in the embodiments of the present invention corresponds to underwater reliability information, which can also be called underwater pressure data, and is generally related to the underwater depth.

[0039] Usually, in order to facilitate analysis and early warning of marine biological outbreaks, data structure can be performed on the marine environmental data of a preset sea area to obtain a data table containing the marine environmental data. For ease of understanding, the following Table 1 shows a form of a data table: Table 1:

[0040] Among them, in the above Table 1, the preset sea area includes the above three scenes as an example, namely scene A, scene B and scene C, which correspond to the nearest area, the middle area, and the farthest area respectively; and each scene contains 5 characteristic indicators, including water temperature T, dissolved oxygen concentration DO, pressure P, sonar echo intensity B, and timestamp Time, which correspond to the above temperature data, dissolved oxygen concentration data, pressure data, sonar data and time parameters respectively.

[0041] Further, assuming that the characteristic of the current preset sea area is biological density, usually represented by D, the marine biological outbreak warning method in the embodiment of the present invention is further described below based on the above Table 1. Specifically, Figure 2 The flowchart of another marine biological outbreak early warning method shown includes the following steps: Step S202, obtaining ocean environment data of at least one scene included in a preset sea area; The marine environment data in the embodiment of the present invention includes characteristic indicators for characterizing the marine environment in each scenario.

[0042] Specifically, referring to the above Table 1, it is assumed that the marine environment data of the preset sea area is constructed in the form of the above Table 1.

[0043] Step S204, based on the pre-configured feature of each scene concerned, obtaining a first weight coefficient of each feature indicator under the feature; Step S206, performing weighted calculation on the feature index according to the first weight coefficient to obtain a comprehensive feature index of the feature concerned in each scene; Specifically, taking the biological density as an example, there are three scenarios based on Table 1. For each scenario, it is necessary to calculate the comprehensive characteristic index of the characteristic of interest. Specifically, it can be calculated by the following formula:

[0044] Among them, Di is a comprehensive characteristic index, represents the weight coefficient of the jth characteristic indicator in the ith scenario, that is, the first weight parameter of the embodiment of the present invention, and Fj represents the specific value of the jth characteristic indicator, which can be obtained from the above Table 1.

[0045] Assuming that the calculation formula of the comprehensive characteristic index is D=0.2T+0.3DO+0.1P+0.4B, that is, in the current preset sea area, when the characteristic of each scene is biological density, the first weight parameters corresponding to the above temperature data, dissolved oxygen concentration data, pressure data, and sonar data are 0.2, 0.3, 0.1, and 0.4 respectively. According to this formula, the biological density of each scene in Table 1 is: Scenario A: =

[0046] Scenario B: =

[0047] Scenario C: =

[0048] The biological density D1, D2 and D3 calculated for each scene at this time are the comprehensive characteristic indicators of the characteristics of concern in each scene.

[0049] In actual use, when the above-mentioned features of concern are other features, such as environmental features, etc., the above-mentioned first weight parameter and the following second weight parameter can be configured as different parameters, which shall be subject to actual use, and the embodiment of the present invention is not limited to this.

[0050] Step S208, obtaining a second weight coefficient corresponding to the pre-configured comprehensive feature index in each scenario; Step S210, performing weighted calculation on the comprehensive characteristic index in each scenario based on the second weight coefficient to obtain an early warning index for a preset sea area; Specifically, continuing to use the above Table 1 as an example, after obtaining the above biological densities D1, D2 and D3, the early warning index of the above preset sea area can be calculated. Specifically, the process of calculating the early warning index can be expressed by weighted calculation, and its calculation formula is expressed as follows: ; Where S represents the comprehensive early warning indicator; represents the weight coefficient of the i-th scenario, that is, the second weight parameter in the embodiment of the present invention, and satisfies =1; n represents the number of scenes, Represents the comprehensive characteristic index of the i-th scene, such as D1, D2 and D3 calculated above.

[0051] Among them, the second weight parameter here , , It can be determined based on the importance of the scene. For example w 1 At this time, the warning index of the above preset sea area can be expressed as

[0052] The process of calculating the early warning index is actually a process of fusing the comprehensive characteristic indicators of multiple scenes. In the embodiment of the present invention, it is a process of fusing the biological density.

[0053] Furthermore, after obtaining the fused early warning indicator, the following steps may be further performed to provide early warning prompts.

[0054] In actual use, the first weight parameter and the second weight parameter can be pre-configured with an initial weight value. Taking the second weight parameter as an example, assuming that the second weight parameter of scene A is 0.6 and the second weight parameter of scene B is 0.4 during the initial allocation, the weights can be optimized through the gradient descent algorithm so that the comprehensive early warning indicators can better reflect the outbreak trend of plankton.

[0055] Specifically, the optimization formula can be expressed as the following formula: , in, represents the weight coefficient of the i-th scenario in the t-th iteration step, represents the learning rate, represents the loss function, which can be calculated using mean square error. When the change in the loss function is less than a certain threshold, the iteration terminates. After iterative optimization, the optimal weight is obtained: for example, the weight of scene A after optimization is 0.7, and the weight of scene B is 0.3.

[0056] In specific implementation, the dynamic adjustment process of the above weight parameters can be set according to actual usage conditions, and the embodiment of the present invention does not limit this.

[0057] Step S212, inputting the early warning indicator into a pre-built early warning model, and outputting an early warning index corresponding to the early warning indicator through the early warning model; Step S214, searching the warning index range to which the warning index belongs in the pre-configured warning level correspondence relationship; The warning level correspondence relationship includes a plurality of pre-configured warning index ranges, and the warning level corresponding to each warning index range; Step S216, determining the warning level corresponding to the warning index range to which the warning index belongs as the warning level of the preset sea area, and generating warning information based on the warning level of the preset sea area.

[0058] Specifically, in the embodiment of the present invention, the early warning model is a model constructed based on a comprehensive evaluation function, which can be expressed as the following decision-making process:

[0059] Among them, W represents the final early warning decision, that is, the early warning index in the embodiments of the present invention. f is a weighted non-linear comprehensive evaluation function for outputting an early warning result according to the comprehensive early warning index Si, and Si is the early warning index of different features of concern.

[0060] Further, the multiple early warning index ranges included in the above early warning level correspondence can usually be pre-configured. For example, when the early warning index range is W > 0.8, it is determined that a marine biological outbreak is predicted. When 0.5 < W ≤ 0.8, a medium risk is predicted; when W ≤ 0.5, a low risk is predicted.

[0061] When the final early warning index output by the above prediction model is W = 0.72, it indicates a medium risk of a marine biological outbreak.

[0062] The above early warning index range can be set according to the actual usage situation, and the embodiments of the present invention do not limit this.

[0063] Moreover, the above method of multi-scenario, multi-sensor data fusion and dynamic weight adjustment enables the early warning model to effectively predict the outbreak trend of marine organisms. And the data fusion of multiple scenarios can make the prediction model more accurate in predicting the outbreak of plankton.

[0064] In addition, for the above early warning information, it can also be indicated by colors. For example, the early warning information is displayed through color codes (orange or blue), which can intuitively guide on-site staff to take corresponding measures.

[0065] Further, in the embodiments of the present invention, sonar data included in the above marine environmental data can also be extracted; the sonar data is processed to obtain the volume scattering intensity of cold source organisms; and the cold source organisms in a preset sea area are monitored based on the volume scattering intensity of cold source organisms.

[0066] Specifically, sonar data processing means in related technologies can be used to convert sonar data into the volume scattering intensity of cold source organisms, and then the cold source organisms in a preset sea area are further monitored.

[0067] Specifically, the monitoring of cold source organisms in the embodiments of the present invention includes instantaneous impact early warning monitoring of cold source organisms, continuous increment early warning monitoring of cold source organisms, and total invasion weight early warning monitoring of cold source organisms.

[0068] Specifically, when conducting instantaneous impact early warning monitoring of cold source organisms, the change rate of the number of cold source organisms can be calculated according to the volume scattering intensity of cold source organisms; among them, the change rate is the change amount of the volume scattering intensity of cold source organisms per unit time; and then an early warning of the instantaneous impact of cold source organisms is made based on the change rate.

[0069] Among them, the volume scattering intensity of cold source organisms is usually represented by SV, also known as the acoustic back volume scattering intensity of cold source organisms in clustered state. The change rate of the above-mentioned cold source organisms can be expressed as ΔSV / Δt, which represents the change in the volume scattering intensity of cold source organisms per unit time, and the unit is decibel / cubic meter*minute (dB / m3*min), which represents the change rate of the number of monitored objects.

[0070] For example, when 10dB<ΔSV / Δt<20dB (10 to 100 times larger than normal marine biomass), it indicates that more organisms are pouring into the water intake, and when ΔSV / Δt>20dB, it indicates that a large number of organisms are currently pouring into the water intake, that is, different warning levels can be set according to actual conditions to warn of instantaneous impact of cold source organisms. The specific warning level can be set according to actual use, and the embodiment of the present invention does not limit this.

[0071] Furthermore, when conducting continuous increase early warning monitoring of cold source organisms, the cumulative amount of the cold source organism volume scattering intensity within a preset time period can be counted; the difference between the cumulative amount and the preset cumulative characteristic value can be compared; and an early warning of the continuous increase of cold source organisms can be issued based on the difference.

[0072] In specific implementation, the cumulative amount of the cold source biological volume scattering intensity within a preset time period is represented by ΣSV, and its unit is decibel / cubic meter (dB).

[0073] Usually, the cumulative amount of the volume scattering intensity of cold source organisms for a period of time before the current time, such as 30 minutes, can be calculated, that is, the cumulative amount of adjacent time periods, and the cumulative amount of various types such as suspended sediment, jellyfish, fish schools, floating garbage, etc. can usually be calculated separately, and then the cumulative amount of each type is compared with the characteristic value of the corresponding type to obtain the difference. In addition, in order to improve the accuracy and universality of statistics, the cumulative amount of adjacent time periods can be compared multiple times to obtain the difference. If the difference is greater than a certain threshold, it means that there is a continuous increase in the number of cold source organisms. That is, an early warning is issued for the continuous increase of cold source organisms based on the difference.

[0074] Furthermore, in an embodiment of the present invention, when early warning monitoring of the total weight of the invasion of cold source organisms is performed, the average flux value of the cold source organisms can be calculated based on the volume scattering intensity of the cold source organisms; and the total amount of organisms can be calculated based on the average flux value; and then an early warning of the total weight of the invasion of cold source organisms can be issued based on the total amount of organisms.

[0075] In specific implementation, when using sonar sensors to monitor cold-source organisms, when cold-source organisms enter the sonar detection beam, the volume scattering intensity (SV) value of the cold-source organisms measured by the sonar is proportional to its density (n) and the average single target intensity (TS), that is, the formula is expressed as: n = SV / TS; Since the cold source biological cluster will be radiated with sound by the sonar multiple times when passing through the sonar detection beam, the above formula actually uses the average value of multiple transmitted and received echoes.

[0076] On this basis, by measuring the average flow velocity v from the water intake toward the shore end, the average absolute value of the cold source organism flux, that is, the average flux value of the cold source organism in the embodiment of the present invention, is calculated, and the formula is expressed as: |F|=n*v; Therefore, within time t, the total biomass of the monitoring section (area S) is B=|F|*S*t; that is, the total amount of organisms in the embodiment of the present invention.

[0077] Furthermore, for the total amount of organisms, the total weight can also be calculated based on the average weight of the organisms. For example, the total weight can be obtained by multiplying the above total amount of organisms by the average weight of the organisms, wherein the average weight is derived from historical experience accumulation or from more authoritative biological survey data.

[0078] Based on the total amount or total weight of the above-mentioned organisms, an early warning can be implemented for the total weight of the invasion of cold source organisms. For example, a corresponding early warning threshold can be set according to the actual sea area, so that an early warning prompt can be issued when the threshold is exceeded, so as to prompt the on-site staff to take corresponding measures.

[0079] In actual use, the above-mentioned early warning model or cold source biological monitoring, including cold source biological instantaneous impact early warning monitoring, cold source biological continuous increment early warning monitoring, and cold source biological invasion total weight early warning monitoring, etc., can be connected to the corresponding AI model, and the knowledge base required by the AI ​​model is established at the same time, so as to realize the early warning prompt of marine biological outbreak with the help of the AI ​​model. It can be set according to the actual use situation, and the embodiment of the present invention does not limit this.

[0080] In summary, the marine biological outbreak warning method provided by the embodiment of the present invention can fuse sonar data in different scenarios, extract representative characteristic indicators, and enhance the prediction ability and robustness of the prediction model through multi-dimensional data fusion.

[0081] At the same time, according to the monitoring needs of cold source biomass, we can establish instantaneous impact warnings for cold source organisms, continuous increase warnings for cold source organisms, total invasion weight warnings for cold source organisms, etc., and realize multi-dimensional comprehensive warning indicators such as AI warnings for cold source organisms. By comparing the deviations between historical data and new data, we can dynamically adjust the weight parameters of the warning indicators to ensure the real-time and accuracy of the warning model.

[0082] Furthermore, based on the early warning prompts, corresponding emergency decisions can be triggered to guide on-site actions, and the early warning model can be continuously optimized and adjusted according to actual conditions to improve the early warning accuracy and response speed.

[0083] Furthermore, the embodiment of the present invention also provides a marine life outbreak warning device, such as Figure 3 The structure diagram of a marine biological outbreak early warning device shown in FIG. 1 includes: The acquisition module 30 is used to acquire the marine environment data of at least one scene included in the preset sea area; wherein the marine environment data includes characteristic indicators for characterizing the marine environment in each of the scenes; The first module 32 is used to obtain a first weight coefficient of each feature index under the feature based on the pre-configured feature concerned by each of the scenarios; A first calculation module 34, configured to calculate a comprehensive characteristic index of the characteristic concerned in each of the scenarios according to the first weight coefficient and the characteristic index; The second module 36 is used to obtain a pre-configured second weight coefficient corresponding to the comprehensive feature index in each of the scenarios; A second calculation module 38, configured to calculate the early warning index of the preset sea area based on the second weight coefficient and the comprehensive characteristic index in each of the scenarios; The early warning module 39 is used to input the early warning indicator into a pre-built early warning model, output the early warning index corresponding to the early warning indicator through the early warning model, and generate an early warning prompt based on the early warning index; wherein the early warning model is a model built based on a comprehensive evaluation function.

[0084] Furthermore, the first calculation module 34 is also used for: The feature indicators are weighted according to the first weight coefficient to obtain a comprehensive feature indicator of the feature concerned in each of the scenarios.

[0085] Furthermore, the second calculation module 38 is also used for: Based on the second weight coefficient, weighted calculation is performed on the comprehensive characteristic index in each of the scenarios to obtain the early warning index of the preset sea area.

[0086] Furthermore, the above-mentioned early warning module 39 is also used for: Searching for the warning index range to which the warning index belongs in the pre-configured warning level correspondence; wherein the warning level correspondence includes a plurality of pre-configured warning index ranges, and a warning level corresponding to each warning index range; determining the warning level corresponding to the warning index range to which the warning index belongs as the warning level of the preset sea area; and generating warning information based on the warning level of the preset sea area.

[0087] Further, the above-mentioned marine environment data includes: at least one of the following data: temperature data, dissolved oxygen concentration data, sonar data, pressure data, time parameters; The above device is also used for: Extracting sonar data included in the marine environment data; processing the sonar data to obtain the volume scattering intensity of cold source organisms; and monitoring the cold source organisms in a preset sea area based on the volume scattering intensity of the cold source organisms.

[0088] The step of monitoring the cold source organisms in a preset sea area based on the cold source organism volume scattering intensity includes: Calculate the change rate of the number of cold source organisms according to the volume scattering intensity of the cold source organisms; wherein the change rate is the change amount of the volume scattering intensity of the cold source organisms per unit time; based on the change rate, warn of the instantaneous impact of the cold source organisms; and, Counting the cumulative amount of the volume scattering intensity of the cold source organism within a preset time period; comparing the difference between the cumulative amount and a preset cumulative characteristic value; and issuing an early warning for the continuous increase of the cold source organism based on the difference; and, The average flux value of the cold source organisms is calculated according to the volume scattering intensity of the cold source organisms; and the total amount of organisms is calculated according to the average flux value; and the total weight of the invasion of the cold source organisms is warned based on the total amount of organisms.

[0089] The marine life outbreak warning device provided in the embodiment of the present invention has the same technical features as the marine life outbreak warning method provided in the above embodiment, so it can also solve the same technical problems and achieve the same technical effects.

[0090] Furthermore, an embodiment of the present invention also provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of the above method when executing the computer program.

[0091] An embodiment of the present invention further provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the steps of the above method are executed.

[0092] Furthermore, an embodiment of the present invention also provides a schematic diagram of the structure of an electronic device, such as Figure 4 As shown, it is a schematic diagram of the structure of the electronic device, wherein the electronic device includes a processor 41 and a memory 40, the memory 40 stores computer executable instructions that can be executed by the processor 41, and the processor 41 executes the computer executable instructions to implement the above method.

[0093] exist Figure 4 In the illustrated embodiment, the electronic device further includes a bus 42 and a communication interface 43 , wherein the processor 41 , the communication interface 43 and the memory 40 are connected via the bus 42 .

[0094] Among them, the memory 40 may include a high-speed random access memory (RAM), and may also include a non-volatile memory (non-volatile memory), such as at least one disk storage. The communication connection between the system network element and at least one other network element is realized through at least one communication interface 43 (which can be wired or wireless), and the Internet, wide area network, local area network, metropolitan area network, etc. can be used. The bus 42 can be an ISA (Industry Standard Architecture) bus, a PCI (Peripheral Component Interconnect) bus or an EISA (Extended Industry Standard Architecture) bus, etc. The bus 42 can be divided into an address bus, a data bus, a control bus, etc. For ease of representation, Figure 4 Only one bidirectional arrow is used in the diagram, but this does not mean that there is only one bus or only one type of bus.

[0095] The processor 41 may be an integrated circuit chip with signal processing capabilities. In the implementation process, each step of the above method can be completed by the hardware integrated logic circuit in the processor 41 or the instruction in the form of software. The above processor 41 can be a general-purpose processor, including a central processing unit (CPU), a network processor (NP), etc.; it can also be a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components. The general-purpose processor can be a microprocessor or the processor can also be any conventional processor. The steps of the method disclosed in the embodiment of the present invention can be directly embodied as a hardware decoding processor to execute, or it can be executed by a combination of hardware and software modules in the decoding processor. The software module can be located in a mature storage medium in the field such as a random access memory, a flash memory, a read-only memory, a programmable read-only memory, or an electrically erasable programmable memory, a register, etc. The storage medium is located in the memory, and the processor 41 reads the information in the memory and completes the above method in combination with its hardware.

[0096] A computer program product of a marine biological outbreak warning method and device provided in an embodiment of the present invention includes a computer-readable storage medium storing program code. The instructions included in the program code can be used to execute the method described in the previous method embodiment. The specific implementation can be found in the method embodiment, which will not be repeated here.

[0097] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working process of the device described above can refer to the corresponding process in the aforementioned method embodiment, and will not be repeated here.

[0098] In addition, in the description of the embodiments of the present invention, unless otherwise clearly specified and limited, the terms "installed", "connected", and "connected" should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection or an indirect connection through an intermediate medium, and it can be the internal communication of two components. For those skilled in the art, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0099] If the functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium, including several instructions to enable a computer device (which can be a personal computer, server, or network device, etc.) to perform all or part of the steps of the methods described in various embodiments of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk, etc., which can store program codes.

[0100] In the description of the present invention, it should be noted that the terms "center", "upper", "lower", "left", "right", "vertical", "horizontal", "inner", "outer", etc., indicating the orientation or positional relationship, are based on the orientation or positional relationship shown in the drawings, and are only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as limiting the present invention. In addition, the terms "first", "second", and "third" are used for descriptive purposes only, and cannot be understood as indicating or implying relative importance.

[0101] Finally, it should be noted that the above embodiments are only specific implementations of the present invention, which are used to illustrate the technical solutions of the present invention, rather than to limit them. The protection scope of the present invention is not limited thereto. Although the present invention is described in detail with reference to the above embodiments, those skilled in the art should understand that any person skilled in the art can still modify the technical solutions recorded in the above embodiments within the technical scope disclosed by the present invention, or can easily think of changes, or make equivalent replacements for some of the technical features therein; and these modifications, changes or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present invention, and should be included in the protection scope of the present invention. Therefore, the protection scope of the present invention shall be based on the protection scope of the claims.

Claims

1. A marine biological outbreak early warning method, characterized in that: The method comprises: Acquire ocean environment data of at least one scene included in a preset sea area; wherein the ocean environment data includes characteristic indicators for characterizing the ocean environment in each of the scenes; Based on the pre-configured feature of each of the scenarios concerned, obtaining a first weight coefficient of each of the feature indicators under the feature; Calculate the comprehensive feature index of the feature concerned in each of the scenarios according to the first weight coefficient and the feature index; Obtaining a pre-configured second weight coefficient corresponding to the comprehensive feature indicator in each of the scenarios; Calculating the early warning index of the preset sea area based on the second weight coefficient and the comprehensive characteristic index in each of the scenarios; The early warning indicator is input into a pre-built early warning model, and the early warning index corresponding to the early warning indicator is output through the early warning model to generate an early warning prompt based on the early warning index; wherein the early warning model is a model built based on a comprehensive evaluation function.

2. The method according to claim 1, characterized in that The step of calculating the comprehensive feature index of the feature concerned in each of the scenarios according to the first weight coefficient and the feature index comprises: The feature indicators are weighted according to the first weight coefficient to obtain a comprehensive feature indicator of the feature concerned in each of the scenarios.

3. The method according to claim 1, characterized in that The step of calculating the early warning index of the preset sea area based on the second weight coefficient and the comprehensive characteristic index in each of the scenarios includes: Based on the second weight coefficient, weighted calculation is performed on the comprehensive characteristic index in each of the scenarios to obtain the early warning index of the preset sea area.

4. The method according to claim 1, characterized in that: The step of generating a warning prompt based on the warning index includes: Searching for the warning index range to which the warning index belongs in the pre-configured warning level correspondence relationship; wherein the warning level correspondence relationship includes a plurality of pre-configured warning index ranges, and the warning level corresponding to each warning index range; Determine the warning level corresponding to the warning index range to which the warning index belongs as the warning level of the preset sea area; Generate warning information based on the warning level of the preset sea area.

5. The method according to claim 1, characterized in that: The marine environment data includes: at least one of the following data: temperature data, dissolved oxygen concentration data, sonar data, pressure data, and time parameters; The method further comprises: Extracting sonar data included in the marine environment data; Processing the sonar data to obtain the cold source biological volume scattering intensity; The cold source organisms in a preset sea area are monitored based on the volume scattering intensity of the cold source organisms.

6. The method according to claim 5, characterized in that The step of monitoring the cold source organisms in a preset sea area based on the cold source organism volume scattering intensity includes: Calculate the change rate of the number of cold source organisms according to the volume scattering intensity of the cold source organisms; wherein the change rate is the change amount of the volume scattering intensity of the cold source organisms per unit time; Based on the change rate, an early warning is given to the instantaneous impact of cold source organisms.

7. The method according to claim 5, characterized in that The step of monitoring the cold source organisms in a preset sea area based on the cold source organism volume scattering intensity also includes: Counting the cumulative amount of the cold source biological volume scattering intensity within a preset time period; Comparing the difference between the cumulative amount and a preset cumulative characteristic value; Based on the difference, an early warning is issued for the continuous increase of the cold source organisms.

8. The method according to claim 5, characterized in that The step of monitoring the cold source organisms in a preset sea area based on the cold source organism volume scattering intensity also includes: Calculating an average flux value of the cold source organisms according to the volume scattering intensity of the cold source organisms; and calculating the total amount of organisms according to the average flux value; Based on the total amount of organisms, an early warning is issued for the total weight of the invasion of cold source organisms.

9. A marine biological outbreak warning device, characterized in that: The device comprises: An acquisition module, used to acquire marine environment data of at least one scene included in a preset sea area; wherein the marine environment data includes characteristic indicators for characterizing the marine environment in each of the scenes; The first module is used to obtain a first weight coefficient of each feature index under the feature based on a pre-configured feature concerned by each of the scenarios; A first calculation module, used for calculating a comprehensive characteristic index of the characteristic concerned in each of the scenarios according to the first weight coefficient and the characteristic index; The second module is used to obtain a second weight coefficient corresponding to the comprehensive feature index in each of the pre-configured scenarios; A second calculation module, used for calculating the early warning index of the preset sea area based on the second weight coefficient and the comprehensive characteristic index in each of the scenarios; An early warning module is used to input the early warning indicator into a pre-built early warning model, output the early warning index corresponding to the early warning indicator through the early warning model, and generate an early warning prompt based on the early warning index; wherein the early warning model is a model built based on a comprehensive evaluation function.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps of the method described in any one of claims 1 to 8 are executed.

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