Method and device for warning of marine organism outbreaks

Abstract

The present invention provides a method and device for early warning of marine organism outbreaks, relating to the technical field of marine organism monitoring and early warning. The method includes: obtaining marine environmental data of a preset sea area; obtaining a first weight coefficient of each characteristic index based on the characteristics concerned in each pre-configured scenario; calculating a comprehensive characteristic index according to the first weight coefficient and the characteristic index; obtaining a second weight coefficient corresponding to each comprehensive characteristic index; calculating an early warning index of the preset sea area based on the second weight coefficient and the comprehensive characteristic index; inputting the early warning index into an early warning model, and outputting an early warning index corresponding to an early warning index to generate an early warning prompt. The method and device for early warning of marine organism outbreaks provided by the present invention can achieve accurate early warning and efficient on-site response. Moreover, the above-mentioned early warning model is a model constructed based on a comprehensive evaluation function, which can effectively cover diverse 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 method and device for early warning of marine biological outbreaks. Background Art

[0002] Currently, the research and application of marine biological monitoring and early warning are still in their infancy. Although the evaluation method based on the echo integration method can be used to monitor marine organisms in related technologies, this method is usually only used to estimate the biomass or evaluate the degree of biological invasion, and it is impossible to directly establish an early warning index system.

[0003] Moreover, the traditional single-index early warning model with the instantaneous impact amount as the core can no longer fully meet the requirements of complex and changeable on-site applications. In addition, the traditional early warning model based on the instantaneous impact amount is also difficult to effectively respond to multiple marine biological outbreak scenarios.

[0004] Therefore, there is a lack of a comprehensive early warning index system for multiple marine biological outbreak scenarios in related technologies, resulting in monitoring blind spots and lagging early warning responses in actual applications. Summary of the Invention

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

[0006] In a first aspect, an embodiment of the present invention provides a method for early warning of marine biological outbreaks. The method includes: obtaining marine environmental data of at least one scenario included in a preset sea area; wherein the marine environmental data includes characteristic indicators for characterizing the marine environment in each scenario; based on the characteristics concerned in each scenario configured in advance, obtaining a first weight coefficient of each characteristic indicator under this characteristic; calculating a comprehensive characteristic indicator of the characteristics concerned in each scenario according to the first weight coefficient and the characteristic indicator; obtaining a second weight coefficient corresponding to the comprehensive characteristic indicator in each scenario configured in advance; calculating an early warning indicator of the preset sea area based on the second weight coefficient and the comprehensive characteristic indicator in each scenario; inputting the early warning indicator into a pre-constructed early warning model, and 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 manner of the first aspect. Among them, the step of calculating the comprehensive feature index of the features of interest in each scenario according to 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 features of interest in each scenario.

[0008] In combination with the first aspect, an embodiment of the present invention provides a second possible implementation manner of the first aspect. Among them, the step of calculating the warning index of the preset sea area based on the second weight coefficient and the comprehensive feature index in each scenario includes: performing weighted calculation on the comprehensive feature index in each scenario according to the second weight coefficient to obtain the 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 manner of the first aspect. Among them, 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 corresponding relationship of warning levels; wherein, the corresponding relationship of warning levels includes a plurality of pre-configured warning index ranges and the warning levels 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; generating a warning message based on the warning level of the preset sea area.

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

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

[0012] Combined with the fourth possible implementation manner of the first aspect, an embodiment of the present invention provides a sixth possible implementation manner of the first aspect. Among them, the step of monitoring the cold source organisms in the preset sea area based on the volume scattering intensity of the cold source organisms further includes: statistically calculating 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 warning of the continuous increase of the cold source organisms based on the difference.

[0013] Combined with the fourth possible implementation manner of the first aspect, an embodiment of the present invention provides a seventh possible implementation manner of the first aspect. Among them, the step of monitoring the cold source organisms in the preset sea area based on the volume scattering intensity of the cold source organisms further 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; warning of the total weight of the invasion of the cold source organisms based on the total amount of organisms.

[0014] In a second aspect, an embodiment of the present invention further provides an early warning device for marine biological outbreaks. The device includes: an acquisition module for acquiring marine environmental data of at least one scenario included in a preset sea area; where the marine environmental data includes characteristic indicators for characterizing the marine environment in each scenario; a first module for obtaining a first weight coefficient of each characteristic indicator under the feature concerned by each scenario based on pre-configuration; a first calculation module for calculating a comprehensive characteristic indicator of the feature concerned in each scenario according to the first weight coefficient and the characteristic indicator; a second module for obtaining a second weight coefficient corresponding to the comprehensive characteristic indicator in each scenario based on pre-configuration; a second calculation module for calculating an early warning indicator of the preset sea area based on the second weight coefficient and the comprehensive characteristic indicator in each scenario; and an early warning module for inputting the early warning indicator into a pre-constructed early warning model, and outputting an early warning index corresponding to the early warning indicator through the early warning model to generate an early warning prompt based on the early warning index; where 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 run by a processor, it executes the steps of the method described in the first aspect above.

[0016] The embodiments of the present invention bring the following beneficial effects:

[0017] An ocean biological outbreak early warning method and device provided by an embodiment of the present invention can obtain ocean environment data of at least one scenario included in a preset sea area; obtain a first weight coefficient of each feature index under the feature based on features concerned by each pre-configured scenario; calculate a comprehensive feature index of the feature concerned in each scenario according to the first weight coefficient and the feature index; obtain a second weight coefficient corresponding to the comprehensive feature index in each pre-configured scenario; calculate an early warning index of the preset sea area based on the second weight coefficient and the comprehensive feature index in each scenario; input the early warning index into a pre-constructed early warning model, and output an early warning index corresponding to the early warning index through the early warning model to generate an early warning prompt based on the early warning index; moreover, the above first weight coefficient and second weight coefficient can be dynamically adjusted according to the actual ocean conditions, which can achieve accurate early warning and efficient on-site response, and the above early warning model is a model constructed based on a comprehensive evaluation function, which can effectively cover diverse ocean biological monitoring requirements and has important application value and technical significance.

[0018] Other features and advantages of the present invention will be described in the following description, and some of them will become obvious from the description, or be understood by implementing the present invention. The objectives and other advantages of the present invention are achieved and obtained by the structures specifically pointed out in the description, the claims and the drawings.

[0019] To make the above objectives, features and advantages of the present invention more obvious and understandable, the following specifically enumerates preferred embodiments and, in conjunction with the accompanying drawings, makes the following detailed description. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] To more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the following will briefly introduce the drawings required for use in the description of the specific embodiments or the prior art. Obviously, the following drawings are some embodiments of the present invention. For those skilled in the art, without creative efforts, other drawings can also be obtained based on these drawings.

[0021] Figure 1 It is a flowchart of an ocean biological outbreak early warning method provided by an embodiment of the present invention;

[0022] Figure 2 It is a flowchart of another ocean biological outbreak early warning method provided by an embodiment of the present invention;

[0023] Figure 3 It is a schematic structural diagram of an ocean biological outbreak early warning device provided by an embodiment of the present invention;

[0024] Figure 4 It is a schematic structural diagram of an electronic device provided by an embodiment of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0025] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings. Apparently, the described embodiments are some, but not all, of the embodiments of the present invention. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0026] Currently, early warning indicators based on single instantaneous values are mostly used to monitor and give early warnings about marine organisms, which are difficult to cover the monitoring requirements of diverse and complex marine organisms. Moreover, there is also a lack of a comprehensive early warning model for various marine organism outbreak scenarios in the related technologies, resulting in monitoring blind spots and lagging early warning responses in practical applications.

[0027] Based on this, a marine organism outbreak early warning method and device provided by the embodiments of the present invention can establish a comprehensive early warning index system for multiple scenarios, covering multi-dimensional monitoring requirements such as instantaneous impact warning of cold source biomass, continuous increment, and total invasion weight.

[0028] To facilitate the understanding of this embodiment, a marine organism outbreak early warning method disclosed by the embodiments of the present invention will be introduced in detail first.

[0029] In a possible implementation manner, the embodiments of the present invention provide a marine organism outbreak early warning method, as shown in the flowchart of a marine organism outbreak early warning method, and the method includes the following steps: Figure 1 as shown in the flowchart of a marine organism outbreak early warning method, and the method includes the following steps:

[0030] Step S102, obtaining marine environment data of at least one scenario included in a preset sea area;

[0031] Among them, the marine environment data in the embodiments of the present invention includes characteristic indicators for characterizing the marine environment in each scenario;

[0032] For example, a monitoring system can be deployed in advance in the preset sea area. For example, sonar sensors can be deployed to monitor underwater terrain 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 the marine environment data in the embodiments of the present invention can be obtained through further data preprocessing.

[0033] Specifically, the process of data preprocessing includes noise removal, signal enhancement, and a rationality check mechanism, etc. to verify the accuracy and integrity of the data. At the same time, for the convenience of analysis, the data can also be normalized, and the formula for normalization can be expressed as:

[0034]

[0035] Among them, Xi is a certain type of sensor data in the i-th scenario, and Xmax and Xmin respectively represent the maximum and minimum values of this data.

[0036] The specific data preprocessing process can be set according to the actual usage situation, and the embodiments of the present invention do not limit this.

[0037] Furthermore, the marine environment data collected by different sensors or detectors is equivalent to a characteristic index of the marine environment. For example, the characteristic index collected by a temperature sensor is temperature data, and the characteristic index collected by a sonar sensor is sonar data, etc. Therefore, the above-mentioned marine environment data in the embodiments of the present invention usually includes multiple characteristic indexes characterizing the marine environment in each scenario.

[0038] Step S104, based on the characteristics concerned in each pre-configured scenario, obtain the first weight coefficient of each characteristic index under this characteristic;

[0039] Step S106, calculate the comprehensive characteristic index of the characteristic concerned in each scenario according to the first weight coefficient and the characteristic index;

[0040] In actual use, the above-mentioned scenario refers to different regions distributed in a preset sea area. For example, the preset sea area includes three different regions: the nearest region A, the middle region B, and the farthest region C. At this time, correspondingly, there can be three scenarios, namely, scenario A, scenario B, and scenario C. Different sea areas or different scenarios have different characteristics concerned. For example, scenario A is the nearest region and needs to focus on the biological distribution. That is, the characteristic concerned in scenario A is the biological distribution; scenario B is the middle region and usually needs to focus on the environmental change situation and the biological distribution. That is, the characteristics concerned in scenario B are the environmental change situation and the biological distribution; scenario C is the farthest region and usually needs to focus on the environmental change situation. That is, the characteristic concerned in scenario C is the environmental change situation.

[0041] Generally, according to the different characteristics concerned in each scenario, the weights of its corresponding each characteristic index are also different. Therefore, for each scenario, the weight parameters of each characteristic index can be pre-configured according to the characteristics concerned, so that the calculated comprehensive characteristic index can be more accurate.

[0042] Therefore, in the above-mentioned step S104, based on the characteristics concerned in each pre-configured scenario, the weight parameters of each characteristic index, that is, the above-mentioned first weight parameters, can be obtained, and then the comprehensive characteristic index of this scenario can be calculated.

[0043] Further, considering that there are usually multiple scenarios in the preset sea area, for each of the above-mentioned comprehensive characteristic indicators corresponding to each scenario, further weighted calculation needs to be performed to obtain the warning indicator for the entire preset sea area, that is, the process including the following steps S108 to S112.

[0044] Step S108: Obtain the second weight coefficient corresponding to the comprehensive characteristic indicator in each scenario configured in advance.

[0045] Step S110: Calculate the warning indicator for the preset sea area based on the second weight coefficient and the comprehensive characteristic indicator in each scenario.

[0046] Step S112: Input the warning indicator into the pre-constructed warning model, and output the warning index corresponding to the warning indicator through the warning model, so as to generate a warning prompt based on the warning index.

[0047] Among them, the warning model in the embodiment of the present invention is a model constructed based on a comprehensive evaluation function.

[0048] In actual use, the above-mentioned first weight parameter and second weight parameter can be configured according to the actual use situation and combined with empirical values. Moreover, as the marine environment changes continuously, for example, seasonal and climatic changes, the first weight parameter and the second weight parameter can also be dynamically adjusted, so that the above-mentioned comprehensive characteristic indicator and warning indicator can better reflect the outbreak trend of marine organisms.

[0049] A method for warning of marine organism outbreaks provided by an embodiment of the present invention can obtain marine environment data of at least one scenario included in a preset sea area; obtain the first weight coefficient of each characteristic indicator under this characteristic based on the characteristics concerned in each scenario configured in advance; calculate the comprehensive characteristic indicator of the characteristic concerned in each scenario according to the first weight coefficient and the characteristic indicator; obtain the second weight coefficient corresponding to the comprehensive characteristic indicator in each scenario configured in advance; calculate the warning indicator for the preset sea area based on the second weight coefficient and the comprehensive characteristic indicator in each scenario; input the warning indicator into the pre-constructed warning model, and output the warning index corresponding to the warning indicator through the warning model, so as to generate a warning prompt based on the warning index. Moreover, the above-mentioned first weight coefficient and second weight coefficient can be dynamically adjusted according to the actual marine situation, which can 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 organism monitoring requirements and has important application value and technical significance.

[0050] In actual use, the above-mentioned marine environmental data can usually be stored in a database, and the accuracy and integrity of the data are verified through a rationality check mechanism. Among them, the rationality check includes outlier detection, data consistency verification, etc., to ensure that the data in the database can be used for subsequent analysis and modeling.

[0051] Furthermore, the marine environmental data in the embodiments of the present invention usually includes at least one of the following data: temperature data, dissolved oxygen concentration data, sonar data, pressure data, time parameter; among them, the pressure data in the embodiments of the present invention corresponds to underwater reliability information, and can also be called underwater pressure data, which is usually related to the underwater depth.

[0052] Generally, for the convenience of analysis and early warning of marine biological outbreaks, for the marine environmental data of a preset sea area, data construction can usually be carried out to obtain a data table containing the marine environmental data. For the convenience of understanding, Table 1 below shows a form of the data table:

[0053] Table 1:

[0054]

[0055] Among them, in Table 1 above, taking the preset sea area including the above three scenarios as an example, namely Scenario A, Scenario B, and Scenario C, which correspond to the nearest area, the middle area, and the farthest area respectively; and each scenario contains 5 characteristic indicators, including water temperature T, dissolved oxygen concentration DO, pressure P, sonar echo intensity B, and time stamp Time, corresponding to the above temperature data, dissolved oxygen concentration data, pressure data, sonar data, and time parameter respectively.

[0056] Furthermore, assuming that the characteristic of interest in the current preset sea area is biological density, which is usually denoted as D, the following further describes the marine biological outbreak early warning method in the embodiments of the present invention based on Table 1 above. Specifically, as Figure 2 shown in the flowchart of another marine biological outbreak early warning method, which includes the following steps:

[0057] Step S202, obtain the marine environmental data of at least one scenario included in the preset sea area;

[0058] Among them, the marine environmental data in the embodiments of the present invention includes the characteristic indicators used to characterize the marine environment in each scenario.

[0059] Specifically, referring to Table 1 above, assume that the marine environmental data of the preset sea area is constructed in the form of Table 1 above.

[0060] Step S204, based on the characteristics of interest in each scenario configured in advance, obtain the first weight coefficient of each characteristic indicator under this characteristic;

[0061] Step S206: Calculate the weighted sum of the feature indicators according to the first weight coefficient to obtain the comprehensive feature indicators of the features of interest in each scenario;

[0062] Specifically, taking the feature of interest in the above-mentioned preset sea area as the biological density as an example, based on Table 1, there are three scenarios. For each scenario, it is necessary to calculate the comprehensive feature indicators of the features of interest. Specifically, it can be calculated through the following formula:

[0063]

[0064] where Di is the comprehensive feature indicator, represents the weight coefficient of the j-th feature indicator in the i-th scenario, that is, the first weight parameter of the embodiments of the present invention, and Fj represents the specific value of the j-th feature indicator, which can be obtained from Table 1 above.

[0065] Assume that the calculation formula for the comprehensive feature indicator is D = 0.2T + 0.3DO + 0.1P + 0.4B. That is, when the feature of interest in the current preset sea area 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 densities in each scenario in Table 1 above are:

[0066] Scenario A: =

[0067] Scenario B: =

[0068] Scenario C: =

[0069] And the biological densities D1, D2, and D3 calculated for each scenario at this time are the comprehensive feature indicators of the features of interest in each scenario.

[0070] In actual use, when the above-mentioned feature of interest is other features, such as environmental features, etc., the above first weight parameter and the following second weight parameter can be configured into different parameters, specifically subject to the actual use situation, and the embodiments of the present invention do not limit this.

[0071] Step S208: Obtain the second weight coefficient corresponding to the comprehensive feature indicator in each scenario pre-configured;

[0072] Step S210: Calculate the weighted sum of the comprehensive feature indicators in each scenario according to the second weight coefficient to obtain the warning indicator of the preset sea area;

[0073] Specifically, continuing with the above Table 1 as an example, after obtaining the above biological densities D1, D2, and D3, the warning indicators for the above preset sea area can be further calculated. Specifically, the process of calculating the warning indicators can be represented by weighted calculation, and its calculation formula is expressed as:

[0074] ;

[0075] where S represents the comprehensive warning indicator; represents the weight coefficient of the i-th scenario, that is, the second weight parameter in the embodiments of the present invention, and satisfies = 1; n represents the number of scenarios, represents the comprehensive characteristic indicator of the i-th scenario, such as D1, D2, and D3 obtained above.

[0076] Among them, the second weight parameter here , , can be determined according to the importance of the scenario. For example w 1 , at this time, the warning indicator of the above preset sea area can be expressed as

[0077] Among them, the process of calculating the warning indicator is actually a process of fusing the comprehensive characteristic indicators of multiple scenarios. In the embodiments of the present invention, it is a process of fusing biological densities.

[0078] Further, after obtaining the fused warning indicator, the following steps can be further executed for warning prompt.

[0079] In actual use, an initial weight value can be pre-configured for the above first weight parameter and second weight parameter. Taking the second weight parameter as an example, assuming that at the initial allocation, the second weight parameter of scenario A is 0.6 and the second weight parameter of scenario B is 0.4, the weights can be optimized by the gradient descent algorithm so that the comprehensive warning indicator can better reflect the outbreak trend of plankton.

[0080] Specifically, the optimization formula can be expressed as the following formula:

[0081] ,

[0082] Among them, represents the weight coefficient of the i-th scenario in the t-th iteration step, represents the learning rate, represents the loss function, and the mean square error can be used for calculation. When the change amount of the loss function is less than a certain threshold, the iteration terminates. After iterative optimization, the optimal weights are obtained: for example, the optimized weight of scenario A is 0.7 and the weight of scenario B is 0.3.

[0083] In specific implementation, the dynamic adjustment process of the above weight parameters can be set according to the actual usage, and the embodiments of the present invention do not limit this.

[0084] Step S212: Input the warning index into a pre-constructed warning model, and output the warning index corresponding to the warning index through the warning model.

[0085] Step S214: Search for the warning index range to which the warning index belongs in the pre-configured corresponding relationship of warning levels.

[0086] Among them, the corresponding relationship of warning levels includes multiple pre-configured warning index ranges, and the warning levels corresponding to each warning index range.

[0087] Step S216: 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, and generate a warning message based on the warning level of the preset sea area.

[0088] Specifically, in the embodiments of the present invention, the warning model is a model constructed based on a comprehensive evaluation function, which can be expressed as the following decision-making process:

[0089]

[0090] Among them, W represents the final warning decision, that is, the warning index in the embodiments of the present invention, f is a weighted non-linear comprehensive evaluation function used to output a warning result according to the comprehensive warning index Si, and Si is the warning index of different features concerned.

[0091] Furthermore, the multiple warning index ranges included in the above corresponding relationship of warning levels can usually be pre-configured. For example, when the 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.

[0092] When the final warning index output by the above prediction model is W = 0.72, it indicates a medium risk of marine biological outbreak.

[0093] The above warning index range can be set according to the actual usage, and the embodiments of the present invention do not limit this.

[0094] Moreover, the above method of multi-scenario, multi-sensor data fusion and dynamic weight adjustment enables the 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.

[0095] In addition, for the above warning information, it can also be indicated by colors. For example, the warning information is displayed through color codes (orange or blue), which can intuitively guide on-site staff to take corresponding measures.

[0096] Furthermore, 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.

[0097] 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.

[0098] Specifically, the monitoring of cold source organisms in the embodiments of the present invention includes instantaneous impact warning monitoring of cold source organisms, continuous increment warning monitoring of cold source organisms, and total invasion weight warning monitoring of cold source organisms.

[0099] Specifically, when conducting instantaneous impact warning monitoring of cold source organisms, the change rate of the number of cold source organisms can be calculated based on the volume scattering intensity of cold source organisms; wherein, 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.

[0100] Among them, the volume scattering intensity of cold source organisms is usually represented by SV, also known as the acoustic backscattering volume intensity of cold source organisms in a cluster state. The above change rate of the number of cold source organisms can be expressed as ΔSV / Δt, which represents the change amount of the volume scattering intensity of cold source organisms per unit time, with the unit of decibels per cubic meter per minute (dB / m3*min), representing the change rate of the number of monitored objects.

[0101] For example, it is set that when 10dB < ΔSV / Δt < 20dB (10 to 100 times larger than the normal marine organisms), it indicates that a large number of organisms are pouring into the water intake, and when ΔSV / Δt > 20dB, it indicates that a huge number of organisms are currently pouring into the water intake. That is, different warning levels can be set according to the actual situation to give an early warning of the instantaneous impact of cold source organisms. The specific warning level can be set according to the actual usage situation, and the embodiments of the present invention do not limit this.

[0102] Furthermore, when conducting continuous increment warning monitoring of cold source organisms, the cumulative amount of the volume scattering intensity of cold source organisms within a preset time period can be statistically calculated; the difference between the cumulative amount and a preset cumulative characteristic value is compared; and an early warning of the continuous increment of cold source organisms is made based on the difference.

[0103] Specifically, when implemented, the cumulative amount of the volume scattering intensity of cold source organisms within a preset time period is represented by ΣSV, and its unit is decibels per cubic meter (dB).

[0104] Generally, the cumulative amount of the volume scattering intensity of cold source organisms in a period of time, such as 30 minutes, before the current time can be calculated, that is, the cumulative amount in adjacent time periods. And usually, the cumulative amounts of various types such as suspended sediment, jellyfish, fish schools, floating garbage, etc. can be calculated separately. Then, the cumulative amount of each type is compared with the characteristic value of the corresponding type to obtain a difference. And in order to improve the accuracy and universality of statistics, the cumulative amounts in adjacent time periods can be compared multiple times to obtain a difference. If the difference is greater than a certain threshold, it indicates that there is a continuous incremental outbreak of cold source organisms. That is, an early warning of the continuous increment of cold source organisms is made according to the difference.

[0105] Furthermore, in the embodiments of the present invention, when warning and monitoring the total invasion weight of cold source organisms, the average flux value of cold source organisms can be calculated according to the volume scattering intensity of cold source organisms; and the total biomass can be calculated according to the average flux value; then, an early warning of the total invasion weight of cold source organisms is made based on the total biomass.

[0106] Specifically, during the monitoring of cold source organisms using a sonar sensor, when cold source organisms enter the sonar detection beam, since the volume scattering intensity (SV) value of cold source organisms measured by the sonar is proportional to its density (n) and the average single-target intensity (TS), that is, expressed by the formula:

[0107] n = SV / TS;

[0108] Since the sonar will perform acoustic radiation on the cold source organisms multiple times during the process of the cold source organisms passing through the sonar detection beam, the average value of multiple received and transmitted echoes is actually used in the above formula.

[0109] On this basis, by measuring the average flow velocity v in the direction towards the shore end of the water intake, the absolute value of the average flux of cold source organisms, that is, the average flux value of cold source organisms in the embodiments of the present invention, is calculated, and its formula is expressed as: |F| = n * v;

[0110] Therefore, within time t, the total biomass passing through the monitoring section (area S) is

[0111] B = |F| * S * t; that is, the total biomass in the embodiments of the present invention.

[0112] Furthermore, for this total biomass, the total weight can also be calculated according to the average weight of the organisms. For example, multiplying the above total biomass by the average weight of the organisms can obtain the total weight, where the average weight is obtained from historical experience accumulation or by referring to relatively authoritative biological survey data.

[0113] Based on the above-mentioned total biomass, or total weight, it is possible to achieve early warning of the total weight of invasive cold-source organisms. For example, corresponding early warning thresholds can be set according to the actual sea area, so as to give an early warning prompt when the threshold is exceeded, in order to prompt on-site staff to take corresponding measures.

[0114] In actual use, the above-mentioned early warning model or cold-source organism monitoring, including instantaneous impact early warning monitoring of cold-source organisms, continuous increment early warning monitoring of cold-source organisms, and total weight early warning monitoring of invasive cold-source organisms, etc., can be connected to the corresponding AI model, and at the same time, a knowledge base required for the AI model is established to achieve early warning prompts for marine organism outbreaks with the help of the AI model. Specifically, it can be set according to the actual use situation, and the embodiments of the present invention do not limit this.

[0115] In summary, the marine organism outbreak early warning method provided by the embodiments of the present invention can fuse sonar data in different scenarios, extract representative characteristic indicators, and through multi-dimensional data fusion, can enhance the prediction ability and robustness of the prediction model.

[0116] At the same time, according to the monitoring requirements of cold-source organism quantity, it is possible to establish instantaneous impact early warning of cold-source organisms, continuous increment early warning of cold-source organisms, total weight early warning of invasive cold-source organisms, etc., and achieve multi-dimensional comprehensive early warning indicators such as AI early warning of cold-source organisms. By comparing the deviation between historical data and new data, the weight parameters of the early warning indicators can be dynamically adjusted to ensure the real-time performance and accuracy of the early warning model.

[0117] Furthermore, according to the early warning prompt, corresponding emergency decisions can be triggered to guide on-site actions, and, according to the actual situation, the early warning model can be continuously optimized and adjusted to improve the early warning accuracy and response speed.

[0118] Furthermore, the embodiments of the present invention also provide a marine organism outbreak early warning device, as Figure 3 shown in the structural schematic diagram of a marine organism outbreak early warning device, the device includes:

[0119] An acquisition module 30, configured to acquire marine environment data of at least one scenario included in a preset sea area; wherein, the marine environment data includes characteristic indicators for characterizing the marine environment in each of the scenarios;

[0120] A first module 32, configured to obtain a first weight coefficient of each characteristic indicator under the feature concerned for each of the scenarios based on the pre-configured features;

[0121] A first calculation module 34, configured to calculate a comprehensive characteristic indicator of the feature concerned for each of the scenarios according to the first weight coefficient and the characteristic indicator;

[0122] The second module 36 is used to obtain the second weight coefficient corresponding to the comprehensive feature index in each of the above scenarios

[0123] The second calculation module 38 is used to calculate the warning index of the preset sea area based on the second weight coefficient and the comprehensive feature index in each of the above scenarios

[0124] The warning module 39 is used to input the warning index into a pre-constructed warning model, and output the warning index corresponding warning index through the warning model, so as to generate a warning prompt based on the warning index; wherein, the warning model is a model constructed based on a comprehensive evaluation function

[0125] Furthermore, the above-mentioned first calculation module 34 is also used for:

[0126] Perform weighted calculation on the feature index according to the first weight coefficient to obtain the comprehensive feature index of the feature of interest in each of the above scenarios

[0127] Furthermore, the above-mentioned second calculation module 38 is also used for:

[0128] Perform weighted calculation on the comprehensive feature index in each of the above scenarios based on the second weight coefficient to obtain the warning index of the preset sea area

[0129] Furthermore, the above-mentioned warning module 39 is also used for:

[0130] Search 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 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 a warning message based on the warning level of the preset sea area

[0131] Furthermore, the above-mentioned marine environmental data includes at least one of the following data: temperature data, dissolved oxygen concentration data, sonar data, pressure data, time parameter

[0132] The above-mentioned device is also used for:

[0133] Extract the sonar data included in the marine environmental data; perform data processing on the sonar data to obtain the volume scattering intensity of cold source organisms; monitor the cold source organisms in the preset sea area based on the volume scattering intensity of cold source organisms

[0134] Wherein, the step of monitoring the cold source organisms in the preset sea area based on the volume scattering intensity of cold source organisms includes:

[0135] Calculate 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 amount of the volume scattering intensity of the cold source organisms per unit time; issue a warning for the instantaneous impact of the cold source organisms based on the change rate; and,

[0136] Statistically calculate the cumulative amount of the volume scattering intensity of the cold source organisms within a preset time period; compare the difference between the cumulative amount and a preset cumulative characteristic value; issue a warning for the continuous increase of the cold source organisms based on the difference; and,

[0137] Calculate the average flux value of the cold source organisms based on the volume scattering intensity of the cold source organisms; and, calculate the total amount of organisms based on the average flux value; issue a warning for the total weight of the invasion of the cold source organisms based on the total amount of organisms.

[0138] The marine organism outbreak warning device provided by the embodiments of the present invention has the same technical features as the marine organism outbreak warning method provided by the above embodiments, so it can also solve the same technical problems and achieve the same technical effects.

[0139] Furthermore, the embodiments of the present invention also provide an electronic device, including a memory, a processor, and a computer program stored on the memory and executable on the processor. When the processor executes the computer program, the steps of the above method are implemented.

[0140] The embodiments of the present invention also provide a computer-readable storage medium, on which a computer program is stored. When the computer program is run by a processor, the steps of the above method are executed.

[0141] Furthermore, the embodiments of the present invention also provide a schematic structural diagram of an electronic device, as Figure 4 shown, which is the schematic structural diagram of the electronic device. Among them, 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. The processor 41 executes the computer-executable instructions to implement the above method.

[0142] In Figure 4 the illustrated embodiment, the electronic device further includes a bus 42 and a communication interface 43. Among them, the processor 41, the communication interface 43, and the memory 40 are connected through the bus 42.

[0143] Among them, the memory 40 may include high-speed random access memory (RAM), and may also include non-volatile memory, such as at least one disk memory. The communication connection between this 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, 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 the sake of convenience of representation, Figure 4 only a bidirectional arrow is used in Figure 4 , but it does not mean that there is only one bus or one type of bus.

[0144] The processor 41 may be an integrated circuit chip with the ability to process signals. In the implementation process, each step of the above method can be completed by the integrated logic circuit in the hardware of the processor 41 or the instructions in the form of software. The above-mentioned processor 41 can be a general-purpose processor, including a central processing unit (CPU for short), a network processor (NP for short), etc.; it can also be a digital signal processor (DSP for short), an application specific integrated circuit (ASIC for short), a field programmable gate array (FPGA for short) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components. The general-purpose processor can be a microprocessor or the processor can also be any conventional processor, etc. The steps of the method disclosed in combination with the embodiments of the present invention can be directly embodied as being executed and completed by a hardware decoding processor, or executed and completed by a combination of the hardware and software modules in the decoding processor. The software module can be located in a mature storage medium in the art such as random access memory, flash memory, read-only memory, programmable read-only memory, or electrically erasable programmable memory, register, etc. This storage medium is located in the memory, and the processor 41 reads the information in the memory and combines its hardware to complete the foregoing method.

[0145] A computer program product of an ocean biological outbreak warning method and device provided by an embodiment of the present invention includes a computer-readable storage medium storing program codes. The instructions included in the program codes can be used to execute the method described in the foregoing method embodiments. For specific implementation, reference can be made to the method embodiments, which will not be elaborated herein.

[0146] Those skilled in the art can clearly understand that for the convenience and conciseness of description, the specific working process of the above-described device can refer to the corresponding process in the foregoing method embodiments, which will not be elaborated herein.

[0147] In addition, in the description of the embodiments of the present invention, unless otherwise clearly defined and limited, the terms "installation", "connection", and "connection" shall be understood in a broad sense. For example, it may be a fixed connection, a detachable connection, or an integral connection; it may be a mechanical connection or an electrical connection; it may be a direct connection or an indirect connection through an intermediate medium, and it may be the communication inside 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 situations.

[0148] If the above functions are implemented in the form of software function 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, in essence, or the part that contributes to the prior art, or a part of this technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present invention. The foregoing storage medium includes: various media such as USB flash drives, mobile hard disks, read-only memories (ROM, Read-Only Memory), random access memories (RAM, Random Access Memory), magnetic disks, or optical discs that can store program codes.

[0149] In the description of the present invention, it should be noted that the orientation or positional relationship indicated by the terms "center", "upper", "lower", "left", "right", "vertical", "horizontal", "inner", "outer", etc. is based on the orientation or positional relationship shown in the drawings. It is 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 should not be construed as a limitation of the present invention. In addition, the terms "first", "second", and "third" are only used for descriptive purposes and cannot be understood as indicating or implying relative importance.

[0150] Finally, it should be noted that the above embodiments are only specific implementation manners of the present invention, used to illustrate the technical solutions of the present invention, rather than limiting it. The protection scope of the present invention is not limited thereto. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that any person skilled in the art within the technical scope disclosed by the present invention can still modify the technical solutions recorded in the foregoing embodiments, or can easily think of changes, or perform equivalent replacements on some of the technical features; 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 all be covered within the protection scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.

Claims

1. An early warning method for marine organism outbreaks, characterized in that, The method includes: Obtaining marine environmental data of at least one scenario included in a preset sea area; wherein, the marine environmental data includes characteristic indicators for characterizing the marine environment under each of the scenarios; the scenario refers to different regions distributed according to distance in the preset sea area; Based on the characteristics concerned for each of the scenarios pre-configured, obtaining a first weight coefficient of each characteristic indicator under this characteristic; wherein, the characteristic concerned for each of the scenarios is the biological density; Calculating a comprehensive characteristic indicator of the characteristic concerned under each of the scenarios according to the first weight coefficient and the characteristic indicator; Obtaining a second weight coefficient corresponding to the comprehensive characteristic indicator under each of the scenarios pre-configured; Calculating a warning indicator of the preset sea area based on the second weight coefficient and the comprehensive characteristic indicator under each of the scenarios; Inputting the warning indicator into a pre-constructed warning model, and outputting a warning index corresponding to the warning indicator through the warning model, so as to generate a warning prompt based on the warning index; wherein, the warning model is a model constructed based on a comprehensive evaluation function; Wherein, the step of calculating a comprehensive characteristic indicator of the characteristic concerned under each of the scenarios according to the first weight coefficient and the characteristic indicator includes: Performing weighted calculation on the characteristic indicator according to the first weight coefficient to obtain a comprehensive characteristic indicator of the characteristic concerned under each of the scenarios; The step of calculating a warning indicator of the preset sea area based on the second weight coefficient and the comprehensive characteristic indicator under each of the scenarios includes: Performing weighted calculation on the comprehensive characteristic indicator under each of the scenarios based on the second weight coefficient to obtain a warning indicator of the preset sea area.

2. 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 a pre-configured warning level correspondence; wherein, the warning level correspondence includes a plurality of pre-configured warning index ranges, and the 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; Generating a warning message based on the warning level of the preset sea area.

3. The method according to claim 1, characterized in that, The marine environmental data includes at least one of the following data: temperature data, dissolved oxygen concentration data, sonar data, pressure data, time parameter; The method further includes: Extracting the sonar data included in the marine environmental data; Performing data processing on the sonar data to obtain the volume scattering intensity of cold source organisms; Monitoring the cold source organisms in the preset sea area based on the volume scattering intensity of cold source organisms.

4. The method according to claim 3, characterized in that The step of monitoring the cold source organisms in the preset sea area based on the volume scattering intensity of cold source organisms includes: Calculating the change rate of the number of cold source organisms according to the volume scattering intensity of cold source organisms; wherein, the change rate is the change amount of the volume scattering intensity of cold source organisms per unit time; Warning of an instantaneous impact of cold source organisms based on the change rate.

5. The method according to claim 3, characterized in that The step of monitoring the cold source organisms in the preset sea area based on the volume scattering intensity of cold source organisms further includes: Statistically accumulate the volume scattering intensity of the cold source organisms within a preset time period; Compare the difference between the accumulated amount and a preset cumulative characteristic value; Based on the difference, give an early warning of the continuous increase of the cold source organisms.

6. The method according to claim 3, wherein The steps of monitoring the cold source organisms in a preset sea area based on the volume scattering intensity of the cold source organisms further include: Calculate the average flux value of the cold source organisms according to the volume scattering intensity of the cold source organisms; and calculate the total biomass according to the average flux value; Based on the total biomass, give an early warning of the total weight of the invasion of the cold source organisms.

7. An early warning device for marine biological outbreaks, characterized in that, The device includes: An acquisition module for acquiring marine environmental data of at least one scenario included in a preset sea area; wherein, the marine environmental data includes characteristic indicators for characterizing the marine environment in each scenario; the scenario refers to different regions distributed according to distance in the preset sea area; A first module for obtaining a first weight coefficient of each characteristic indicator under this characteristic based on the characteristics concerned by each preset scenario; wherein, the characteristic concerned by each scenario is the biological density; A first calculation module for calculating a comprehensive characteristic indicator of the characteristic concerned in each scenario according to the first weight coefficient and the characteristic indicator; A second module for obtaining a second weight coefficient corresponding to the comprehensive characteristic indicator in each preset scenario; A second calculation module for calculating an early warning indicator of the preset sea area based on the second weight coefficient and the comprehensive characteristic indicator in each scenario; An early warning module for inputting the early warning indicator into a pre-constructed early warning model, and 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; Among them, the first calculation module is used for: Perform weighted calculation on the characteristic indicator according to the first weight coefficient to obtain a comprehensive characteristic indicator of the characteristic concerned in each scenario; The second calculation module is used for: Perform weighted calculation on the comprehensive characteristic indicator in each scenario based on the second weight coefficient to obtain the early warning indicator of the preset sea area.

8. A computer-readable storage medium, characterized in that, A computer program is stored on the computer-readable storage medium, and when the computer program is run by a processor, it executes the steps of the method according to any one of claims 1 to 6 above.

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