Data-driven alien invasive species supervision method and supervision system

Abstract

The invention discloses a data-driven alien invasive species supervision method and supervision system, and relates to the technical field of data processing, and the method comprises the steps: building a species label library of a target supervision region, carrying out the dependency relationship recognition, and outputting a species dependency relationship network; when the alien invasive species are monitored, acquiring invasive species information; the trained chain type influence analysis model is downloaded, chain type analysis is carried out on invasive species information in combination with the species dependency relationship network, chain type influence indexes are obtained, and the direct influence index is the influence degree of population reduction in the species label library directly caused by the invasive species information; the indirect influence index is the influence degree of reduction of other populations caused by directly reduced populations; and uploading the chain influence index to an invasive species supervision platform, and cleaning alien invasive species according to cleaning equipment. The technical problem that in the prior art, the treatment efficiency of the invasive species is poor is solved, and the technical effect of efficient treatment of the invasive species is achieved.

Description

Technical Field

[0001] The present invention relates to the technical field of data processing, and particularly relates to a data-driven method and system for monitoring alien invasive species. Background Art

[0002] With the acceleration of globalization and the expansion of human activities, the threat of alien invasive species to local ecosystems is increasing day by day. In the fields of agricultural production, ecological protection, and urban management, the control of invasive species has become an important task. However, with the increase in the complexity of ecosystems and the diversification of the spread patterns of invasive species, the monitoring and control of invasive species also face severe challenges. Traditional methods for monitoring invasive species usually rely on manual observation or single monitoring means, and have problems such as limited monitoring scope, slow response speed, and low control efficiency, making it difficult to meet the needs of current ecological protection work. Summary of the Invention

[0003] This application provides a data-driven method and system for monitoring alien invasive species, which are used to solve the technical problem in the prior art of poor control efficiency of invasive species.

[0004] In view of the above problems, this application provides a data-driven method and system for monitoring alien invasive species.

[0005] In the first aspect of this application, a data-driven method for monitoring alien invasive species is provided. The method includes:

[0006] Establish a species tag library for the target monitoring area; identify the dependency relationships in the species tag library and output a species dependency network; when the invasive species monitoring platform detects an alien invasive species, obtain the information of the invasive species; download the trained chain impact analysis model in the invasive species monitoring platform, and perform chain analysis on the invasive species information in combination with the species dependency network to obtain a chain impact index, where the chain impact index is calculated through a direct impact index and multiple indirect impact indices. The direct impact index is the degree of impact of the invasive species information directly causing a reduction in the population in the species tag library, and the indirect impact index is the degree of impact of the directly reduced population causing a reduction in other populations; upload the chain impact index to the invasive species monitoring platform, and clean the alien invasive species according to the cleaning equipment connected to the invasive species monitoring platform.

[0007] In the second aspect of this application, a data-driven system for monitoring alien invasive species is provided. The system includes:

[0008] A tag library building module for building a species tag library for a target supervision area; a dependency relationship recognition module for recognizing the dependency relationships in the species tag library and outputting a species dependency relationship network; an invasive species information acquisition module for acquiring invasive species information when an invasive species supervision platform detects an alien invasive species; a chain analysis module for downloading a trained chain impact analysis model in the invasive species supervision platform and performing chain analysis on the invasive species information in combination with the species dependency relationship network to obtain chain impact indicators, where the chain impact indicators are calculated through direct impact indicators and multiple indirect impact indicators, and the direct impact indicator is the degree of impact of the invasive species information directly causing a reduction in the population in the species tag library, and the indirect impact indicator is the degree of impact of the directly reduced population causing a reduction in other populations; a cleaning module for uploading the chain impact indicators to the invasive species supervision platform and cleaning the alien invasive species according to the cleaning equipment connected to the invasive species supervision platform.

[0009] One or more technical solutions provided in this application have at least the following technical effects or advantages:

[0010] This application builds a species tag library for a target supervision area; recognizes the dependency relationships in the species tag library and outputs a species dependency relationship network; acquires invasive species information when an invasive species supervision platform detects an alien invasive species; downloads a trained chain impact analysis model in the invasive species supervision platform and performs chain analysis on the invasive species information in combination with the species dependency relationship network to obtain chain impact indicators, where the chain impact indicators include direct impact indicators and multiple indirect impact indicators, and the direct impact indicator is the degree of impact of the invasive species information directly causing a reduction in the population in the species tag library, and the indirect impact indicator is the degree of impact of the directly reduced population causing a reduction in other populations; uploads the chain impact indicators to the invasive species supervision platform and cleans the alien invasive species according to the cleaning equipment connected to the invasive species supervision platform. This invention solves the technical problem of the poor efficiency of controlling invasive species in the prior art. By conducting ecological surveys and data mining to build a species tag library, using dependency relationship analysis to generate a species dependency relationship network, combining with a chain impact analysis model to quantitatively evaluate the multi-level impact of alien invasive species on the ecosystem, generating chain impact indicators, and optimizing the scheduling of cleaning equipment, it achieves the technical effect of efficiently controlling invasive species. Description of the Drawings

[0011] To more clearly illustrate the technical solutions in the embodiments of the present invention, the following will briefly introduce the accompanying drawings required for the description of the embodiments. Obviously, the accompanying drawings in the following description are only some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other accompanying drawings can be obtained based on these drawings.

[0012] Figure 1 Schematic flow chart of a data-driven method for monitoring alien invasive species provided by an embodiment of the present application;

[0013] Figure 2 Schematic structural diagram of a data-driven system for monitoring alien invasive species provided by an embodiment of the present application.

[0014] Explanation of reference numerals: Tag library establishment module 11, Dependency relationship recognition module 12, Invasive species information acquisition module 13, Chain analysis module 14, Cleaning module 15. Detailed implementation manners

[0015] The present application provides a data-driven method and system for monitoring alien invasive species, aiming to solve the technical problem of poor efficiency in controlling invasive species in the existing technology. By conducting ecological surveys and data mining to establish a species tag library, using dependency relationship analysis to generate a species dependency relationship network, combining a chain impact analysis model to quantitatively evaluate the multi-level impacts of alien invasive species on the ecosystem, generating chain impact indicators, and optimizing the scheduling of cleaning equipment, the technical effect of efficiently controlling invasive species is achieved.

[0016] The following will clearly and completely describe the technical solutions in the embodiments of the present application with reference to the accompanying drawings in the embodiments of the present application. Obviously, the described embodiments are only some embodiments of the present application, rather than all embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative efforts belong to the scope of protection of the present application.

[0017] It should be noted that any variations of the terms "including" and "having" are intended to cover non-exclusive inclusions. For example, a process, method, system, product, or server that includes a series of steps or units does not necessarily have to be limited to those clearly listed steps or units, but may include other steps or modules that are not clearly listed or are inherent to these processes, methods, products, or devices.

[0018] Embodiment 1, as Figure 1 shown, the present application provides a data-driven method for monitoring alien invasive species, and the method includes:

[0019] Step S100: Establish a species tag library for the target monitoring area.

[0020] In the embodiment of the present application, first, through a data collection method, using channels such as field surveys, remote sensing technology, species databases, and literature, the basic information of all species in the target area is collected. Then, a species classification and annotation method is adopted to classify the collected species data. Specifically, according to taxonomic principles, species are classified into taxonomic levels such as families, genera, and species, and each species is assigned a clear label. After the annotation is completed, the information of each species is sorted out to obtain the species label library of the target supervision area.

[0021] Step S200: Identify the dependency relationships in the species label library and output a species dependency network.

[0022] In the embodiment of the present application, first, the invasive species supervision platform accesses the ecological literature library, extracts the dependency relationship labels between species, such as predation, competition, and mutual benefit relationships. Then, based on these dependency relationship labels, the dependency weights between species are calculated to generate a species dependency relationship matrix, which reflects the intensity of the dependency between species. Finally, a species dependency network is constructed using this matrix, where each species is a node in the network, and the dependency relationship between species is represented by the weight of the edge.

[0023] Furthermore, in the method provided by the application embodiment, when outputting the species dependency network, it further includes:

[0024] The invasive species supervision platform accesses the ecological literature library through an API interface, extracts the dependency relationship labels between species from the ecological literature library, including predation relationship labels, competition relationship labels, and mutual benefit relationship labels; calculates the species dependency weights of the species label library according to the dependency relationship labels to generate a species dependency relationship matrix, and constructs the species dependency network using the species dependency relationship matrix. The nodes of the species dependency network represent species, and the edge weights represent the intensity of the dependency.

[0025] In the embodiment of the present application, the invasive species supervision platform accesses the ecological literature library through an API interface. The ecological literature library is a resource library containing a large amount of ecological research data and literature, including ecological interaction information between different species. Through the API interface, the invasive species supervision platform automatically extracts the required dependency relationship labels from this literature library. These labels specifically include the predation relationship between species (i.e., one species is the food source of another species), the competition relationship (i.e., the competition for resources between species), and the mutual benefit relationship (i.e., the relationship where species obtain mutual benefits through cooperation).

[0026] Next, calculate the species dependence weights of the species label library according to the dependence relationship tags. Specifically, for the predation relationship, consider factors such as predation frequency, predation success rate, and population density ratio. The predation frequency refers to the frequency of predation events, the predation success rate is the probability that a predator successfully captures its prey, and the population density ratio reflects the population ratio between the predator and the prey. These data are determined by technical experts. For example, if the predation frequency is 0.8, the predation success rate is 0.7, and the population density ratio is 0.6, the predation relationship weight calculated by multiplying the predation frequency × predation success rate × population density ratio is 0.336. For the competition relationship, the weight calculation is based on the resource competition ratio and the population density ratio. For example, if the resource competition ratio between species A and species B is 0.5 and the population density ratio is 0.7, the weight of the competition relationship obtained by multiplying the resource competition ratio × population density ratio is 0.35. For the mutual benefit relationship, the weight calculation depends on the cooperation benefit and the cooperation frequency. For example, if the benefits of species A and B are 0.6 and 0.7 respectively, and the cooperation frequency is 0.9, by The obtained mutual benefit relationship weight is 0.585. Finally, all the calculated weights are normalized to ensure that the maximum value is 1, so that the weights are between 0 and 1.

[0027] After obtaining the dependence weights between species, organize these weights into a species dependence relationship matrix, where each element of the matrix represents the dependence strength between two species. Next, use the species dependence relationship matrix to construct a species dependence relationship network. In this network, nodes represent species, edges represent the dependence relationships between species, and the weights of the edges are determined by the dependence weights between species.

[0028] Step S300: When the invasive species supervision platform detects an alien invasive species, obtain the information of the invasive species.

[0029] In the embodiment of the present application, the invasive species supervision platform monitors the species in the target area in real time through sensors, image acquisition (such as drone photography or satellite images), etc. By comparing the monitored species information with the existing species data in the species label library, if the species is not in the label library, the platform will determine it as an alien invasive species.

[0030] To obtain information on invasive species, first, the population quantity of alien invasive species is obtained through simple field investigation and sample collection methods. To calculate the proportion of local species' resources occupied by invasive species, it is calculated by comparing the consumption of invasive species and local species on the same resource. For example, if local species A consumes 500 liters of water per day, and invasive species B consumes 400 liters of water per day, and the total water source is 2000 liters, then it is calculated that species B occupies 20% of the total water source resources, and species A occupies 25% of the resources. By comparing these two proportions, it is obtained that the proportion of invasive species B occupying the resources of local species A is 80%, that is, species B occupies 80% of the resources of local species A.

[0031] Through the above process, information on invasive species is obtained.

[0032] Step S400: Download the trained chain impact analysis model in the invasive species supervision platform, and combine the species dependence network to conduct chain analysis on the invasive species information to obtain chain impact indicators. The chain impact indicators are calculated through direct impact indicators and multiple indirect impact indicators. Among them, the direct impact indicator is the degree of impact of the invasive species information directly causing the reduction of the population in the species label library, and the indirect impact indicator is the degree of impact of the directly reduced population causing the reduction of other populations.

[0033] In the embodiment of the present application, the trained chain impact analysis model is downloaded in the invasive species supervision platform, and the chain analysis is conducted on the invasive species information in combination with the species dependence network to obtain chain impact indicators. Specifically, by combining the species dependence network to conduct chain analysis on the invasive species information, the direct impact indicator and multiple indirect impact indicators are determined, and then the chain impact indicators are calculated through the expression of the chain impact indicators. Among them, the direct impact indicator is calculated through the expression of the direct impact indicator, and the direct impact indicator is the degree of impact of the invasive species information directly causing the reduction of the population in the species label library. The indirect impact indicator is calculated through the expression of the indirect impact indicator, and it is the degree of impact of the directly reduced population causing the reduction of other populations.

[0034] Furthermore, in the method provided by the application embodiment, the expression for the chain impact analysis model to calculate the chain impact indicator EDI is:

[0035]

[0036] where i is the i-th species in the species label library, I dierct (i) is the direct impact indicator of the alien invasive species on the i-th species, $EDI_{it}$ is the indirect impact index of the alien invasive species on the $i$-th species at the $t$-th layer. $T$ is the maximum number of layers of the spread of the alien invasive species affecting the species dependence network, which is used to limit the depth of the chain impact analysis. $\alpha$ is the attenuation coefficient, and $\Delta EDI$ is the impact error based on the random perturbation of environmental factors.

[0037] In the embodiment of the present application, the chain impact index $EDI$ is calculated through the chain impact analysis model. Among them, $EDI$ is the chain impact index, which quantifies the comprehensive impact of the invasive species on all species in the target ecosystem. The direct impact index is calculated through the expression of the preset direct impact index, and the indirect impact index is calculated through the expression of the preset indirect impact index. Among them, the maximum number of layers of the spread of the alien invasive species affecting the species dependence network, the attenuation coefficient, and the impact error based on the random perturbation of environmental factors are determined in advance by technical experts. $T$ is a positive integer greater than 0. Through the calculation of the expression of the chain impact index $EDI$, the chain impact index is obtained.

[0038] Furthermore, in the method provided by the application embodiment, the expression for calculating the direct impact index is:

[0039] $I$ dierct $(i)=W$ predation $(i)\cdot P$ inv $+W$ competition $(i)R$ inv ;

[0040] Among them, $W$ predation is the predation weight of the alien invasive species on species $i$, $P$ inv is the population quantity of the alien invasive species in the invasive species information, $W$ competition is the resource occupancy ratio weight of the alien invasive species on species $i$, $R$ inv is the resource occupancy ratio of the alien invasive species in the invasive species information.

[0041] In the embodiment of the present application, the direct impact index is calculated through the expression of the direct impact index. The direct impact index is used to quantify the degree of impact of the invasive species directly causing the reduction of the population of the target species $i$, including two aspects: predation behavior and resource competition.

[0042] In the expression of the direct impact index, the predation weight of the alien invasive species on species $i$ and the resource occupancy ratio weight of the alien invasive species on species $i$ are determined by technical experts in combination with historical experience and ecological data. The population quantity of the alien invasive species and the resource occupancy ratio of the alien invasive species are extracted from the aforementioned invasive species information. Finally, these parameters are substituted into the expression of the direct impact index for calculation to obtain the direct impact index.

[0043] Furthermore, in the method provided by the application embodiment, the expression for calculating the indirect impact index is:

[0044]

[0045] Among them, W interaction (i, k) is the interaction weight between species i and species k in the species dependence relationship network, i is the target species whose indirect impact is being analyzed, k is the species that has a dependence relationship with species i, t is the level of the current indirect impact, is the indirect impact index of species k at the (t - 1)-th layer.

[0046] In the embodiments of the present application, when calculating through the expression of the indirect impact index, first, the interaction weight between species i and species k in the species dependence relationship network is obtained. This weight is the edge weight between two species in the species dependence relationship network. i is the target species whose indirect impact is being analyzed, and k is the species that has a dependence relationship with species i. The indirect impact index represents the indirect impact of species k on other species at the previous layer ((t - 1)-th layer), and its source is determined through recursive calculation. Among them, t is less than or equal to T.

[0047] By substituting each coefficient into the expression of the indirect impact index for calculation, the indirect impact index is obtained.

[0048] Step S500: Upload the chain impact index to the invasive species supervision platform, and clean the alien invasive species according to the cleaning equipment connected to the invasive species supervision platform.

[0049] In the embodiments of the present application, first, the chain impact index is uploaded to the invasive species supervision platform. The invasive species supervision platform determines the number of cleaning equipment required according to the value of the chain impact index according to a preset rule. Specifically, different sizes of chain impact indexes correspond to different numbers of cleaning equipment, and this rule is preset by technical experts. After determining the number of cleaning equipment, according to the geographical information of the target supervision area, such as the area, the cleaning equipment is evenly distributed to the target supervision area to automatically clean the alien invasive species.

[0050] Furthermore, the method provided by the embodiments of the application further includes:

[0051] Obtain the regional attributes of the target supervision area, mark the protected species of the target supervision area with the regional attributes; identify the protected species in the species label library and configure the weights of the protection importance to generate a species protection relationship matrix, and update the species dependence relationship network through the species protection relationship matrix.

[0052] In the embodiment of the present application, first, the regional attributes of a preset target supervision area are obtained. The regional attributes can be categories such as livestock areas, wildlife protection areas, water source protection areas, etc. Next, the regional attributes are used to mark the protected species in the target supervision area, that is, technical experts mark the animals and plants in the target supervision area according to the regional attributes to determine the protected species. For example, in a wildlife protection area, endangered wild animals are screened as the protected objects.

[0053] Subsequently, the protected species in the species tag library are identified and their protection importance weights are configured. This process includes obtaining a preset protection importance coefficient (for example, 1.5), which quantifies the priority and importance of the species in ecological protection. Next, the original relationship weights between the protected species and the dependent species are adjusted using the protection importance coefficient. In the species dependence relationship network, the weight configuration is completed by multiplying the protection importance coefficient by the original weight of the edge related to the protected species. For example, if the original weight is 0.4 and the coefficient is 1.5, the updated weight is 0.6. The updated weights are used to generate a species protection relationship matrix, where the rows and columns in the matrix represent the protected species and their dependent species respectively, and the values are the updated weights.

[0054] Finally, the species dependence relationship network is dynamically updated through the species protection relationship matrix. Specifically, the weights of the updated protected species and their dependent species are used to replace the original weights in the species dependence relationship network to form a new species dependence relationship network.

[0055] Furthermore, in the method provided by the application embodiment, for cleaning alien invasive species according to the cleaning equipment connected to the invasive species supervision platform, it further includes:

[0056] Establish a mapping relationship between the chain effect index samples and the cleaning equipment quantity samples, and evaluate the cleaning effect based on the mapping relationship to obtain the cleaning effect index samples corresponding to the chain effect index samples and the cleaning equipment quantity samples; the invasive species supervision platform performs mapping analysis on the chain effect index according to the preset cleaning effect index samples, outputs the corresponding cleaning equipment quantity, and controls the cleaning equipment quantity to clean the alien invasive species.

[0057] In the embodiment of the present application, first, the chain effect index samples and the cleaning equipment quantity samples are obtained from the historical database and the mapping relationship between the chain effect index samples and the cleaning equipment quantity samples is established. For example, when the chain effect index is 100, 1 device is used, and when the chain effect index is 200, 2 devices are used.

[0058] Next, based on the chain effect index samples and the number of cleaning equipment samples, the cleaning effect is evaluated to determine the cleaning effect index samples. The cleaning effect index samples are used to quantify the efficiency or effect of the cleaning task, such as the proportion of the chain effect index reduced. Specifically, in the evaluation process, by comparing the initial value of the chain effect index with the remaining value after cleaning and combining the number of equipment used, the cleaning efficiency is calculated. For example, when the chain effect index is 150 and 2 pieces of equipment are used, and the index is reduced to 50 after cleaning, the calculated cleaning efficiency is (150 - 50) / 150 = 67%. When the chain effect index is 200 and 3 pieces of equipment are used, and the index is reduced to 60 after cleaning, the cleaning efficiency is 70%. Through this process, the cleaning effect index samples corresponding to the chain effect index samples and the number of cleaning equipment samples are obtained.

[0059] Next, the invasive species supervision platform conducts a mapping analysis on the chain effect index according to the preset cleaning effect index samples. Specifically, the preset cleaning effect index samples are obtained, such as 70%, and the chain effect index at this time is obtained. These two data are compared with the mapping relationship established above to determine the number of cleaning equipment.

[0060] Finally, according to the determined number of cleaning equipment, these cleaning equipment are evenly distributed according to the size of the target supervision area to perform the cleaning of alien invasive species.

[0061] Furthermore, in the method provided by the application embodiment, after updating the species dependency network, it further includes:

[0062] Conduct a chain analysis on the invasive species information in combination with the species dependency network to obtain a chain effect path, upload the chain effect path to the invasive species supervision platform, and determine whether the chain effect path includes protected species. If it includes protected species, a protection cleaning task is additionally generated; while cleaning the alien invasive species through the cleaning equipment, the protected species are protected according to the protection cleaning task.

[0063] In the embodiment of the present application, first, a chain analysis is conducted on the invasive species information in combination with the species dependency network. Specifically, the chain analysis is carried out by using the maximum number of propagation layers of the alien invasive species on the species dependency network. The maximum number of propagation layers refers to the hierarchical depth of the impact of the invasive species on other species. For example, starting from the invasive species, it directly affects the species in the first layer, and indirectly affects the species in the second layer through the first layer, and so on until the preset maximum number of layers is reached. In the chain analysis, starting from the invasive species node, it propagates along the weight of each edge in the network in turn, and finally determines the chain effect path.

[0064] Next, upload the chain impact path to the invasive species supervision platform. The supervision platform uses the protected species database to analyze the chain impact path and determine whether protected species are involved in the path. If the path contains protected species, additional protection and cleaning tasks are generated, that is, an alarm message is sent to relevant staff. After the staff receives the alarm message, measures are taken to protect the protected species. For example, the actual threat situation is evaluated through on-site inspections, and temporary protection facilities are deployed.

[0065] Finally, while cleaning the alien invasive species through the cleaning equipment, protect the protected species according to the protection and cleaning tasks, that is, the staff conducts on-site protection of the protected species according to the actual situation.

[0066] In the embodiment of the present application, in summary, the embodiment of the present application has at least the following technical effects:

[0067] The present application establishes a species tag library for the target supervision area; identifies the dependency relationships of the species tag library and outputs a species dependency relationship network; when the invasive species supervision platform monitors an alien invasive species, obtains the invasive species information; downloads a trained chain impact analysis model in the invasive species supervision platform, and combines the species dependency relationship network to perform chain analysis on the invasive species information to obtain chain impact indicators, where the chain impact indicators include direct impact indicators and multiple indirect impact indicators. Among them, the direct impact indicator is the degree of impact on the reduction of the population in the species tag library directly caused by the invasive species information, and the indirect impact indicator is the degree of impact on the reduction of other populations caused by the directly reduced population; upload the chain impact indicators to the invasive species supervision platform, and clean the alien invasive species according to the cleaning equipment connected to the invasive species supervision platform. The present invention solves the technical problem of poor governance efficiency of invasive species in the prior art. By conducting ecological surveys and data mining to establish a species tag library, using dependency relationship analysis to generate a species dependency relationship network, combining a chain impact analysis model to quantitatively evaluate the multi-level impact of alien invasive species on the ecosystem, generating chain impact indicators, and optimizing the scheduling of cleaning equipment, the technical effect of efficiently governing invasive species is achieved.

[0068] Embodiment 2, based on the same inventive concept as the data-driven alien invasive species supervision method in the foregoing embodiment, as Figure 2 shown, the present application provides a data-driven alien invasive species supervision system. The system in the embodiment of the present application and the method embodiment are based on the same inventive concept. Among them, the system includes:

[0069] A tag library building module 11, which is used to build a species tag library for a target supervision area; a dependency relationship recognition module 12, which is used to recognize the dependency relationships in the species tag library and output a species dependency relationship network; an invasive species information acquisition module 13, which is used to obtain invasive species information when the invasive species supervision platform detects an alien invasive species; a chain analysis module 14, which is used to download a trained chain impact analysis model in the invasive species supervision platform, and perform chain analysis on the invasive species information in combination with the species dependency relationship network to obtain a chain impact index, where the chain impact index is calculated through a direct impact index and multiple indirect impact indices. Among them, the direct impact index is the degree of impact of the invasive species information directly causing a reduction in the population in the species tag library, and the indirect impact index is the degree of impact of the directly reduced population causing a reduction in other populations; a cleaning module 15, which is used to upload the chain impact index to the invasive species supervision platform and perform alien invasive species cleaning according to the cleaning device connected to the invasive species supervision platform.

[0070] Furthermore, the system is also used to implement the following functions:

[0071] The invasive species supervision platform accesses the ecological literature library through an API interface, extracts the dependency relationship tags between species from the ecological literature library, including predation relationship tags, competition relationship tags, and mutual benefit relationship tags; calculates the species dependency weights of the species tag library according to the dependency relationship tags, generates a species dependency relationship matrix, and constructs the species dependency relationship network by using the species dependency relationship matrix. The nodes of the species dependency relationship network represent species, and the edge weights represent the dependency intensity.

[0072] Furthermore, the system is also used to implement the following functions:

[0073]

[0074] Among them, i is the i-th species in the species tag library, I dierct (i) is the direct impact index of the alien invasive species on the i-th species, is the indirect impact index of the alien invasive species on the i-th species at the t-th layer. T is the maximum propagation layer of the alien invasive species affecting the species dependency relationship network, which is used to limit the depth of the chain impact analysis. α is the attenuation coefficient, and ΔEDI is the impact error based on the random perturbation of environmental factors.

[0075] Furthermore, the system is also used to implement the following functions:

[0076] I dierct (i) = Wpredation (i)·P inv +W competition (i)R inv ;

[0077] Among them, W predation is the predation weight of the alien invasive species on species i, P inv is the population quantity of the alien invasive species in the invasive species information, W competition is the resource occupancy ratio weight of the alien invasive species on species i, R inv is the resource occupancy ratio of the alien invasive species in the invasive species information.

[0078] Furthermore, the system is also used to implement the following functions:

[0079]

[0080] Among them, W interaction (i, k) is the interaction weight between species i and species k in the species dependence relationship network, i is the target species being analyzed for indirect influence, k is the species having a dependence relationship with species i, and t is the current level of indirect influence. is the indirect influence index of species k at the (t - 1)th level.

[0081] Furthermore, the system is also used to implement the following functions:

[0082] Obtain the regional attributes of the target supervision area, mark the protected species in the target supervision area with the regional attributes; identify the protected species in the species label library and configure the weights of protection importance to generate a species protection relationship matrix, and update the species dependence relationship network through the species protection relationship matrix.

[0083] Furthermore, the system is also used to implement the following functions:

[0084] Establish a mapping relationship between the chain - type influence index samples and the cleaning equipment quantity samples, evaluate the cleaning effect based on the mapping relationship to obtain the cleaning effect index samples corresponding to the chain - type influence index samples and the cleaning equipment quantity samples; the invasive species supervision platform performs mapping analysis on the chain - type influence index according to the preset cleaning effect index samples, outputs the corresponding cleaning equipment quantity, and controls the cleaning equipment quantity to clean the alien invasive species.

[0085] Furthermore, the system is also used to implement the following functions:

[0086] Chain-analyze the invasive species information in combination with the species dependence network to obtain a chain impact path, upload the chain impact path to the invasive species supervision platform, and determine whether the chain impact path includes protected species. If it includes protected species, additionally generate a protection and cleaning task; while cleaning the alien invasive species through the cleaning device, protect the protected species according to the protection and cleaning task.

[0087] It should be noted that the above order of the embodiments of the present application is only for description and does not represent the superiority or inferiority of the embodiments. And the above specific embodiments of the present specification have been described. The processes depicted in the drawings do not necessarily require the specific order and continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0088] The above are only the preferred embodiments of the present application and are not intended to limit the present application. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principles of the present application shall be included within the protection scope of the present application.

[0089] This specification and the drawings are only exemplary descriptions of the present application and are considered to cover any and all modifications, variations, combinations, or equivalents within the scope of the present application. Obviously, those skilled in the art can make various changes and modifications to the present application without departing from the scope of the present application. Thus, if these modifications and variations of the present application fall within the scope of the present application and its equivalent technologies, the present application is intended to include these changes and modifications.

Claims

1. A data-driven method for monitoring and managing alien invasive species, characterized in that, The method includes: Establishing a species tag library for the target supervision area; Identifying the dependency relationships in the species tag library and outputting a species dependency network; When the invasive species supervision platform detects an alien invasive species, obtaining the information of the invasive species; Downloading a trained chain impact analysis model in the invasive species supervision platform, and performing chain analysis on the invasive species information in combination with the species dependency network to obtain chain impact indicators. The chain impact indicators are calculated through direct impact indicators and multiple indirect impact indicators. Among them, the direct impact indicator is the degree of impact on the reduction of the population in the species tag library directly caused by the invasive species information, and the indirect impact indicator is the degree of impact on the reduction of other populations caused by the directly reduced population; Uploading the chain impact indicators to the invasive species supervision platform, and cleaning the alien invasive species according to the cleaning equipment connected to the invasive species supervision platform.

2. The method according to claim 1, wherein The method for outputting the species dependency network includes: The invasive species supervision platform accesses the ecological literature library through an API interface, and extracts the dependency relationship tags between species from the ecological literature library, including predation relationship tags, competition relationship tags, and mutual benefit relationship tags; Calculating the species dependency weights of the species tag library according to the dependency relationship tags to generate a species dependency relationship matrix, and constructing the species dependency network by using the species dependency relationship matrix. The nodes of the species dependency network represent species, and the edge weights represent the dependency intensity.

3. The method according to claim 1, wherein The expression for calculating the chain impact indicator EDI by the chain impact analysis model is: where i is the i-th species in the species label library, and I dierct (i) is the direct impact index of the alien invasive species on the i-th species, is the indirect impact index of the alien invasive species on the i-th species at the t-th layer. T is the maximum propagation layer of the alien invasive species affecting the species dependence network, which is used to limit the depth of the chain impact analysis. α is the attenuation coefficient, and ΔEDI is the impact error based on the random perturbation of environmental factors.

4. The method according to claim 3, wherein The expression for calculating the direct impact indicator is: I dierct (i) = W predation (i)·P inv +W competition (i)R inv ; Among them, W predation is the predation weight of the alien invasive species on species i, P inv is the population quantity of the alien invasive species in the invasive species information, W competition is the resource occupancy proportion weight of the alien invasive species on species i, R inv is the resource occupancy proportion of the alien invasive species in the invasive species information.

5. The method according to claim 3, characterized in that The expression for calculating the indirect impact indicator is: Among them, W interaction (i, k) is the interaction weight between species i and species k in the species dependence network, i is the target species whose indirect influence is being analyzed, k is the species that has a dependence relationship with species i, and t is the level of the current indirect influence. is the indirect influence index of species k at the (t - 1)-th layer.

6. The method according to claim 2, wherein The method includes: Obtaining the regional attributes of the target supervision area and marking the protected species in the target supervision area with the regional attributes; Identifying the protected species in the species tag library and configuring the weights of the protection importance, generating a species protection relationship matrix, and updating the species dependency network through the species protection relationship matrix.

7. The method according to claim 1, wherein Cleaning the alien invasive species according to the cleaning equipment connected to the invasive species supervision platform. The method includes: Establishing a mapping relationship between the chain impact indicator samples and the cleaning equipment quantity samples, and evaluating the cleaning effect according to the mapping relationship to obtain cleaning effect indicator samples corresponding to the chain impact indicator samples and the cleaning equipment quantity samples; The invasive species supervision platform performs mapping analysis on the chain impact indicators according to the preset cleaning effect indicator samples, outputs the corresponding cleaning equipment quantity, and controls the cleaning equipment quantity to clean the alien invasive species.

8. The method according to claim 7, wherein After updating the species dependency network, the method further includes: Performing chain analysis on the invasive species information in combination with the species dependency network to obtain a chain impact path, uploading the chain impact path to the invasive species supervision platform, and determining whether the chain impact path includes protected species. If it includes protected species, an additional protection cleaning task is generated; While cleaning the alien invasive species through the cleaning equipment, protecting the protected species according to the protection cleaning task.

9. A data-driven monitoring system for alien invasive species, characterized in that, The system includes: A tag library building module for building a species tag library for a target supervision area; A dependency relationship recognition module for recognizing the dependency relationships in the species tag library and outputting a species dependency relationship network; An invasive species information acquisition module for acquiring invasive species information when the invasive species supervision platform detects an alien invasive species; A chain analysis module for downloading a trained chain impact analysis model in the invasive species supervision platform, and performing chain analysis on the invasive species information in combination with the species dependency relationship network to obtain chain impact indicators, where the chain impact indicators are calculated through direct impact indicators and multiple indirect impact indicators. Among them, the direct impact indicator is the degree of impact of the invasive species information directly causing a reduction in the population in the species tag library, and the indirect impact indicator is the degree of impact of the directly reduced population causing a reduction in other populations; A cleaning module for uploading the chain impact indicators to the invasive species supervision platform and cleaning the alien invasive species according to the cleaning equipment connected to the invasive species supervision platform.

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