Multi-level index control method and system for entry and exit biological resources

Abstract

The application discloses a kind of multistage indexes of control method and system of entry and exit biological resources, and the application relates to the technical field of entry and exit biological resources, according to the level gradient relationship, the standard value of the biological resource security index of each level is determined according to the corresponding weight vector, the accuracy of the standard value of the biological resource security index of each level is guaranteed, and the ordered detection effect of the standard value of the biological resource security index of each level is improved.In the level gradient relationship, based on the level gradient relationship and the biological resource security index of each level, the corresponding first-level biological resource security index is determined;Mark the standard value of the first-level biological resource security index, determine the safety risk index of entry and exit biological resources according to the standard value of the first-level biological resource security index and the corresponding weight vector, guarantee the accurate evaluation of the safety risk index of entry and exit biological resources, so as to accurately control the safety risk of entry and exit biological resources.

Description

Technical Field

[0001] This invention relates to the technical field of imported and exported biological resources, and in particular to a method and system for controlling multi-level indicators of imported and exported biological resources. Background Technology

[0002] With the development of technology, the import and export of biological resources are generally controlled by customs authorities. Imported and exported biological resources refer to biological resources of special value or importance that need to cross national borders for introduction, export, or transshipment. These resources encompass microbial resources, laboratory animals, and biotechnology or biomanufactured products. Currently, the import and export of biological resources requires corresponding risk assessments. However, assessments based on single-dimensional safety indicators fail to consider the hierarchical relationships between different levels of biological resource safety indicators, affecting the accuracy of the standard values ​​for each level and hindering the precise assessment of the safety risk index of imported and exported biological resources. Summary of the Invention

[0003] The purpose of this invention is to overcome the shortcomings of the prior art. This invention provides a method and system for controlling multi-level indicators of biological resources entering and leaving the country.

[0004] This invention provides a method for controlling multi-level indicators of imported and exported biological resources, including: A database of imported and exported biological resources is collected, and a multi-level indicator set is determined based on the traversal of the database. In this multi-level indicator set, biological resource safety indicators at each level are marked, and the corresponding level gradient relationship is determined according to the ranking of biological resource safety indicators at each level. The standard values ​​of the biological resource safety indicators at each level are determined based on the gradient relationship at this level, the biological resource safety indicators at each level, and the corresponding weight vectors. In this level of gradient relationship, the corresponding primary biological resource security indicators are determined based on this level of gradient relationship and the biological resource security indicators at each level; The standard value of the primary biological resource safety indicator is marked, and the safety risk index of the imported and exported biological resources is determined based on the standard value of the primary biological resource safety indicator and the corresponding weight vector.

[0005] This invention provides a control system for multi-level indicators of imported and exported biological resources. The control system is applied to the aforementioned control method for multi-level indicators of imported and exported biological resources. The control system includes: The multi-level indicator set module is used to collect the database of imported and exported biological resources and determine the multi-level indicator set based on the traversal of the database of imported and exported biological resources. The level gradient relationship module is used to mark the biological resource safety indicators at each level in the multi-level indicator set, and determine the corresponding level gradient relationship according to the sorting of the biological resource safety indicators at each level. The standard value module is used to determine the standard values ​​of biological resource safety indicators at each level based on the gradient relationship at that level, the biological resource safety indicators at each level, and the corresponding weight vectors. The primary biological resource safety index module is used to determine the corresponding primary biological resource safety index based on the gradient relationship at this level and the biological resource safety indexes at each level. The safety risk index module is used to mark the standard value of the primary biological resource safety indicator and determine the safety risk index of imported and exported biological resources based on the standard value of the primary biological resource safety indicator and the corresponding weight vector.

[0006] Compared with the prior art, the beneficial effects of the present invention are: In this embodiment of the invention, a database of inbound and outbound biological resources is collected using the method described herein, and a multi-level indicator set is determined based on the traversal of the database. Within this multi-level indicator set, biological resource safety indicators at each level are marked, and a corresponding level gradient relationship is determined based on the ranking of the biological resource safety indicators at each level. The standard values ​​of the biological resource safety indicators at each level are determined based on this level gradient relationship, the biological resource safety indicators at each level, and the corresponding weight vectors. The introduction of this level gradient relationship ensures the accuracy of the standard values ​​of the biological resource safety indicators at each level, and improves the orderly detection effect of the standard values ​​of the biological resource safety indicators at each level.

[0007] Therefore, in this hierarchical gradient relationship, the corresponding primary biological resource safety indicators are determined based on this hierarchical gradient relationship and the biological resource safety indicators at each level; the standard value of the primary biological resource safety indicator is marked, and the safety risk index of imported and exported biological resources is determined according to the standard value of the primary biological resource safety indicator and the corresponding weight vector. The primary biological resource safety indicator is introduced, and the safety risk assessment of imported and exported biological resources is carried out based on the primary biological resource safety indicator. This realizes the overall consideration of the standard value of the primary biological resource safety indicator and the corresponding weight vector, ensuring the accurate assessment of the safety risk index of imported and exported biological resources, so as to facilitate the precise control of the safety risks of imported and exported biological resources. Attached Figure Description

[0008] Figure 1 This is a flowchart illustrating the method for controlling multi-level indicators of imported and exported biological resources in an embodiment of the present invention. Figure 2This is a schematic diagram of the structure of the control system for multi-level indicators of biological resources entering and leaving the country in an embodiment of the present invention; Figure 3 This is a schematic diagram of the hierarchical structure in the multi-level indicator control method for import and export biological resources in this embodiment of the invention; Figure 4 This is a schematic diagram of the structural composition of the multi-level index control method for import and export biological resources in this embodiment of the invention. Detailed Implementation

[0009] The technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention.

[0010] Please see Figures 1 to 4 A multi-level indicator control method for imported and exported biological resources includes: Step S11: Collect a database of imported and exported biological resources, and determine a multi-level indicator set based on the traversal of the database of imported and exported biological resources. Step S12: In this multi-level indicator set, mark the biological resource safety indicators at each level, and determine the corresponding level gradient relationship according to the ranking of the biological resource safety indicators at each level; Step S13: Determine the standard values ​​of the biological resource safety indicators at each level based on the gradient relationship at this level, the biological resource safety indicators at each level, and the corresponding weight vectors; Step S14: In this level gradient relationship, determine the corresponding primary biological resource security indicator based on this level gradient relationship and the biological resource security indicators at each level; Step S15: Mark the standard value of the primary biological resource safety indicator, and determine the safety risk index of inbound and outbound biological resources based on the standard value of the primary biological resource safety indicator and the corresponding weight vector; refer to Figure 2 In step S11, a database of imported and exported biological resources is collected, and a multi-level indicator set is determined based on the traversal of the database of imported and exported biological resources. In the specific implementation of this invention, the specific steps are as follows: S111: Collect images of imported and exported biological resources, determine the types of imported and exported biological resources based on the image recognition, mark the types of imported and exported biological resources, and match the types and types of imported and exported biological resources to the database of imported and exported biological resources. S112: In the database of imported and exported biological resources, the database of imported and exported biological resources is traversed, and multiple levels of indicators for exported biological resources are determined based on the traversal of the database of imported and exported biological resources. Based on the classification of the multiple levels of indicators for exported biological resources, a multi-level indicator set is determined.

[0011] In the embodiments of this application, professional image acquisition equipment, such as high-definition cameras or scanners, is used to photograph or scan biological resources entering and leaving the country; the shooting environment is ensured to have sufficient light and a simple background to reduce interference during image recognition; for live biological resources, special measures may be required, such as the use of anesthesia or fixation techniques, to ensure the safety and stability of the biological resources during the shooting process.

[0012] Image recognition technologies, such as deep learning algorithms or machine learning models, are used to analyze the collected images. These algorithms or models are usually extensively trained and can identify the characteristics of various biological resources, such as shape, color, and texture. By comparing the image features with features in a known biological resource database, the types of biological resources entering or leaving the country can be determined. At this point, for some biological resources, the type information may include the species name, genetic markers, ecotype, etc., which helps to more accurately identify and manage biological resources. The labeling process may require the assistance of expert knowledge or reference to relevant literature.

[0013] The identified biological resource types and models are matched with existing databases of inbound and outbound biological resources. These databases typically contain detailed information on various biological resources, such as ecological characteristics, genetic information, distribution range, potential hazards, and quarantine requirements. Once a match is successful, detailed information about the biological resource in the database can be obtained, providing a basis for subsequent safety risk assessment and management.

[0014] Furthermore, the database of imported and exported biological resources is traversed, and multiple levels of indicators for exported biological resources are determined based on the traversal of the database. A multi-level indicator set is determined based on the classification of the multiple levels of indicators for exported biological resources, which takes into account the overall consideration of the classification of multiple levels of indicators for exported biological resources and ensures the accuracy of the multi-level indicator set.

[0015] At this point, database query languages ​​(such as SQL) or database management tools are used to traverse the database of inbound and outbound biological resources. During the traversal, it is necessary to access various tables and fields in the database to ensure that all information related to biological resources is obtained. For each record, its data content and structure need to be carefully reviewed to ensure the accuracy and completeness of the data. At the same time, during the traversal of the database, multiple levels of safety indicators are identified and determined based on the characteristics of biological resources and management needs. These indicators may include primary indicators (such as the type, origin, and use of biological resources), secondary indicators (such as genetic characteristics, ecological adaptability, and reproductive capacity), and more detailed tertiary indicators (such as specific quarantine requirements, transportation conditions, and storage environment). The determination of indicators needs to refer to relevant laws, standards, and scientific research results to ensure their scientific validity and rationality.

[0016] The identified indicators at all levels are categorized and organized to form a multi-level indicator set. During the categorization process, the logical relationships and hierarchical structure between the indicators need to be considered to ensure the rationality and systematic nature of the multi-level indicator set. At the same time, each indicator needs to be clearly defined and explained to facilitate subsequent security risk assessment and management. In step S12, biological resource safety indicators at each level are marked in the multi-level indicator set, and the corresponding level gradient relationship is determined according to the sorting of biological resource safety indicators at each level. In the specific implementation of this invention, the specific steps are as follows: S121: Monitor the multi-level indicator set in real time, determine the biological resource safety indicators at each level based on the screening of the multi-level indicator set, and mark the biological resource safety indicators at each level. S122: The level hierarchy of biological resource safety indicators is determined based on the detection of biological resource safety indicators at various levels. The corresponding level gradient relationship is determined by comparing the level hierarchy of biological resource safety indicators. Biological resource safety indicators include primary indicators and secondary indicators. Primary indicators include bioinformation, inspection and approval, packaging characteristics, logistics links and emergency management. Secondary indicators are multiple sub-indicators corresponding to primary indicators. In the embodiments of this application, the multi-level indicator set is monitored in real time. Advanced monitoring technologies and systems are used to monitor the multi-level indicator set in real time. This includes periodically or in real time collecting, updating and analyzing data of each level of indicator. The monitoring system needs to have efficient data processing capabilities, be able to process large amounts of data in real time and quickly identify anomalies or potential risks. The monitoring scope should cover all key multi-level indicators, including but not limited to biometrics, inspection and approval, packaging characteristics, logistics links and emergency management.

[0017] A set of preset screening rules and thresholds are used to identify which multi-level indicators may constitute biological resource safety risks. When the monitoring system detects that the data of an indicator exceeds the preset threshold or does not comply with regulations, that indicator is considered a biological resource safety indicator. The screening process needs to be highly automated to reduce human intervention and errors, while ensuring the accuracy and timeliness of the screening results. At the same time, the screened biological resource safety indicators are marked for subsequent analysis, evaluation, and management. The marking information should include key information such as indicator name, level, current status, risk level, and discovery time. The marking process needs to be tightly integrated with the monitoring system to ensure the accuracy and real-time nature of the marking information. The marked safety indicators should be recorded in the system log or database for subsequent querying and analysis.

[0018] Furthermore, the levels of biosafety indicators are determined based on the detection of biosafety indicators at various levels. The corresponding level gradient relationship is determined by comparing the levels of biosafety indicators. Biosafety indicators include primary indicators and secondary indicators. Primary indicators include bioinformation, inspection and approval, packaging characteristics, logistics links, and emergency management. Secondary indicators are multiple sub-indicators corresponding to primary indicators. This comprehensive consideration of comparing the levels of biosafety indicators ensures the accuracy of the corresponding level gradient relationship.

[0019] At this point, biological resource safety indicators at all levels are tested and analyzed to determine their level hierarchy. The division of levels is usually based on factors such as the severity, scope of impact, and urgency of the indicators. Primary indicators usually cover broader and more fundamental aspects, such as bioinformatics and inspection and approval, which have a global impact on biological resource safety. Secondary indicators are further refinements and specifications of primary indicators, such as "species matching degree" under bioinformatics and "document integrity" under inspection and approval.

[0020] After determining the levels of indicators, we need to compare these levels to determine the hierarchical relationship between them. The hierarchical relationship reflects the logical relationship and mutual influence between indicators at different levels. Generally, higher-level indicators have a guiding and constraining effect on lower-level indicators, while lower-level indicators are the specific manifestation and refinement of higher-level indicators. By determining the hierarchical relationship, we can better understand and manage biological resource security indicators and ensure their coordination and consistency.

[0021] In step S13, the standard values ​​of the biological resource safety indicators at each level are determined based on the gradient relationship at this level, the biological resource safety indicators at each level, and the corresponding weight vectors. In the specific implementation of this invention, the specific steps are as follows: S131: Among multiple primary indicators, construct the corresponding primary indicator judgment matrix, convert the primary indicator judgment matrix into a corresponding table, normalize the primary indicator judgment matrix by column, add the normalized columns together and divide the sum vector by n to obtain the weight vector corresponding to the primary indicator. S132: Determine the first coefficient based on the gradient relationship at this level and the biological resource safety indicators at each level; determine the second coefficient based on the biological resource safety indicators at each level and the corresponding weight vector; and determine the standard value of the biological resource safety indicators at each level based on the first coefficient, the second coefficient, and the coefficient matching table.

[0022] In the embodiments of this application, among multiple primary indicators, a judgment matrix corresponding to the primary indicator is constructed, and the judgment matrix of the primary indicator is transformed into a corresponding table. The judgment matrix of the primary indicator is normalized column by column. The normalized columns are added together and the vector of the sum is divided by n to obtain the weight vector corresponding to the primary indicator. The weight vector corresponding to the primary indicator is introduced.

[0023] At this point, the judgment matrix is ​​used to reflect the relative importance among multiple primary indicators. Typically, domain experts judge the relative importance of each indicator based on experience and quantify it using a certain scale (such as the 1-9 scale). This results in a square matrix where each element represents the importance of the row indicator relative to the column indicator. Meanwhile, the judgment matrix is ​​presented in tabular form to facilitate subsequent data processing and analysis. At this point, the elements of the judgment matrix are directly filled into the table, with the rows and columns corresponding to the names of the primary indicators.

[0024] Normalization is performed to eliminate the influence of different scales on the results, ensuring that the sum of the elements in each column is 1. Each element in the judgment matrix is ​​divided by the sum of that column to obtain a new normalized matrix. At this point, the normalized element = original element / sum of its column. The cumulative importance of each primary indicator in all comparisons is obtained by summing these elements. Optionally, the elements of each row of the normalized matrix are summed to obtain a new vector, representing the weight of each primary indicator, ensuring that the sum of all weights is 1. Then, each element of the vector obtained in the previous step is divided by the number of primary indicators, n.

[0025] Furthermore, a first coefficient is determined based on the gradient relationship at this level and the biosafety indicators at each level. A second coefficient is determined based on the biosafety indicators at each level and their corresponding weight vectors. Standard values ​​for biosafety indicators at each level are determined based on the first coefficient, the second coefficient, and the coefficient matching table. This approach takes into account the overall considerations of the first coefficient, the second coefficient, and the coefficient matching table, ensuring the accuracy of the standard values ​​for biosafety indicators at each level. At the same time, the gradient relationship at this level is introduced, taking into account the overall considerations of the gradient relationship at this level, the biosafety indicators at each level, and their corresponding weight vectors, ensuring the accuracy of the standard values ​​for biosafety indicators at each level, and improving the orderly detection effect of the standard values ​​for biosafety indicators at each level.

[0026] At this point, the first coefficient reflects the importance or priority of biological resource security indicators at different levels. This is usually based on a predefined level gradient relationship, which may be a qualitative assessment framework used to describe the relative importance between indicators at different levels. For example, higher-level indicators may be considered more important than lower-level indicators. A coefficient is assigned to each level of indicator, which can be a numerical value (such as 1, 2, 3, etc., indicating increasing importance) or a level (such as high, medium, low).

[0027] The second coefficient reflects the contribution of each level of biological resource safety indicators in the actual assessment. It is a combination of the weight vector and the actual indicator performance (such as scores, ratings, etc.). At this time, the scores or ratings of each level of indicators are multiplied by the corresponding weights to obtain the weighted score or weighted rating. This weighted value is the second coefficient. For each indicator, the product of its score (or rating) and weight is calculated to obtain the weighted score (or weighted rating) of that indicator.

[0028] By combining the first and second coefficients, a coefficient matching table is used to determine the standard values ​​for each level of indicators. These standard values ​​can be used to measure the overall performance or risk level of biological resource safety indicators. Optionally, the coefficient matching table is a predefined table that maps standard values ​​based on the combination of the first and second coefficients. This table may be developed based on historical data, expert experience, or industry standards. The standard values ​​that match the combination of the first and second coefficients are found by searching the coefficient matching table.

[0029] Specifically, suppose we have the following biological resource safety indicators and their hierarchical relationships: High-level indicator: Bioinformation (A); Mid-level indicator: Inspection and approval (B), Packaging characteristics (C); Low-level indicator: Logistics links (D), Emergency management (E); and we have obtained the weight vectors of these indicators through a certain method (such as the analytic hierarchy process): A: 0.4; B: 0.25; C: 0.2; D: 0.1; E: 0.05; Now, suppose we obtain the following scores through actual evaluation: A: 90 points; B: 80 points; C: 75 points; D: 60 points; E: 50 points.

[0030] Suppose we assign a coefficient of 3 to high-level indicators, a coefficient of 2 to mid-level indicators, and a coefficient of 1 to low-level indicators; the second coefficient for A is 0.4. 90 = 36; the second coefficient of B = 0.25 80 = 20; the second coefficient of C = 0.2 75 = 15; the second coefficient of D = 0.1 60 = 6; the second coefficient of E = 0.05 50 = 2.5; Collect the corresponding standard value matching table, as shown in Table 1: Table 1 Standard Value Matching Table Based on this standard value matching table, we can find the standard values ​​that match the first and second coefficients of each indicator: A: First coefficient 3, second coefficient 36, corresponding standard value is "high"; B: First coefficient 2, second coefficient 20, corresponding standard value is "medium"; C: First coefficient 2, second coefficient 15, corresponding standard value is "medium"; D: First coefficient 1, second coefficient 6, since there is no directly corresponding range in the table, it can be judged as "low" based on the trend; E: First coefficient 1, second coefficient 2.5, also judged as "low".

[0031] In step S14, based on the gradient relationship at this level and the biological resource security indicators at each level, the corresponding primary biological resource security indicators are determined. In the specific implementation of this invention, the specific steps are as follows: S141: Monitor the gradient relationship at this level in real time, determine the matching path of biological resource safety indicators based on the gradient relationship at this level and the biological resource safety indicators at each level, and determine the first-level path based on the identification of the matching path of biological resource safety indicators. S142: Mark the nodes of each biological resource safety indicator based on the detection of the primary path, determine the corresponding primary biological resource safety indicator based on the detection of the nodes of each biological resource safety indicator, then trace the primary biological resource safety indicator and output the associated secondary biological resource safety indicator.

[0032] In the embodiments of this application, the gradient relationship at this level is monitored in real time, and the matching path of the biological resource safety indicators is determined based on the gradient relationship at this level and the biological resource safety indicators at each level. The first-level path is determined based on the identification of the matching path of the biological resource safety indicators, which is compatible with the overall consideration of the identification of the matching path of the biological resource safety indicators and ensures the accuracy of the first-level path.

[0033] At this point, real-time monitoring of the hierarchical relationship means continuously tracking and updating the relationships between the levels in the biological resource safety indicator system. This includes the definition of each level, the hierarchical relationship between levels, and the changes in indicators within each level. Monitoring methods can include periodic reviews, automatic updates of information systems, or expert consultations. A monitoring cycle should be set, such as a comprehensive review every quarter or year. Information technology, such as databases or cloud platforms, should be used to automate the updating and storage of the hierarchical relationship. A feedback mechanism should be established to allow relevant personnel to report changes or errors in the hierarchical relationship.

[0034] A matching path refers to the associated path of bioresource safety indicators from the highest level to the lowest level (or from a specific level to other levels). Determining the matching path requires analyzing the level gradient relationship to identify the logical connections and dependencies between indicators at each level. At this point, the level gradient relationship is graphically represented, such as using a tree diagram or network diagram, to more intuitively understand the relationship between each level and indicator. Starting from the highest level, the associated paths of indicators are analyzed level by level until the required lowest level or specific indicator is reached. Each matching path is recorded, including the starting level, the ending level, and all indicators and levels traversed along the path.

[0035] The primary pathway refers to the highest-level pathway in the biological resource safety indicator system, representing the framework and core of the entire indicator system. Determining the primary pathway requires screening the highest-level pathway from all matching pathways, which is usually the top-level and directly related indicators. At the same time, the levels of all matching pathways are compared to identify the highest-level pathway. The indicators on the primary pathway are then confirmed, which are usually the most important and globally influential indicators in the entire indicator system. The primary pathway is then verified and confirmed to ensure its accuracy and rationality.

[0036] Furthermore, nodes of each biological resource safety indicator are marked based on the detection of the primary path, and the corresponding primary biological resource safety indicators are determined based on the detection of the nodes of each biological resource safety indicator. At this point, the primary biological resource safety indicators are traced back, and the associated secondary biological resource safety indicators are output. This takes into account the overall consideration of the detection of the nodes of each biological resource safety indicator, and ensures the accuracy of the corresponding primary biological resource safety indicators.

[0037] At this point, based on the established primary pathway, each biological resource safety indicator is marked as a node. A node can be understood as the position or identifier of an indicator within the indicator system, helping us to better understand and organize the relationships between indicators. The process of marking nodes typically involves classifying, encoding, or assigning specific identifiers to indicators. Then, each indicator on the primary pathway is analyzed one by one to determine its specific position within the indicator system. Based on the analysis results, a unique node identifier is assigned to each indicator; this identifier can be numbers, letters, or a combination thereof. The node identifier is stored along with the indicator information in a database or information system for subsequent querying and use.

[0038] Having marked all nodes, we need to further determine which indicators belong to the primary biological resource safety indicators. Primary indicators are usually the most important and globally influential indicators in the indicator system, and they are located at the highest level of the indicator system. At the same time, we need to review all indicators on the primary path and classify them according to their level and importance. We need to identify those indicators that are located at the highest level and have a significant impact on the entire indicator system, and determine them as primary biological resource safety indicators. We need to record the information of the primary indicators, including their names, node identifiers, and their positions in the indicator system.

[0039] Tracing primary biosecurity indicators means gaining a deep understanding of their historical data, trends, influencing factors, and relationships with other indicators. The tracing process helps us better understand the current status and potential problems of these indicators, providing a scientific basis for developing management strategies. At the same time, it involves collecting historical data on primary indicators, including monitoring results and assessment reports from previous years, and analyzing the trends of these indicators to identify possible fluctuations or anomalies. Explore the factors that influence changes in primary indicators, including changes in the natural environment, human activities, and policy adjustments; analyze the relationship between primary indicators and other indicators to understand their interactions and impacts.

[0040] After tracing the primary biological resource safety indicators, we need to identify the secondary biological resource safety indicators directly related to these primary indicators. Secondary indicators are usually concretizations or refinements of primary indicators, providing more detailed information to support the understanding and management of primary indicators. At this point, based on the hierarchical relationship and the correlation between indicators, we start from the primary indicators and identify their directly subordinate secondary indicators. We record the information of the secondary indicators, including their names, node identifiers, and their correlation with the primary indicators. We then output the primary indicators and their associated secondary indicators together to form a complete indicator system structure diagram or report. In step S15, the standard value of the primary biological resource safety indicator is marked, and the safety risk index of the imported and exported biological resources is determined based on the standard value of the primary biological resource safety indicator and the corresponding weight vector. In the specific implementation of this invention, the specific steps are as follows: S151: Collect primary biological resource safety indicators, determine the standard value of the primary biological resource safety indicator based on the matching of the primary biological resource safety indicator and the database of imported and exported biological resources, and collect the corresponding weight vector based on the tracing of the standard value of the primary biological resource safety indicator. S152: Match the corresponding safety risk assessment model according to the standard value and corresponding weight vector of the first-level biological resource safety indicator, and output the safety risk index of imported and exported biological resources based on the safety risk assessment model; The calculation formula for the safety risk assessment model is as follows: This represents the weight coefficient corresponding to the evaluation index. ); This represents the standard value of the sub-indicator corresponding to the i-th indicator.

[0041] In the embodiments of this application, primary biological resource safety indicators are collected, and the standard value of the primary biological resource safety indicators is determined based on the matching of the primary biological resource safety indicators with the database of imported and exported biological resources. The corresponding weight vector is collected based on the tracing of the standard value of the primary biological resource safety indicators, which takes into account the overall consideration of matching the primary biological resource safety indicators with the database of imported and exported biological resources, and ensures the accuracy of the standard value of the primary biological resource safety indicators.

[0042] At this point, identify and collect the highest-level primary indicators from the biological resource safety indicator system. These indicators are usually key parameters for measuring the safety status of biological resources and can comprehensively reflect the health status, ecosystem service functions, and biodiversity levels of biological resources. Consult relevant documents or materials on the biological resource safety indicator system to clarify the definition and scope of the primary indicators. Based on the structure of the indicator system, screen from high to low levels to ensure that the collected indicators are primary indicators. Record the name, definition, and other key information of each primary indicator.

[0043] After collecting primary indicators, they need to be matched with the database of imported and exported biological resources to determine the standard values ​​or thresholds for these indicators. Standard values ​​are usually determined based on historical data, international standards, etc., and represent the performance level of the indicator under ideal or safe conditions. At this time, the database of imported and exported biological resources is accessed to obtain historical data or monitoring results related to the primary indicators. The historical data is analyzed to determine the standard value or safety threshold for each primary indicator. This may require consideration of factors such as data volatility and trends. If there is no directly relevant historical data in the database, international standards, policy regulations, or experts can be consulted to determine reasonable standard values.

[0044] After determining the standard values ​​of the primary indicators, it is necessary to trace and determine the importance of each indicator in the overall safety risk assessment, i.e., to collect the corresponding weight vector. The weight vector reflects the degree of contribution of different indicators to the safety risk assessment results and is a key parameter in the safety risk assessment model. At the same time, based on the definition and scope of the primary indicators, the correlation, mutual influence and their respective importance to biological resource safety are analyzed. A weight value is assigned to each primary indicator using methods such as expert scoring, analytic hierarchy process (AHP), and entropy weighting. The weight values ​​are recorded to form a weight vector, and the sum of the weight values ​​is ensured to be 1 (or 100%, depending on the specific situation).

[0045] Furthermore, based on the standard value and corresponding weight vector of the primary biological resource safety indicator, a corresponding safety risk assessment model is matched, and the safety risk index of imported and exported biological resources is output based on the safety risk assessment model. The safety risk index of imported and exported biological resources output by the safety risk assessment model is introduced. At the same time, the primary biological resource safety indicator is introduced, and the safety risk assessment of imported and exported biological resources is carried out based on the primary biological resource safety indicator. This realizes the overall consideration of the standard value and corresponding weight vector of the primary biological resource safety indicator, ensuring the accurate assessment of the safety risk index of imported and exported biological resources, so as to facilitate the precise control of the safety risks of imported and exported biological resources.

[0046] At this point, based on the established standard values ​​and corresponding weight vectors of the primary biological resource safety indicators, a suitable safety risk assessment model is selected. The safety risk assessment model is typically an algorithm or system that compares the actual values ​​of the primary indicators with the standard values ​​and calculates the overall safety risk index using the weight vectors. Then, the nature and characteristics of the primary indicators are analyzed, and a suitable safety risk assessment model is selected. For example, if the indicator is a continuous variable, a weighted summation model can be chosen; if the indicator is a categorical variable, a logistic regression model can be chosen. It is crucial to ensure that the selected model fully considers the influence of the weight vectors, i.e., the different contributions of different indicators to safety risk. If multiple candidate models exist, the optimal model can be selected by comparing their accuracy, stability, and operability.

[0047] After selecting a suitable safety risk assessment model, we need to compare the actual values ​​of the primary indicators with the standard values, calculate the degree of deviation (or compliance) of each indicator, and then combine the weight vector to calculate the overall safety risk index using the safety risk assessment model. The safety risk index is a quantitative value used to represent the level of safety risk faced by imported and exported biological resources. At this point, we collect the actual value data of the primary indicators to ensure the accuracy and completeness of the data. According to the requirements of the safety risk assessment model, we preprocess the actual value data, such as standardization and normalization. We compare the preprocessed actual value data with the standard values ​​to calculate the degree of deviation (or compliance). We multiply the degree of deviation (or compliance) by the weight vector to obtain the weighted deviation (or weighted compliance) of each indicator. We sum the weighted deviations (or weighted compliance) of all indicators (or combine them in other ways) to obtain the overall safety risk index. Based on the magnitude of the safety risk index, we determine the level of safety risk faced by imported and exported biological resources and take corresponding management measures.

[0048] The calculation formula for the safety risk assessment model is as follows: This represents the weight coefficient corresponding to the evaluation index. ); This represents the standard value of the sub-indicator corresponding to the i-th indicator.

[0049] In another embodiment of this application, the analytic hierarchy process (AHP) is used to calculate the weights of the indicators in the safety risk assessment system for imported and exported biological resources. In this case, when constructing the hierarchical structure, the research questions need to be hierarchically processed to form a hierarchical and ordered model. Generally, the hierarchy can be divided into three layers: the highest layer (purpose layer), the middle layer (criteria layer), and the lowest layer (scheme layer). Based on the already constructed indicator system of the safety risk assessment model for imported and exported biological resources, it is made systematic and hierarchical, thereby completing the construction of the hierarchical structure.

[0050] The selected safety indicators for import and export biological resources include five primary indicators: bioinformation, inspection and approval, packaging characteristics, logistics links, and emergency management, as well as several secondary specific indicators, which constitute the original indicator system of the import and export biological resources safety index evaluation model, as shown in Tables 2, 3, 4, 5, and 6. Table 2. Original Indicator System for the Import and Export Biological Resource Safety Index Evaluation Model (Bioinformatics) Table 3. Original Indicator System for the Import and Export Biological Resource Safety Index Evaluation Model (Inspection and Approval) Table 4. Original Indicator System for the Import and Export Biological Resource Safety Index Evaluation Model (Packaging Characteristics) Table 5. Original Indicator System for the Import and Export Biological Resource Safety Index Evaluation Model (Logistics Link) Table 6. Original Indicator System for the Import and Export Biological Resource Safety Index Evaluation Model (Emergency Management) In the steps of calculating weights using the Analytic Hierarchy Process (AHP), constructing and assigning values ​​to the judgment matrix is ​​the most crucial step. Current research often employs the three-scale and nine-scale methods to construct these matrices. However, in practice, both methods have limitations, potentially leading to biased evaluation results. Because the judgment boundaries are relatively simple, the three-scale method can result in low discriminative power among the indicators. Conversely, the nine-scale method, with its relatively ambiguous judgment boundaries, struggles to rigorously differentiate the importance of each indicator. Therefore, this paper proposes an improved five-scale method. This method overcomes the shortcomings of both the three-scale and nine-scale methods, and is simpler in form, more logically sound, and better aligned with human subjective thinking.

[0051] Table 7: Meaning of Importance Scale The indicators in the criterion layer have different weights in the target layer, and their perceived importance also varies. Therefore, this paper adopts a five-scale method, using numbers 1-9 and their reciprocals as scales to assign values ​​to the differences in importance between pairs of indicators, thus constructing the judgment matrix. The importance scale values ​​and their specific meanings are shown in Table 6 above.

[0052] When constructing the judgment matrix for the primary indicators, the five primary indicators are first denoted as A1 (bioinformatics), A2 (emergency management), A3 (logistics links), A4 (packaging characteristics), and A5 (inspection and approval). Furthermore, to ensure the authenticity and effectiveness of the constructed judgment matrix, this paper invited several customs experts and experts in the fields of safety evaluation to construct judgment matrices and provide value assignment suggestions. Finally, through comprehensive analysis of the construction results and value assignment suggestions given by the experts, the judgment matrix A is obtained as shown in formula (1): (1) Convert the matrix into a table, as shown in Table 8 below: The judgment matrix A constructed in Table 8 Furthermore, the methods for calculating the weight vector using the analytic hierarchy process (AHP) include the following four: geometric mean, eigenvector method, arithmetic mean, and least squares method. This paper uses the arithmetic mean method (summation method) to calculate the weight vector. Since each column in the judgment matrix A approximately reflects the distribution of weights, the weight vector can be determined by calculating the arithmetic mean of all column vectors. The calculation method is shown in formula (2): (2) The specific steps for calculating the weight vector using the arithmetic mean method (summation method) are as follows: normalize the judgment matrix A column by column, add the normalized columns together, and divide the summed vector by n to obtain the weight vector.

[0053] After constructing the judgment matrix, it is necessary to normalize the judgment matrix A column by column according to formula (3). After normalizing the judgment matrix A, a new normalized judgment matrix will be obtained. The new normalized judgment matrix is ​​named matrix B. The sum of the data in each column of the normalized matrix is ​​1. The specific results are shown in Table 9: (3) Table 9 shows the normalized matrix B. The weight vector is calculated by normalizing the judgment matrix A to obtain matrix B. Then, the columns of matrix B need to be summed to obtain the eigenvector. The specific calculation results are shown in Table 10. After obtaining the eigenvector, it is necessary to normalize the obtained eigenvector using formula (4). The result after normalization is the weight vector W. The final weight vector can be used as the weight value of the five primary indicators. W% is the weight percentage of the five primary indicators. The final indicator weights are shown in Table 11. (4) Table 10: Feature Vector Table Table 11 Weight Vector Table After calculating the weights W of the five primary indicators, it is necessary to determine that the calculated weights are not necessarily effective or desirable. Therefore, a consistency ratio needs to be calculated to verify the consistency of the judgment matrix, thereby ensuring that the obtained indicator weights are acceptable. The specific calculation steps are as follows: When calculating the largest eigenvalue of the judgment matrix A, the first step is to calculate the eigenvalues ​​of each indicator according to formula (5). The specific calculation results are shown in Table 12 below.

[0054] (5) Table XII. Characteristic Root Table The largest eigenvalue of matrix A Take the average of the five characteristic roots corresponding to A1, A2, A3, A4, and A5 respectively, that is... Calculate the consistency index. Calculate the consistency index according to formula (6): (6) Where n represents the order of the matrix, i.e., CI = (5.25949829 - 5) / (5 - 1) = 0.051899658 Find the average random consistency index RI, see Table XIII for details. Table 13. Average Random Consistency Index The number of primary indicators is 5, so n=5. Therefore, the average random consistency indicator RI is selected as 1.12.

[0055] After obtaining the consistency index and the average random consistency index, the consistency ratio needs to be calculated according to the formula (7), that is, CR=0.051899658 / 1.12=0.0463389804<0.1.

[0056] When CR < 0.1, the consistency of the judgment matrix is ​​generally considered acceptable; otherwise, the judgment matrix should be appropriately modified. Once the judgment matrix passes the consistency test, the calculated result can be used as the weight of the index element.

[0057] The consistency ratio CR calculated in this paper is 0.0463389804 < 0.1, indicating that the calculation results passed the consistency test and the calculated weights are acceptable. Therefore, the weights of the five primary indicators can be determined to be 15.5499%, 6.7296%, 38.0783%, 27.5118%, and 12.1305%, respectively. The weights of the 57 secondary indicators are calculated in the same way. The final indicator weights obtained by the analytic hierarchy process are shown in Table 14.

[0058] Table 14. Weights of Indicators Determined by the Analytic Hierarchy Process By analogy, the weights of the secondary indicators in the risk indicator system for the safety of imported and exported biological resources can be obtained, as shown in Tables 1-5. Given the relatively small differences in the standardized evaluation values ​​of the risk assessment indicators for the safety of imported and exported biological resources, but the significant differences in the importance of each indicator, the weighted linear sum method is preferred for indicator synthesis. Therefore, the weights of each indicator obtained in the above research are integrated with the standardized data. Following the principles of scientific rigor and feasibility, and considering the independence of evaluation indicators at each level, as well as the project's focus on differences in indicator importance, the weighted linear sum method is used for calculating the secondary indicators, primary indicators, and the risk assessment model for the safety of imported and exported biological resources.

[0059] The import and export biological resource safety risk index is defined as a linear weighted sum of five primary indicators and five primary sub-indicators, namely, biological information, inspection and approval, packaging characteristics, logistics links, and emergency management, as shown in formula (9). The calculation formula for the safety risk assessment model is as follows: (9) This represents the weight coefficient corresponding to the evaluation index. ); This represents the standard value of the sub-indicator corresponding to the i-th indicator.

[0060] Similarly, the standard values ​​of each primary sub-indicator are... Each is formed by weighted linear summation of its corresponding secondary indicators.

[0061] Please see Figure 2 , Figure 2 This is a schematic diagram illustrating the structural composition of the multi-level indicator control system for importing and exporting biological resources in an embodiment of the present invention; the multi-level indicator control system for importing and exporting biological resources includes: The multi-level indicator set module 21 is used to collect the database of imported and exported biological resources and determine the multi-level indicator set based on the traversal of the database of imported and exported biological resources. The level gradient relationship module 22 is used to mark the biological resource safety indicators at each level in the multi-level indicator set, and determine the corresponding level gradient relationship according to the sorting of the biological resource safety indicators at each level. The standard value module 23 is used to determine the standard values ​​of the biological resource safety indicators at each level based on the gradient relationship of the level, the biological resource safety indicators at each level, and the corresponding weight vectors. The primary biological resource safety index module 24 is used to determine the corresponding primary biological resource safety index based on the gradient relationship at this level and the biological resource safety indexes at each level. The safety risk index module 25 is used to mark the standard value of the primary biological resource safety indicator and determine the safety risk index of imported and exported biological resources based on the standard value of the primary biological resource safety indicator and the corresponding weight vector.

[0062] The technical features of the above embodiments can be combined arbitrarily. For the sake of brevity, not all combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

Claims

1. A method for controlling multi-level indicators of imported and exported biological resources, characterized in that, include: A database of imported and exported biological resources is collected, and a multi-level indicator set is determined based on the traversal of the database. In this multi-level indicator set, biological resource safety indicators at each level are marked, and the corresponding level gradient relationship is determined according to the ranking of biological resource safety indicators at each level. The standard values ​​of the biological resource safety indicators at each level are determined based on the gradient relationship at this level, the biological resource safety indicators at each level, and the corresponding weight vectors. In this level of gradient relationship, the corresponding primary biological resource security indicators are determined based on this level of gradient relationship and the biological resource security indicators at each level; The standard value of the primary biological resource safety indicator is marked, and the safety risk index of the imported and exported biological resources is determined based on the standard value of the primary biological resource safety indicator and the corresponding weight vector.

2. The method for controlling multi-level indicators of imported and exported biological resources according to claim 1, characterized in that, The database of imported and exported biological resources is collected, and a multi-level indicator set is determined based on the traversal of the database, including: Images of imported and exported biological resources are collected, the types of imported and exported biological resources are determined based on the image recognition, and the types of imported and exported biological resources are marked. The types and types of imported and exported biological resources are then matched with the database of imported and exported biological resources. In the database of imported and exported biological resources, the database is traversed, and multiple levels of indicators for exported biological resources are determined based on the traversal of the database. A multi-level indicator set is determined based on the classification of the multiple levels of indicators for exported biological resources.

3. The method for controlling multi-level indicators of imported and exported biological resources according to claim 1, characterized in that, In this multi-level indicator set, biosecurity indicators at each level are marked, and the corresponding level gradient relationship is determined according to the ranking of biosecurity indicators at each level, including: The multi-level indicator set is monitored in real time, and biological resource safety indicators at each level are determined based on the screening of the multi-level indicator set, and biological resource safety indicators at each level are marked. The levels of biological resource safety indicators are determined based on the detection of biological resource safety indicators at various levels. The corresponding level gradient relationship is determined by comparing the levels of biological resource safety indicators. Biological resource safety indicators include primary indicators and secondary indicators. Primary indicators include biological information, inspection and approval, packaging characteristics, logistics links and emergency management. Secondary indicators are multiple sub-indicators corresponding to primary indicators.

4. The method for controlling multi-level indicators of imported and exported biological resources according to claim 4, characterized in that, The process of determining the standard values ​​of biological resource safety indicators at each level based on the gradient relationship, the biological resource safety indicators at each level, and the corresponding weight vectors includes: Among multiple primary indicators, a judgment matrix for each primary indicator is constructed, and the judgment matrix is ​​transformed into a corresponding table. The judgment matrix of the primary indicator is then normalized column by column. The normalized columns are summed, and the summed vector is divided by n to obtain the weight vector corresponding to the primary indicator.

5. The method for controlling multi-level indicators of imported and exported biological resources according to claim 4, characterized in that, Based on the gradient relationship at this level, the bioresource security indicators at each level, and the corresponding weight vectors, the standard values ​​of the bioresource security indicators at each level are determined, which also includes: The first coefficient is determined based on the gradient relationship at this level and the biological resource safety indicators at each level. The second coefficient is determined based on the biological resource safety indicators at each level and the corresponding weight vector. The standard values ​​of the biological resource safety indicators at each level are determined based on the first coefficient, the second coefficient, and the coefficient matching table.

6. The method for controlling multi-level indicators of imported and exported biological resources according to claim 1, characterized in that, In this level of gradient relationship, the corresponding primary biological resource safety indicators are determined based on this level of gradient relationship and the biological resource safety indicators at each level, including: The gradient relationship at this level is monitored in real time. Based on the gradient relationship at this level and the biological resource safety indicators at each level, the matching path of the biological resource safety indicators is determined. The first-level path is determined based on the identification of the matching path of the biological resource safety indicators.

7. The method for controlling multi-level indicators of imported and exported biological resources according to claim 6, characterized in that, The method of determining the corresponding primary biological resource safety indicators based on the gradient relationship and the biological resource safety indicators at each level within this gradient relationship also includes: The nodes of each biological resource safety indicator are marked based on the detection of the primary path. The corresponding primary biological resource safety indicators are determined based on the detection of the nodes of each biological resource safety indicator. At this time, the primary biological resource safety indicators are traced back and the associated secondary biological resource safety indicators are output.

8. The method for controlling multi-level indicators of imported and exported biological resources according to claim 1, characterized in that, The standard value for marking the primary biological resource safety indicator, and the determination of the safety risk index for imported and exported biological resources based on the standard value of the primary biological resource safety indicator and the corresponding weight vector, including: Collect primary biological resource safety indicators, determine the standard value of the primary biological resource safety indicator based on the matching of the primary biological resource safety indicator and the database of imported and exported biological resources, and collect the corresponding weight vector based on the traceability of the standard value of the primary biological resource safety indicator. Based on the standard value and corresponding weight vector of the primary biological resource safety indicator, a corresponding safety risk assessment model is matched, and the safety risk index of imported and exported biological resources is output based on the safety risk assessment model.

9. The method for controlling multi-level indicators of imported and exported biological resources according to claim 8, characterized in that, The standard value for marking the primary biological resource safety indicator, and the determination of the safety risk index for imported and exported biological resources based on the standard value of the primary biological resource safety indicator and the corresponding weight vector, further include: The calculation formula for the safety risk assessment model is as follows: This represents the weight coefficient corresponding to the evaluation index. ); This represents the standard value of the sub-indicator corresponding to the i-th indicator.

10. A control system for multi-level indicators of imported and exported biological resources, characterized in that, The control system for the multi-level indicators of imported and exported biological resources is applied to the control method for the multi-level indicators of imported and exported biological resources as described in any one of claims 1-9, wherein the control system for the multi-level indicators of imported and exported biological resources includes: The multi-level indicator set module is used to collect the database of imported and exported biological resources and determine the multi-level indicator set based on the traversal of the database of imported and exported biological resources. The level gradient relationship module is used to mark the biological resource safety indicators at each level in the multi-level indicator set, and determine the corresponding level gradient relationship according to the sorting of the biological resource safety indicators at each level. The standard value module is used to determine the standard values ​​of biological resource safety indicators at each level based on the gradient relationship at that level, the biological resource safety indicators at each level, and the corresponding weight vectors. The primary biological resource safety index module is used to determine the corresponding primary biological resource safety index based on the gradient relationship at this level and the biological resource safety indexes at each level. The safety risk index module is used to mark the standard value of the primary biological resource safety indicator and determine the safety risk index of imported and exported biological resources based on the standard value of the primary biological resource safety indicator and the corresponding weight vector.

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