Method and apparatus for obtaining a universal chemical combination for mixture toxicity assessment

Abstract

The present invention provides a method and device for obtaining a general chemical combination for mixture toxicity assessment, including: counting the total number of chemicals in a target environment, and constructing a compound detection matrix of the target environment according to the chemical concentrations detected at sampling and detection points and the total number of the chemicals; constructing a mapping relationship between chemicals and analytical detection limits, and converting the compound detection matrix into a compound presence / absence matrix based on the target chemical concentration and the analytical detection limit mapped to the target chemical; constructing a first frequent item set of chemicals based on the occurrence frequency of candidate chemicals in the compound presence / absence matrix and a first threshold of the frequency; optimizing the first frequent item set of chemicals from lower-order to higher-order chemical combinations based on an item set optimization strategy, and sequentially obtaining higher-order frequent item sets; and obtaining a general chemical combination based on the first frequent item set of chemicals and the sequentially obtained higher-order frequent item sets. The accuracy of environmental mixture toxicity assessment and risk evaluation can be improved.

Description

Technical Field

[0001] The present invention relates to the technical field of environmental monitoring, and in particular, to a method and device for obtaining a general chemical combination for mixture toxicity assessment. Background Art

[0002] The mixed exposure of pollutants (chemicals) in the actual environment is a common rule. It is necessary to conduct toxicity studies on the mixed exposure of pollutants (chemical combinations) based on the pollutants detected in the actual environment to evaluate the combined risk. Currently, the research on the mixed exposure toxicity of pollutants mainly focuses on the toxicity studies of binary mixtures (binary chemical combinations) composed of two pollutants or ternary mixtures (ternary chemical combinations) composed of three pollutants. However, due to the fact that the types and exposure scenarios of pollutants (chemicals) in the actual environment are often more complex, relying solely on the toxicity research results of binary mixtures or ternary mixtures to comprehensively evaluate the mixed exposure toxicity of chemicals in the environment will deviate significantly from the actual situation, resulting in a low accuracy of the mixture toxicity assessment for the target environment. For example, the number of possible co-exposure mixture combinations composed of only 20 chemicals theoretically exceeds one million (2 20 -1 = 1048575), and for each additional chemical, the number of mixture combinations doubles. Although the exposure of chemicals in the actual environment, especially the mixed exposure of chemicals, is not completely random and undergoes various construction processes, the actual number of mixed exposures of n chemicals experienced in the real environment will be much less than 2 n -1. However, there is a large gap between the chemical mixed exposure based on binary chemical combinations or ternary chemical combinations and the mixed exposure of combinations between various chemicals in the actual environment. Therefore, how to screen and identify the chemical combinations existing in the actual environment from a large number of possible chemical mixed exposures to reduce the number of chemical combinations for environmental mixture toxicity assessment and improve the efficiency and accuracy of environmental mixture toxicity assessment is a problem that must be solved in the research on environmental toxicity risk assessment. Summary of the Invention

[0003] In view of this, the purpose of the present invention is to provide a method and device for obtaining a general chemical combination for toxicity assessment to improve the accuracy of environmental mixture toxicity assessment.

[0004] In a first aspect, an embodiment of the present invention provides a method for obtaining a general chemical combination for toxicity assessment, including:

[0005] Statistically count the total number of chemicals detected at each sampling and detection point in the target environment. For each sampling and detection point, construct a chemical detection matrix for this sampling and detection point based on the chemical concentration detected at this sampling and detection point and the total number of the chemicals, and construct a compound detection matrix for the target environment based on the chemical detection matrices of each sampling and detection point;

[0006] Query the pre-set mapping relationship between chemicals and analytical detection limits, and based on the target chemical concentration in the compound detection matrix and the analytical detection limit mapped to this target chemical, convert the compound detection matrix into a compound presence / absence matrix;

[0007] For each candidate chemical in the compound presence / absence matrix, construct a first frequent item set of chemicals based on the occurrence frequency of this candidate chemical in the compound presence / absence matrix and the pre-set first threshold of frequency;

[0008] Based on the pre-set item set optimization strategy, optimize the first frequent item set of chemicals from low-order chemical combinations to high-order chemical combinations, and sequentially obtain high-order frequent item sets;

[0009] Based on the first frequent item set of chemicals and the sequentially obtained high-order frequent item sets, obtain a general chemical combination for mixture toxicity assessment.

[0010] In a second aspect, an embodiment of the present invention provides a device for obtaining a general chemical combination for mixture toxicity assessment, including:

[0011] A concentration matrix construction module, configured to statistically count the total number of chemicals detected at each sampling and detection point in the target environment. For each sampling and detection point, construct a chemical detection matrix for this sampling and detection point based on the chemical concentration detected at this sampling and detection point and the total number of the chemicals, and construct a compound detection matrix for the target environment based on the chemical detection matrices of each sampling and detection point;

[0012] A presence / absence matrix conversion module, configured to query the pre-set mapping relationship between chemicals and analytical detection limits, and based on the target chemical concentration in the compound detection matrix and the analytical detection limit mapped to this target chemical, convert the compound detection matrix into a compound presence / absence matrix;

[0013] A low-order frequent item set construction module, configured to for each candidate chemical in the compound presence / absence matrix, construct a first frequent item set of chemicals based on the occurrence frequency of this candidate chemical in the compound presence / absence matrix and the pre-set first threshold of frequency;

[0014] A high-order frequent itemset construction module, configured to optimize the first frequent itemset of the chemical substances from low-order chemical combinations to high-order chemical combinations based on a preset itemset optimization strategy, and sequentially obtain high-order frequent item sets;

[0015] A chemical combination acquisition module, configured to obtain general chemical combinations for mixture toxicity assessment based on the first frequent itemset of the chemical substances and the sequentially obtained high-order frequent item sets.

[0016] According to a third aspect of the present invention, there is provided a storage medium, on which a computer program is stored, and when the program is executed by a processor, the steps of the method for obtaining general chemical combinations for mixture toxicity assessment in any possible implementation manner of the first aspect are implemented.

[0017] According to a fourth aspect of the present invention, there is provided an electronic device, including a memory, a processor, and a computer program stored on the memory and executable on the processor, and when the processor executes the program, the steps of the method for obtaining general chemical combinations for mixture toxicity assessment in any possible implementation manner of the first aspect are implemented.

[0018] To make the above objects, features, and advantages of the present invention more obvious and understandable, the following specifically enumerates preferred embodiments and, in conjunction with the accompanying drawings, details are described as follows. Description of the Drawings

[0019] To more clearly illustrate the technical solutions of the embodiments of the present invention, the following will briefly introduce the drawings required in the embodiments. It should be understood that the following drawings only show some embodiments of the present invention, and therefore should not be regarded as limiting the scope. For those of ordinary skill in the art, other related drawings can be obtained based on these drawings without creative efforts.

[0020] Figure 1 Shows a schematic flowchart of the method for obtaining general chemical combinations for mixture toxicity assessment provided by the embodiments of the present invention;

[0021] Figure 2 Shows another schematic diagram of the method for obtaining general chemical combinations for mixture toxicity assessment provided by the embodiments of the present invention;

[0022] Figure 3 Shows yet another schematic diagram of the method for obtaining general chemical combinations for mixture toxicity assessment provided by the embodiments of the present invention;

[0023] Figure 4 Shows a schematic diagram of constructing multi-level nodes in the method for obtaining general chemical combinations for mixture toxicity assessment provided by the embodiments of the present invention;

[0024] Figure 5 The schematic structural diagram of the device for obtaining a general chemical combination for mixture toxicity assessment provided by an embodiment of the present invention is shown;

[0025] Figure 6 The schematic structural diagram of an electronic device provided by an embodiment of the present invention. Detailed implementation manners

[0026] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. Apparently, the described embodiments are only some of the embodiments of the present invention, rather than all of the embodiments. Usually, the components of the embodiments of the present invention described and illustrated herein can be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of the present invention provided in the accompanying drawings is not intended to limit the scope of the claimed present invention, but merely represents selected embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative efforts shall fall within the protection scope of the present invention.

[0027] In the related art, based on binary mixtures (binary chemical combinations) or ternary mixtures, the method for studying the mixed exposure toxicity of pollutants in the actual environment is difficult to comprehensively evaluate the toxicity of chemical combinations that may exist in the environment, and the evaluation accuracy of environmental toxicity is relatively low. Therefore, based on the mixed exposure of chemicals in the actual environment, how to screen and identify the chemical combinations existing in the actual environment from a large number of possible chemical combinations is a problem that must be solved in the research on environmental toxicity risk assessment.

[0028] For the actual environment, among the detected chemicals, any combination of chemicals may form a chemical mixed exposure combination. For example, if 20 antibiotics are detected in a certain actual river basin, the number of antibiotic combinations composed of these 20 antibiotics will theoretically exceed one million (2 20 -1 = 1048575), but among these one million theoretical antibiotic combinations, the vast majority do not actually exist in the environment, or the amount is extremely scarce, and the toxic effect on the environment can be ignored. That is, among the co-exposure combinations of chemicals (chemical combinations) constructed in various ways, only a small number of chemical combinations are commonly or frequently present in the actual environment, while a large number of chemical combinations do not exist in the actual environment, or the toxic effect of the chemical combination on the environment can be ignored. Therefore, it is necessary to analyze the frequently occurring antibiotic combinations (mixtures) in this river basin from the 20 antibiotics, that is, to obtain the common general chemical combinations in the river basin for corresponding mixture toxicity assessment, so as to effectively reduce the workload of mixture toxicity assessment and improve the efficiency and accuracy of mixture toxicity assessment.

[0029] In this embodiment, a small number of chemical co-exposure combinations that are common or frequent in the actual environment and whose toxic effects on the environment cannot be ignored are called "common chemical combinations". The method of this embodiment screens and obtains common chemical combinations to provide a reference for subsequent environmental toxicity risk assessment, effectively reducing the number of chemical combinations for environmental mixture toxicity assessment and improving the efficiency of environmental mixture toxicity assessment. Specifically, based on chemical detection concentration data, frequent itemset mining (FIM) technology is used. For example, frequent itemset mining (FIM) is performed on 20 antibiotics obtained by detecting 20 sampling and detection points in the target environment to obtain the actually existing or highly probable antibiotic combinations composed of 20 antibiotics in the target environment. Then, according to the minimum support threshold (general level, such as a 50% probability), common antibiotic combinations are screened out. Based on the screened common antibiotic combinations, higher-order common antibiotic combinations are further screened for mixture toxicity assessment. For example, among the common antibiotic combinations screened according to the minimum support threshold, there are antibiotic combinations {C1, C2}, {C1, C4} and the antibiotic degree combination {C1, C2, C3}. Among them, the antibiotic degree combination {C1, C2, C3} is a higher-order combination (third order), and the antibiotic combinations {C1, C2}, {C1, C4} are lower-order combinations (second order). Therefore, among the common antibiotic combinations screened according to the minimum support, the higher-order combination may contain the lower-order combination (the higher-order combination {C1, C2, C3} contains the lower-order combination {C1, C2}, but does not contain the lower-order combination {C1, C4}). Since for the study of mixture toxicity assessment of mixtures, more complex combinations (higher-order combinations) are preferentially studied, through higher-order combination screening, the lower-order combination {C1, C2} can be eliminated to further improve the efficiency of mixture toxicity assessment. Thus, from the large number of chemical combinations that may theoretically form, common chemical combinations with actual and universal combinations are screened out, providing key reference information for the coexistence characteristics of chemicals and ecological risk assessment in the actual environment, and at the same time providing an important material basis and method support for mixture design in mixture toxicity research.

[0030] In this embodiment, the FIM technology is a big data mining technology originally used for shopping basket analysis, that is, to identify the set of items (frequent itemsets) that are frequently purchased together (i.e., frequently bought) from the list of items purchased in each consumer's shopping basket. Here, a single item is called an item, and a set of k items is called a k-itemset. In this embodiment, different environmental objects (such as collection and detection points) are defined as a transaction, each chemical is an item, and a set of k chemicals is called a k-itemset. The common chemical combinations in different environments are equivalent to the frequent itemsets in FIM. In this way, screening and identifying the common chemical combinations in different environments is converted into determining the frequent itemsets in FIM.

[0031] In this embodiment, the frequent itemset mining technology in data mining is used to screen and identify the common co-exposure combinations of antibiotics in different environmental systems, thereby forming a method for identifying common chemical combinations using FIM. Specifically, based on the pre-acquired basic dataset of chemical concentrations in different actual environments, a corresponding concentration threshold is set for each chemical, and the original data (basic dataset) is processed according to the concentration threshold to construct a "yes-no" dataset. The FIM technology is used to initially mine the frequently occurring chemical combinations to form common chemical combinations. Further, for the highest-order combination existing in each screened common chemical combination, a frequent itemset technology is established to identify the higher-order common chemical combinations.

[0032] An embodiment of the present invention provides a method for obtaining common chemical combinations for mixture toxicity assessment, which will be described below through embodiments.

[0033] Figure 1 The schematic flowchart of the method for obtaining common chemical combinations for mixture toxicity assessment provided by the embodiment of the present invention is shown. As Figure 1 shown, the process includes:

[0034] S101, count the total number of chemicals detected at each sampling and detection point in the target environment. For each sampling and detection point, based on the chemical concentration detected at the sampling and detection point and the total number of chemicals, construct a chemical detection matrix for the sampling and detection point, and based on the chemical detection matrices of each sampling and detection point, construct a compound detection matrix for the target environment;

[0035] In this embodiment, as an optional embodiment, the chemical detection matrix of the sampling and detection point is a row matrix, the number of columns included in the row matrix is the total number of chemicals, and each column corresponds to a detected chemical.

[0036] In this embodiment, as an alternative embodiment, taking a certain river basin as the target environment and taking the concentrations (ng / L) of 5 chemicals in 8 water samples (sampling and detection points, abbreviated as sampling points) as an example, the compound detection matrix of the target environment constructed based on the collected raw data is shown in Table 1. In Table 1, NR indicates not detected.

[0037]

[0038] S102. Query the pre-set mapping relationship between chemicals and analytical detection limits, and based on the target chemical concentration in the compound detection matrix and the analytical detection limit mapped to the target chemical, convert the compound detection matrix into a compound presence / absence matrix.

[0039] In this embodiment, when applying the FIM technology to basket analysis, it is analyzed based on the "presence - absence" of items in the consumer's shopping list. Therefore, when applying the FIM technology to the analysis of chemical concentrations in the actual environment, establish a "presence - absence" or "1 - 0" data set of relevant chemicals in different environmental objects, so as to convert the concentration data of each chemical into a chemical "presence - absence" data set according to the analytical detection limit of the chemical, thereby filtering out chemicals whose impact on the environment can be ignored.

[0040] In this embodiment, as an alternative embodiment, based on the target chemical concentration in the compound detection matrix and the analytical detection limit mapped to the target chemical, converting the compound detection matrix into a compound presence / absence matrix includes:

[0041] Traverse the target chemical concentration corresponding to each chemical in the compound detection matrix, obtain the analytical detection limit mapped to the chemical from the mapping relationship. If the target chemical concentration is greater than or equal to the analytical detection limit, update the target chemical concentration corresponding to the chemical to 1, otherwise, update the target chemical concentration corresponding to the chemical to 0.

[0042] In this embodiment, in the compound detection matrix, the columns are the detected chemicals, the rows are the sampling and detection points, and the row - column values are the detected chemical concentrations. As an alternative embodiment, if the chemical concentration is greater than the analytical detection limit corresponding to the chemical, it indicates that the chemical exists or is "present" or is "1", otherwise, it is determined that the chemical does not exist or is "absent" or is "0".

[0043] In this embodiment, as an alternative embodiment, for the analytical detection limit of a chemical, based on the impact of the chemical on the environment, the set analytical detection limit may vary depending on the instrument used to detect the chemical and the detection method. For example, for detecting antibiotic A using a certain detection method with a certain instrument, the set analytical detection limit is 0.04 ng / L. For detecting antibiotic A using another instrument with the same detection method, the set analytical detection limit may also be 0.035 ng / L. In this embodiment, taking the detection using a certain detection method with a certain instrument as an example, for each sampling and detection point, if the detection result of antibiotic A < 0.04 ng / L, it means that antibiotic A does not exist at the corresponding sampling point, that is, "none" or "0". As an alternative embodiment, the "yes - no" data conversion is performed on the chemical concentration data in Table 1, and the resulting compound presence - absence matrix is shown in Table 2.

[0044]

[0045] In this embodiment, after processing the chemical concentration data sets of each sampling and detection point in the target environment into "yes - no" data sets (compound presence - absence matrices), it is convenient to subsequently process the "yes - no" data sets using the FIM technique.

[0046] S103. For each candidate chemical in the compound presence - absence matrix, based on the occurrence frequency of the candidate chemical in the compound presence - absence matrix and a preset first frequency threshold, construct the first frequent item set of chemicals;

[0047] In this embodiment, let I = {a1, a2, …, am} be the set of items, where a1, a2, …, am are m different items, each item representing a chemical, m being the total number of chemicals, which is the number of columns of the compound presence - absence matrix. D = {T1, T2, …, Tn} is the transaction data set, and each transaction Ti (i ∈ {1, 2, …, n}) is a subset of I. Among them, each transaction is identified by a corresponding transaction identifier (TID, Task Identifier), representing the sampling and detection point, and n is the number of sampling and detection points in the target environment, that is, the number of rows of the compound presence - absence matrix.

[0048] In this embodiment, if a subset A of I satisfies A T, then it is said that transaction T contains subset A. Among them, the support of a subset (item set) is defined as: the proportion of the number of transactions containing the subset in the total number of transactions. If the support of a certain item set is greater than the preset minimum support threshold, then this item set is called a frequent item set or a frequent pattern, and a frequent item set with a length of k is called a frequent k - item set. As an alternative embodiment, since the number of chemicals in the compound presence - absence matrix is fixed, the support can be characterized by the occurrence frequency.

[0049] In this embodiment, the total number of chemicals included in different sampling detection points corresponds to items, the item set corresponds to the mixture composed of chemicals, different sampling detection points correspond to transactions, the support degree is the proportion of the number of chemicals containing the same item set (composed of the same phase) in the total number of chemicals, and the mixture with a support degree greater than the preset support degree threshold is a common chemical mixture.

[0050] In this embodiment, it is assumed that the number of sampling detection points is 5, and the total number of chemicals detected at the 5 sampling detection points is 5. Si represents the i-th sampling detection point, Ci represents the i-th chemical, and ND represents not detected.

[0051] Among them, S1 = {C2, C3, C5}, indicating that in sampling detection point 1, it contains three chemicals C2, C3, and C5;

[0052] S2 = {C1, C3, C4, C5};

[0053] S3 = {C1, C2, C3, C4};

[0054] S4 = {C1, C3, C4};

[0055] S5 = {C1, C2, C3, C4}.

[0056] Then the constructed presence - absence matrix of compounds is shown in Table 3.

[0057]

[0058] In this embodiment, it is assumed that the first frequency threshold is set to 3. Then, based on Table 3, for chemical C1, the occurrence frequency in the presence - absence matrix of compounds is 4, which is greater than the first frequency threshold 3. Then C1 is placed in the first frequent item set of chemicals. In this way, the finally obtained first frequent item set of chemicals includes: C1, C2, C3, and C4, that is, (C1, C2, C3, C4).

[0059] S104. Based on the preset item set optimization strategy, optimize the first frequent item set of chemicals from low - order chemical combinations to high - order chemical combinations, and sequentially obtain high - order frequent item sets;

[0060] In this embodiment, as an optional embodiment, based on the preset item set optimization strategy, optimize the first frequent item set of chemicals from low - order chemical combinations to high - order chemical combinations, and sequentially obtain high - order frequent item sets, including:

[0061] A11, combining candidate chemicals in the first frequent item set of chemicals in pairs to obtain binary chemical combinations, obtaining the frequencies of occurrence of the binary chemical combinations in the compound presence / absence matrix, and constructing a second frequent item set of chemicals based on the binary chemical combinations whose frequencies of occurrence are greater than or equal to a preset second frequency threshold;

[0062] In this embodiment, taking the first frequent item set of chemicals including C1, C2, C3 and C4 as an example, the binary chemical combinations that are combined in pairs include six combinations: (C1, C2), (C1, C3), (C1, C4), (C2, C3), (C2, C4) and (C3, C4).

[0063] In this example, for the binary chemical combination (C1, C2), the frequency of occurrence (co-occurrence frequency) in the compound presence matrix is 2; the frequency of occurrence of (C1, C3) is 4, the frequency of occurrence of (C1, C4) is 4, the frequency of occurrence of (C2, C3) is 3, and the frequency of occurrence of (C2, C4) is 2. Chemicals C3 and C4 are present at sampling points S2, S3, S4, and S5 at the same time, so the frequency of occurrence of (C3, C4) is 4. If the second frequency threshold is set to 3, the constructed second frequent item set of chemicals includes: {(C1, C3), (C1, C4), (C2, C3), (C3, C4)}.

[0064] A12, for the candidate chemicals in the second frequent item set of chemicals, any three candidate chemical combinations are performed to obtain a third-order chemical combination, and the occurrence frequencies of the third-order chemical combinations in the compound presence / absence matrix are sequentially obtained. Based on the third-order chemical combinations whose occurrence frequencies are greater than or equal to a preset third frequency threshold, a third frequent item set of chemicals is constructed until there is no higher-order chemical combination whose frequency is greater than or equal to the preset high-order frequency threshold.

[0065] In this embodiment, as an optional embodiment, any three candidate chemical combinations are performed on the candidate chemicals in the second frequent item set of chemicals, including:

[0066] Eliminating binary chemical combinations whose occurrence frequency is equal to a preset second frequency threshold from the second frequent item set of chemicals to obtain a filtered second frequent item set of chemicals;

[0067] Three candidate chemicals are randomly selected from the second frequent item filtered set of chemicals to obtain the third-order chemical combination.

[0068] In this embodiment, as an alternative embodiment, the monotonicity of support in the FIM algorithm (i.e., if a k-itemset or k-component chemical mixture is extended (e.g., by adding one or more chemicals thereto), the support of the k-itemset or k-component chemical mixture will not increase) can be utilized to screen for common chemical combinations. For example, taking the above itemset {C3, C4} as an example, if the support of the itemset {C3, C4} is 0.8, then after adding a new chemical to this itemset, the support of the resulting new itemset cannot exceed the support of this itemset, which is 0.8. For instance, when adding the new chemical C2 to the itemset {C3, C4}, the resulting new itemset {C2, C3, C4} appears together 2 times in 5 samples, and the corresponding support is 0.4. That is, assuming the minimum common level is 50%, if the support of a combination (itemset) is 0.5, then for all other combinations obtained by adding one or more chemicals to this combination, the corresponding support cannot be greater than 0.5. Therefore, there is no need for further screening.

[0069] Figure 2 Another schematic diagram showing the method for obtaining common chemical combinations for mixture toxicity assessment provided by the embodiment of the present invention is as follows Figure 2As shown, in this embodiment, the Apriori algorithm is used to obtain general chemical combinations. By scanning all the obtained data, as an alternative embodiment, each item set (compound presence / absence matrix) is scanned in sequence. For example, the support (frequency of occurrence) of the 1-item set C1 is scanned. Assuming that the set minimum support is 2, based on the support of each scanned item set and according to the minimum support (frequency threshold), pruning is performed. Suppose the set L1 of frequent 1-item sets is obtained, including antibiotics ({1}, {2}, {3}, {5}); then, combinations of second-level frequent items in the set L1 of frequent 1-item sets are constructed. For example, the combinations of second-level frequent items in the set L1 ({1}, {2}, {3}, {5}) include: ({1 2}, {2 3}, {3 5}, {1 3}, {2 5}, {1 5}), thus generating the set L2 of candidate 2-item sets. Next, the support of each chemical combination in the set of candidate 2-item sets (2-item sets) is scanned for the second time, and then based on the minimum support, the set L2 of frequent 2-item sets is obtained through pruning. Specifically, the support of the chemical combination {1 2} is 1, the support of {2 3} is 2, the support of {3 5} is 1, the support of {1 3} is 2, the support of {2 5} is 3, and the support of {1 5} is 2. Among them, the supports of {1 2} and {3 5} are less than the minimum support of 2 and are excluded. In this way, the set L2 of frequent 2-item sets obtained through pruning includes ({2 3}, {1 3}, {2 5}, {1 5}); then, combinations of third-level frequent items in L2 are constructed to generate the set C3 of candidate 3-item sets. Since the set L2 of frequent 2-item sets only contains antibiotics 1, 2, 3, and 5, the set C3 of candidate 3-item sets generated includes: ({1 2 3}, {1 3 5}, {2 3 5}). The support of the 3-item set is scanned, and the set L3 of frequent 3-item sets is obtained through pruning, which is {2 3 5}. Since the frequent 3-item set only contains three antibiotics, therefore, there is no need to construct a fourth-level set, and the maximum frequent item set is the 3-item set L3.

[0070] In this embodiment, as another alternative embodiment, taking the second-level frequent item sets of chemicals including: (C1, C3), (C1, C4), (C2, C3), and (C3, C4) as an example, the number of candidate chemicals included is 4, and the number of higher-order combinations is 3. Then, 4 third-level chemical combinations can be constructed, which are: (C1, C2, C3), (C1, C2, C4), (C2, C3, C4).

[0071] In this embodiment, for the 3-order chemical combination (C1, C2, C3), the occurrence frequency in Table 3 is 2; the occurrence frequency of (C1, C2, C4) is 2; the occurrence frequency of (C2, C3, C4) is 2. If the preset third frequency threshold is 3, the processing of the 3-order chemical combination ends, and the general chemical combinations obtained for mixture toxicity assessment are (C1, C2, C3), (C1, C2, C4), and (C2, C3, C4); if the preset third frequency threshold is 2, since the occurrence frequencies of the 3-order chemical combinations: (C1, C2, C3), (C1, C2, C4), and (C2, C3, C4) are all equal to the third frequency threshold, the 3-order chemical combinations: (C1, C2, C3), (C1, C2, C4), and (C2, C3, C4) are placed in the third chemical frequent item set for 4-order combination. As an alternative embodiment, the number of chemicals included in the third chemical frequent item set is 4. Therefore, the 4-order chemical combination is (C1, C2, C3, C4), and this 4-order chemical combination is the general chemical combination obtained for mixture toxicity assessment.

[0072] In this embodiment, as another alternative embodiment, based on the preset item set optimization strategy, the first chemical frequent item set is optimized from low-order chemical combinations to high-order chemical combinations, and high-order frequent item sets are obtained in sequence, including:

[0073] B11, construct a root node;

[0074] B12, in the compound presence / absence matrix corresponding to the first chemical frequent item set, extract the candidate chemicals in the first row, arrange them in descending order of the occurrence frequency, and sequentially construct multiple levels of child nodes under the root node. Among them, the level of the child node is the number of candidate chemicals included in the first row, and the candidate chemical with a high occurrence frequency is the parent node of the candidate chemical with a low occurrence frequency. Set the count of the candidate chemicals of each level of child node to 1;

[0075] B13, traverse the other rows in the compound presence / absence matrix, arrange them in descending order of the occurrence frequency of the candidate chemicals, traverse each candidate chemical in the sorted row. If the i-th candidate chemical in this row is the same as the candidate chemical of the i-th child node under the root node, increment the count of this child node by 1. If they are different, starting from the (i - 1)-th child node under the root node, create a child node for the i-th candidate chemical under the (i - 1)-th child node, set the count of the candidate chemical of the newly created child node to 1, and under the newly created child node, sequentially construct multiple levels of child nodes for the candidate chemicals after the i-th candidate chemical in this row;

[0076] Figure 3Another schematic diagram showing the method provided by the embodiment of the present invention for obtaining a general chemical combination for mixture toxicity assessment is shown. As Figure 3 shown, in this embodiment, the chemicals detected at each sampling and detection point (TID: 100 - 500) in the target environment are obtained ( Figure 3 on the left), the number of times each chemical detected in the target environment appears at each sampling and detection point is counted, and based on the number of times the chemical appears, the chemicals greater than the minimum support (for example, the minimum support is 3) are found to obtain frequent items. For each frequent item, they are re - sorted in the order of support size ( Figure 3 in the middle), based on the re - sorted frequent items, for each sampling and detection point, the sampling point is updated according to the sorted frequent items, and the sampling point item set obtained according to the sorted frequent items is obtained ( Figure 3 on the right).

[0077] Figure 4 A schematic diagram showing the construction of multi - level nodes in the method provided by the embodiment of the present invention for obtaining a general chemical combination for mixture toxicity assessment is shown. As Figure 4 shown, based on Figure 3 construct an FP - Tree: It consists of three parts: the frequent 1 - item set (also called the frequent item header table), the root node (root) marked as null, and the item prefix subtree (head of node - links). For example, the frequent item header table is f, c, a, b, m, p arranged from largest to smallest in terms of support, and the item prefix subtree contains three - level nodes. The process of constructing the FP - Tree is to insert the items in the transaction into the item prefix subtree sequentially starting from the root node. When encountering the same item, the count of the child node is incremented by 1, and when encountering a different item, a new child node is created.

[0078] In this embodiment, the frequencies of the statistically - counted chemicals from high to low are: chemical f: 4, chemical c: 4, chemical a: 3, chemical b: 3, chemical m: 3, chemical p: 3, and the frequencies of the remaining chemicals are all less than 3. In this embodiment, the threshold is set to 3;

[0079] Assume that for sampling and detection point 100, the detected chemicals include: f, a, c, d, g, i, m, p. After threshold screening and sorting, the first row in the compound presence - absence matrix is: f, c, a, m, p;

[0080] For sampling and detection point 200, the detected chemicals include: a, b, c, f, l, m, o. After threshold screening and sorting, the second row in the compound presence - absence matrix is: f, c, a, b, m;

[0081] For sampling detection point 300, the detected chemicals include: b, f, h, j, o. After threshold screening and sorting, the third row in the compound presence / absence matrix is: f, b;

[0082] For sampling detection point 400, the detected chemicals include: b, c, k, s, p. After threshold screening and sorting, the fourth row in the compound presence / absence matrix is: c, b, p;

[0083] For sampling detection point 500, the detected chemicals include: a, f, c, e, l, p, m, n. After threshold screening and sorting, the fifth row in the compound presence / absence matrix is: f, c, a, m, p;

[0084] For f, c, a, m, p sorted in the first row; under the root node, construct an f child node with a count of 1. Under the f child node, construct a c child node with a count of 1. Under the c child node, construct an a child node with a count of 1. Under the a child node, construct an m child node with a count of 1. Under the m child node, construct a p child node with a count of 1;

[0085] For f, c, a, b, m sorted in the second row; under the root node, there is an f child node, so update the count of this f child node to 2. Similarly, for the second chemical c and the third chemical a, there are corresponding second-level (c child node) and third-level (a child node) child nodes, and update the counts of the c child node and the a child node to 2 respectively. For the fourth chemical b, the fourth-level (m child node) does not match the chemical b, so construct a b child node with a count of 1 under the third-level (a child node) (parallel to the m child node), and correspondingly, construct an m child node with a count of 1 under the b child node;

[0086] For f, b in the third row; under the root node, there is an f child node, so update the count of this f child node to 3. For the second chemical b, the second-level (c child node) does not match the chemical b, so construct a b child node with a count of 1 under the first-level (f child node) (parallel to the c child node);

[0087] For c, b, p in the fourth row; under the root node, there is no c child node, so construct a c child node with a count of 1 under the root node (parallel to the f child node), and under this c child node, construct b and p child nodes with counts of 1 in sequence;

[0088] For f, c, a, m, p in the 5th row; under the root node, there is an f child node. Therefore, update the count of this f child node to 4. Similarly, for the 2nd chemical c, the 3rd chemical a, the 4th chemical m, and the 5th chemical p, there are corresponding 2nd-level child nodes (c child nodes), 3rd-level child nodes (a child nodes), 4th-level child nodes (m child nodes), and 5th-level child nodes (p child nodes). Increment the count values of each child node by 1 respectively, and finally obtain the multi-level child nodes of the candidate chemicals.

[0089] B14. From the multi-level child nodes, select candidate frequent chemicals, locate the positions of the candidate frequent chemicals in the multi-level child nodes, perform root node tracing for each located position to obtain the child node chain corresponding to each position, obtain the common chemicals included in each child node chain, accumulate the counts of the common chemicals included in each child node chain to obtain a frequent item set containing the counts of the common chemicals. If the count of the common chemicals exceeds the pre-set count threshold, determine the frequent item set corresponding to the count of the common chemicals as a high-order frequent item set.

[0090] In this embodiment, mining high-order frequent item sets means starting from a specific suffix, constructing the conditional pattern base of the FP-Tree, and determining whether it is frequent according to the updated counts of the items on the conditional pattern base. For example, taking the antibiotic p as the suffix, the two prefixes of this antibiotic p form conditional pattern bases respectively as: {{p, m, a, c, f: 2}, {p, b, c: 1}}, and the generated conditional FP-Tree is: <p:3, c:3>. The finally obtained frequent item set is {p, c: 3}. Specifically, in the item prefix subtree, there are conditional pattern bases formed by two prefixes of the chemical p, respectively: {{p, m, a, c, f: 2}, {p, b, c: 1}}, where the numbers are the counts of the chemical p. Among the conditional pattern bases formed by the two prefixes of the chemical p, the common chemicals are p and c. Accumulate the counts of the chemicals p and c respectively to generate the conditional FP-Tree: <p:3, c:3>. Therefore, the finally obtained frequent item set is {p, c: 3}.

[0091] S105. Based on the first frequent item set of the chemicals and the sequentially obtained high-order frequent item sets, obtain the general chemical combinations for toxicity test evaluation.

[0092] In this embodiment, the toxicity test is evaluated as a mixture toxicity evaluation. Using the FIM algorithm, all general chemical combinations containing two or more chemicals can be initially screened out. However, in practical applications, the components of some low-order general chemical combinations may be repeated with those of high-order general chemical combinations, indicating that these low-order combinations actually exist in a more complex form. Therefore, studying high-order general chemical combinations can not only avoid repeated analysis, but also more comprehensively reveal the complex correlation relationships between chemicals, which is more practically significant. Therefore, in this embodiment, all frequent itemsets screened by the FIM algorithm are further screened. As an alternative embodiment, based on the first frequent itemset of chemicals and the high-order frequent itemsets obtained in sequence, general chemical combinations for mixture toxicity evaluation are obtained, including:

[0093] C11. From the high-order frequent itemsets obtained in sequence, obtain the high-order frequent itemset containing the largest number of chemicals. Based on the high-order frequent itemset containing the largest number of chemicals, construct a first set, and construct a second set based on the remaining frequent itemsets other than the first set, where the largest number of chemicals is n;

[0094] In this embodiment, the high-order frequent itemset with the number of chemicals being n (natural number) is used as the first set, and the remaining frequent itemsets (the number of chemicals being n - 1, n - 2, …, 3, 2) are used as the second set. Among them, the high-order frequent itemset containing the largest number of chemicals is the highest-order frequent itemset, which is the itemset with the largest number of chemicals contained in each frequent itemset. The second set includes the first frequent itemset of chemicals and the high-order frequent itemsets obtained in sequence, excluding the highest-order frequent itemset.

[0095] C12. From the second set, extract all candidate frequent itemsets with the number of chemicals being n - 1. For each candidate frequent itemset, if the candidate frequent itemset is a subset of any frequent itemset in the first set, then from the second set, eliminate the candidate frequent itemset; if not, merge the candidate frequent itemset with the first set and update the first set;

[0096] In this embodiment, for each high-order frequent itemset with the number of chemicals being n - 1 in the second set, determine whether the high-order frequent itemset is a subset of any itemset in the first set, that is, determine whether the first set contains the high-order frequent itemset. If so, then eliminate the high-order frequent itemset from the second set and proceed to judge the next high-order frequent itemset; if not, then cut the high-order frequent itemset from the second set, and merge the cut high-order frequent itemset with the first set to form a new first set, and proceed to judge the next high-order frequent itemset. Among them, the merge means placing the cut high-order frequent itemset in the first set, and together with the original high-order frequent itemset with the number of chemicals being n in the first set, becoming two subsets of the first set.

[0097] C13. Traverse all candidate frequent itemsets in the second set where the number of chemicals is less than n - 1. For each candidate frequent itemset, if the candidate frequent itemset is a subset of any frequent itemset in the first set, remove the candidate frequent itemset from the second set; if not, merge the candidate frequent itemset with the updated first set.

[0098] In this embodiment, in the above manner, successively determine the itemsets in the second set with the number of chemicals being n - 2, n - 3, etc., until all itemsets with the number of chemicals being 2 in the second set are determined.

[0099] C14. Obtain the first set that has been finally updated to get the general chemical combinations for the mixture toxicity assessment.

[0100] In this embodiment, the second set contains all chemical combinations with the number of chemicals being n - 1, n - 2, …, 3, 2. Start from the chemical combinations with the number of chemicals being n - 1 in the second set and make judgments with the first set. If it is a subset, remove it; if not, merge it with the first set to form a new first set. Then make judgments with the new first set from the chemical combinations with the number of chemicals being n - 2 in the second set until all chemical combinations with the number of chemicals being 2 in the second set are judged. The final first set is the highest - order frequent itemset, representing the most complex form of each general chemical combination.

[0101] The method of this embodiment can ensure that only the most complex general chemical combinations are retained, avoiding duplication and redundancy.

[0102] In this embodiment, assume that the first set and the second set are as shown in Table 4.

[0103]

[0104] In this embodiment, in Table 4 above, {'C2', 'C3', 'C4'} is the chemical combination with the largest number of chemicals (3), which is used as the first set. In practical applications, if there are multiple chemical combinations with 3 chemicals, then these multiple chemical combinations are respectively placed into the first set. The remaining chemical combinations {'C4', 'C3'}, {'C2', 'C4'}, {'C2', 'C3'}, {'C1', 'C3'} are the second set, that is, the second set contains 4 chemical combinations. Next, it is determined whether the chemical combinations with the number of chemicals being (3 - 1 = 2) in the second set are subsets of the first set. Among them, the chemical combinations {'C4', 'C3'}, {'C2', 'C4'}, {'C2', 'C3'} are all subsets of the first set {'C2', 'C3', 'C4'}. Therefore, these three chemical combinations are removed from the second set. The chemical combination {'C1', 'C3'} is not a subset of the first set, so the first set is updated based on this chemical combination to obtain a new first set ({'C1', 'C3'}, {'C2', 'C3', 'C4'}).

[0105] In this embodiment, since the chemical combination with 2 chemicals is the lowest-order chemical combination, the new set ({'C1', 'C3'}, {'C2', 'C3', 'C4'}) is the final general chemical combination, as shown in Table 5.

[0106]

[0107] In this embodiment, for the 5 detected chemicals, the theoretically possible number of chemical combinations is 31, while the final general chemical combinations obtained by the method of this embodiment are actually only 2. These two general chemical combinations occur frequently in the actual environment and are universal. Therefore, the method of this embodiment can screen out a small number of actual general combinations from the large number of chemical combinations that may be formed theoretically.

[0108] In this embodiment, by obtaining a small amount of a general chemical combination, it can be subsequently studied as a priority mixture. As an alternative embodiment, each target chemical contained in the general chemical combination is obtained; according to the concentration ranges of the respective target chemicals in the target environment, for each chemical combination in the general chemical combination, a reagent for evaluating the toxicity of the mixture is configured based on the concentration ranges of the chemicals contained in the chemical combination; a mixture toxicity experiment is performed based on each configured reagent to obtain a mixture toxicity evaluation result. For example, the selected general chemical combination {'C2', 'C3', 'C4'} is used for mixture toxicity research. According to the concentration ranges of the three chemicals 'C2', 'C3', and 'C4' in the actual environment, the general chemical combination is designed for mixtures, and the toxicity of each mixture is evaluated and the toxic interactions are analyzed to reveal the toxicity change rules of the general chemical combination, providing practical methods and techniques for the mixture toxicity evaluation and risk assessment of mixed pollutants in the actual environment.

[0109] In the related art, in the study of mixtures, the selected mixtures may not necessarily exist or be prevalent in the actual environment, thus deviating from the practical environmental significance. The general chemical combination screened by the method of this embodiment frequently occurs in the actual environment and has universality, and the corresponding mixture toxicity research thereof has more practical environmental significance.

[0110] Figure 5 The schematic structural diagram of the device for obtaining a general chemical combination for mixture toxicity evaluation provided by an embodiment of the present invention is shown. As Figure 5 shown, the device includes:

[0111] A concentration matrix construction module 501, configured to count the total number of chemicals detected at each sampling and detection point in the target environment, and for each sampling and detection point, construct a chemical detection matrix for this sampling and detection point based on the chemical concentration detected at this sampling and detection point and the total number of chemicals, and construct a compound detection matrix for the target environment based on the chemical detection matrices of each sampling and detection point;

[0112] In this embodiment, as an alternative embodiment, the chemical detection matrix of the sampling and detection point is a row matrix, the number of columns included in the row matrix is the total number of chemicals, and each column corresponds to a detected chemical.

[0113] A presence / absence matrix conversion module 502, configured to query a pre-set mapping relationship between chemicals and analytical detection limits, and based on the target chemical concentration in the compound detection matrix and the analytical detection limit mapped to this target chemical, convert the compound detection matrix into a compound presence / absence matrix;

[0114] In this embodiment, as an alternative embodiment, the presence / absence matrix conversion module 502 is specifically configured to:

[0115] Traverse the target chemical concentration corresponding to each chemical in the compound detection matrix, obtain the analytical detection limit mapped by this chemical from the mapping relationship. If the target chemical concentration is greater than or equal to the analytical detection limit, update the target chemical concentration corresponding to this chemical to 1; otherwise, update the target chemical concentration corresponding to this chemical to 0.

[0116] The low-order frequent item set construction module 503 is configured to, for each candidate chemical in the presence / absence matrix of compounds, construct a first chemical frequent item set based on the occurrence frequency of this candidate chemical in the presence / absence matrix of compounds and a preset first frequency threshold;

[0117] The high-order frequent item set construction module 504 is configured to optimize the first chemical frequent item set from low-order chemical combinations to high-order chemical combinations based on a preset item set optimization strategy, and sequentially obtain high-order frequent item sets;

[0118] In this embodiment, as an alternative embodiment, the high-order frequent item set construction module 504 is specifically configured to:

[0119] Combine the candidate chemicals in the first chemical frequent item set in pairs to obtain binary chemical combinations, obtain the occurrence frequency of these binary chemical combinations in the presence / absence matrix of compounds, and construct a second chemical frequent item set based on the binary chemical combinations whose occurrence frequency is greater than or equal to a preset second frequency threshold;

[0120] Combine any three candidate chemicals in the second chemical frequent item set to obtain third-order chemical combinations, sequentially obtain the occurrence frequency of these third-order chemical combinations in the presence / absence matrix of compounds, and construct a third chemical frequent item set based on the third-order chemical combinations whose occurrence frequency is greater than or equal to a preset third frequency threshold, until there are no high-order chemical combinations whose occurrence frequency is greater than or equal to a preset high-order frequency threshold.

[0121] In this embodiment, as an alternative embodiment, the values of the first frequency threshold, the second frequency threshold, and the third frequency threshold are the same. As another alternative embodiment, the values of the first frequency threshold, the second frequency threshold, and the third frequency threshold may be different from each other or partially the same.

[0122] In this embodiment, as an alternative embodiment, combining any three candidate chemicals in the second chemical frequent item set includes:

[0123] From the second most frequent item set of the chemicals, eliminate the binary chemical combinations whose occurrence frequencies are equal to the preset second frequency threshold to obtain the second most frequent item filtered set of chemicals;

[0124] Arbitrarily select three candidate chemicals from the second most frequent item filtered set of chemicals to obtain the third-order chemical combination.

[0125] In this embodiment, as another alternative embodiment, the high-order frequent item set construction module 504 is specifically configured to:

[0126] Construct a root node;

[0127] In the compound presence / absence matrix corresponding to the first most frequent item set of the chemicals, extract the candidate chemicals in the first row, arrange them in descending order of the occurrence frequencies of the candidate chemicals, and sequentially construct multiple levels of child nodes under the root node. Among them, the level of the child node is the number of candidate chemicals included in the first row, and the candidate chemical with a higher occurrence frequency is the parent node of the candidate chemical with a lower occurrence frequency. Set the count of the candidate chemicals of each level of child nodes to 1;

[0128] Traverse the other rows in the compound presence / absence matrix, arrange them in descending order of the occurrence frequencies of the candidate chemicals, traverse each candidate chemical in the sorted row. If the i-th candidate chemical in this row is the same as the candidate chemical of the i-th child node under the root node, increment the count of this child node by 1. If they are different, starting from the (i - 1)-th child node under the root node, create a child node for the i-th candidate chemical under the (i - 1)-th child node, set the count of the candidate chemical of the newly created child node to 1, and under the newly created child node, sequentially construct multiple levels of child nodes for the candidate chemicals after the i-th candidate chemical in this row;

[0129] Select candidate frequent chemicals from the multiple levels of child nodes, locate the positions of the candidate frequent chemicals in the multiple levels of child nodes, perform root node tracing for each located position to obtain the child node chain corresponding to each position, obtain the common chemicals included in each child node chain, accumulate the counts of the common chemicals included in each child node chain to obtain a frequent item set including the count of the common chemicals. If the count of the common chemicals exceeds the preset count threshold, determine the frequent item set corresponding to the count of the common chemicals as the high-order frequent item set.

[0130] The chemical combination acquisition module 505 is used to obtain a general chemical combination for performing mixture toxicity assessment based on the first most frequent item set of the chemicals and the sequentially obtained high-order frequent item sets.

[0131] In this embodiment, as an alternative embodiment, the chemical combination acquisition module 505 is specifically configured to:

[0132] From the sequentially obtained high-order frequent item sets, obtain the high-order frequent item set containing the largest number of chemicals. Based on the high-order frequent item set containing the largest number of chemicals, construct a first set, and construct a second set based on the remaining frequent item sets other than the first set, where the largest number of chemicals is n;

[0133] From the second set, extract all candidate frequent item sets with the number of chemicals being n - 1. For each candidate frequent item set, if the candidate frequent item set is a subset of any frequent item set in the first set, remove the candidate frequent item set from the second set. If not, merge the candidate frequent item set with the first set and update the first set;

[0134] Traverse all candidate frequent item sets in the second set with the number of chemicals less than n - 1. For each candidate frequent item set, if the candidate frequent item set is a subset of any frequent item set in the first set, remove the candidate frequent item set from the second set. If not, merge the candidate frequent item set with the updated first set;

[0135] Obtain the finally updated first set to obtain the universal chemical combination for mixture toxicity assessment.

[0136] In this embodiment, as an alternative embodiment, the apparatus further includes:

[0137] A mixture toxicity assessment module (not shown in the figure) for obtaining each target chemical contained in the universal chemical combination;

[0138] According to the concentration ranges of the respective target chemicals in the target environment, for each chemical combination in the universal chemical combination, configure a reagent for mixture toxicity testing according to the concentration ranges of the chemicals included in the chemical combination;

[0139] Perform mixture toxicity tests based on each configured reagent to obtain mixture toxicity assessment results.

[0140] Based on the same inventive concept, an embodiment of the present invention further provides a storage medium, on which a computer program is stored. When the program is executed by a processor, the steps of the method for obtaining a universal chemical combination for mixture toxicity assessment in any possible implementation manner described above are implemented.

[0141] Optionally, the storage medium may be a non-temporary computer-readable storage medium. For example, the non-temporary computer-readable storage medium may be a ROM, a random access memory (RAM), a CD-ROM, a magnetic tape, a floppy disk, and an optical data storage device, etc.

[0142] Based on the same inventive concept, see Figure 6, an embodiment of the present invention further provides an electronic device, including a memory 101 (such as a non-volatile memory), a processor 102, and a computer program stored on the memory 101 and executable on the processor 102. When the processor 102 executes the program, it implements the steps of the method for obtaining a general chemical combination for mixture toxicity assessment in any possible implementation manner above, which is equivalent to the device for obtaining a general chemical combination for mixture toxicity assessment as described above. Of course, this processor can also be used to process other data or perform operations. The electronic device can be a device such as a PC, a server, a terminal, etc.

[0143] As Figure 6 shown, the electronic device generally may further include: a memory 103, a network interface 104, and an internal bus 105. In addition to these components, other hardware may also be included, which will not be elaborated here.

[0144] It should be noted that the above device for obtaining a general chemical combination for mixture toxicity assessment can be implemented by software. As a logically meaningful device, it is formed by the processor 102 of the electronic device where it is located reading the computer program instructions stored in the non-volatile memory into the memory 103 and running them.

[0145] It should be noted that: similar reference numerals and letters represent similar items in the following drawings. Therefore, once an item is defined in one drawing, it does not need to be further defined and explained in subsequent drawings. In addition, the terms "first", "second", "third", etc. are only used for distinguishing descriptions and cannot be understood as indicating or implying relative importance.

[0146] Finally, it should be noted that: the above-described embodiments are only specific implementation manners of the present application, used to illustrate the technical solutions of the present application, rather than limiting them. The protection scope of the present application is not limited thereto. Although the present application has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that: any person skilled in the art within the technical scope disclosed by the present application can still modify the technical solutions recorded in the foregoing embodiments, or can easily think of changes, or perform equivalent replacements on some of the technical features; and these modifications, changes or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present application. All should be covered within the protection scope of the present application. Therefore, the protection scope of the present application should be subject to the protection scope of the claims.

Claims

1. A method for obtaining a general chemical combination for mixture toxicity assessment, characterized in that, Including: Count the total number of chemicals detected at each sampling and detection point in the target environment. For each sampling and detection point, construct a chemical detection matrix for this sampling and detection point based on the chemical concentration detected at this sampling and detection point and the total number of the chemicals, and construct a compound detection matrix for the target environment based on the chemical detection matrices of each sampling and detection point; Construct a mapping relationship between chemicals and analytical detection limits, and convert the compound detection matrix into a compound presence / absence matrix based on the target chemical concentration in the compound detection matrix and the analytical detection limit mapped to this target chemical; For each candidate chemical in the compound presence / absence matrix, construct a first frequent item set of chemicals based on the occurrence frequency of this candidate chemical in the compound presence / absence matrix and a preset first threshold of frequency; Based on a preset item set optimization strategy, optimize the first frequent item set of chemicals from low-order chemical combinations to high-order chemical combinations, and sequentially obtain high-order frequent item sets; Based on the first frequent item set of chemicals and the sequentially obtained high-order frequent item sets, obtain general chemical combinations for mixture toxicity assessment and risk evaluation; 2. The method for obtaining a general chemical combination for mixture toxicity assessment according to claim 1, characterized in that, The step of, based on a preset item set optimization strategy, optimizing the first frequent item set of chemicals from low-order chemical combinations to high-order chemical combinations and sequentially obtaining high-order frequent item sets includes: Combine the candidate chemicals in the first frequent item set of chemicals pairwise to obtain binary chemical combinations, obtain the occurrence frequency of these binary chemical combinations in the compound presence / absence matrix, and construct a second frequent item set of chemicals based on the binary chemical combinations whose occurrence frequency is greater than or equal to a preset second threshold of frequency; Combine any three candidate chemicals in the second frequent item set of chemicals to obtain third-order chemical combinations, sequentially obtain the occurrence frequency of these third-order chemical combinations in the compound presence / absence matrix, and construct a third frequent item set of chemicals based on the third-order chemical combinations whose occurrence frequency is greater than or equal to a preset third threshold of frequency until there are no high-order chemical combinations whose occurrence frequency is greater than or equal to a preset high-order threshold of frequency; 3. The method for obtaining a general chemical combination for mixture toxicity assessment according to claim 2, characterized in that, The step of combining any three candidate chemicals in the second frequent item set of chemicals includes: Exclude the binary chemical combinations whose occurrence frequency is equal to the preset second threshold of frequency from the second frequent item set of chemicals to obtain a filtered set of the second frequent item set of chemicals; Arbitrarily select three candidate chemicals from the filtered set of the second frequent item set of chemicals to obtain the third-order chemical combinations; 4. The method for obtaining a universal chemical combination for mixture toxicity assessment according to claim 1 or 2, characterized in that, The step of, based on a preset item set optimization strategy, optimizing the first frequent item set of chemicals from low-order chemical combinations to high-order chemical combinations and sequentially obtaining high-order frequent item sets includes: Construct a root node; In the compound presence / absence matrix corresponding to the first frequent itemset of chemicals, extract the candidate chemicals in the first row, arrange them in descending order of the occurrence frequency of the candidate chemicals, and successively construct multiple levels of child nodes under the root node. Among them, the number of levels of the child nodes is the number of candidate chemicals included in the first row, and the candidate chemical with a higher occurrence frequency is the parent node of the candidate chemical with a lower occurrence frequency. Set the count of the candidate chemicals for each level of child nodes to 1; Traverse the other rows in the compound presence / absence matrix, arrange them in descending order of the occurrence frequency of the candidate chemicals, traverse each candidate chemical in the sorted row. If the i-th candidate chemical in the row is the same as the candidate chemical of the i-th child node under the root node, increment the count of this child node by 1. If they are different, starting from the (i - 1)-th child node under the root node, create a child node for the i-th candidate chemical under this (i - 1)-th child node, set the count of the candidate chemical of the newly created child node to 1, and under the newly created child node, successively construct multiple levels of child nodes for the candidate chemicals after the i-th candidate chemical in the row; Select candidate frequent chemicals from the multiple levels of child nodes, locate the positions of the candidate frequent chemicals in the multiple levels of child nodes, perform root node tracing for each located position to obtain the child node chain corresponding to each position, obtain the common chemicals included in each child node chain, accumulate the counts of the common chemicals included in each child node chain to obtain a frequent itemset containing the counts of the common chemicals. If the count of the common chemicals exceeds a pre-set count threshold, determine the frequent itemset corresponding to this count of the common chemicals as a high-order frequent itemset.

5. The method for obtaining a general chemical combination for mixture toxicity assessment according to any one of claims 1 to 4, characterized in that, Based on the first frequent itemset of chemicals and the successively obtained high-order frequent itemsets, obtaining a general chemical combination for performing mixture toxicity assessment includes: From the successively obtained high-order frequent itemsets, obtain the high-order frequent itemset containing the largest number of chemicals. Based on the high-order frequent itemset containing the largest number of chemicals, construct a first set, and construct a second set based on the remaining frequent itemsets other than the first set. Among them, the largest number of chemicals is n; From the second set, extract all candidate frequent itemsets with the number of chemicals being n - 1. For each candidate frequent itemset, if this candidate frequent itemset is a subset of any frequent itemset in the first set, remove this candidate frequent itemset from the second set. If not, merge this candidate frequent itemset with the first set and update the first set; Traverse all candidate frequent itemsets in the second set with the number of chemicals less than n - 1. For each candidate frequent itemset, if this candidate frequent itemset is a subset of any frequent itemset in the first set, remove this candidate frequent itemset from the second set. If not, merge this candidate frequent itemset with the updated first set; Obtain the finally updated first set to obtain the general chemical combination for performing mixture toxicity assessment.

6. The method for obtaining a universal chemical combination for mixture toxicity assessment according to any one of claims 1 to 4, characterized in that, Based on the concentration of the target chemical in the compound detection matrix and the analytical detection limit mapped by the target chemical, converting the compound detection matrix into a compound presence / absence matrix includes: Traverse the target chemical concentration corresponding to each chemical in the compound detection matrix, and obtain the analytical detection limit mapped by this chemical from the mapping relationship. If the target chemical concentration is greater than or equal to the analytical detection limit, update the target chemical concentration corresponding to this chemical to 1; otherwise, update the target chemical concentration corresponding to this chemical to 0.

7. The method for obtaining a general chemical combination for mixture toxicity assessment and risk evaluation according to any one of claims 1 to 4, characterized in that, The method includes: Obtain each target chemical contained in the general chemical combination; According to the concentration ranges of the target chemicals present in the target environment, for each chemical combination in the general chemical combination, configure a reagent for mixture toxicity assessment based on the concentration ranges of the chemicals contained in this chemical combination. Perform mixture toxicity assessment based on each configured reagent to obtain a mixture toxicity assessment result.

8. An apparatus for obtaining a general chemical combination for mixture toxicity assessment, characterized in that, The device for obtaining a general chemical combination for mixture toxicity assessment includes: A concentration matrix construction module, which is used to count the total number of chemicals detected at each sampling and detection point in the target environment. For each sampling and detection point, construct a chemical detection matrix for this sampling and detection point based on the chemical concentration detected at this sampling and detection point and the total number of chemicals, and construct a compound detection matrix for the target environment based on the chemical detection matrices of each sampling and detection point. A presence / absence matrix conversion module, which is used to query the pre-set mapping relationship between chemicals and analytical detection limits, and convert the compound detection matrix into a compound presence / absence matrix based on the target chemical concentration in the compound detection matrix and the analytical detection limit mapped by this target chemical. A low-order frequent item set construction module, which is used to construct a first chemical frequent item set for each candidate chemical in the compound presence / absence matrix based on the occurrence frequency of this candidate chemical in the compound presence / absence matrix and a pre-set first frequency threshold. A high-order frequent item set construction module, which is used to optimize the first chemical frequent item set from low-order chemical combinations to high-order chemical combinations based on a pre-set item set optimization strategy, and sequentially obtain high-order frequent item sets. A chemical combination acquisition module, which is used to obtain a general chemical combination for mixture toxicity assessment based on the first chemical frequent item set and the sequentially obtained high-order frequent item sets.

9. A storage medium, characterized in that, A program or instruction is stored on a storage medium, and when the program or instruction is run by a processor, it implements the steps of the method for obtaining a general chemical combination for mixture toxicity assessment according to any one of claims 1 to 7.

10. An electronic device, comprising a memory, a processor, and a computer program stored on the memory and executable on the processor, characterized in that, When the processor executes the program, it implements the steps of the method for obtaining a general chemical combination for mixture toxicity assessment according to any one of claims 1 to 7.

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