Method, device and equipment for pushing payment information of infrastructure project
By acquiring and processing the character encoding of payment information for infrastructure projects and generating verification hash values, and combining this with the LSTM algorithm to calculate risk coefficients, the problem of poor information transmission and payment delays caused by data silos in power grid infrastructure projects has been solved, enabling accurate delivery and real-time monitoring of payment information.
Patent Information
- Application Number
- CN202510878581.7
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-06-27
- Publication Date
- 2025-10-28
AI Technical Summary
In power grid infrastructure projects, the existing wage payment system suffers from data silos, which leads to frequent obstructions in information transmission, making it difficult to achieve real-time monitoring and accurate payments, and lacking effective supervision methods.
By obtaining the target construction unit's payment information and payment system identifier, determining the character encoding, processing it into a standard binary string, generating a verification hash value, and sending it to the contractor's payment system to ensure data format uniformity and accuracy, the LSTM algorithm is used to calculate the risk coefficient for payment information push.
It enables precise interpretation of data across different systems, ensures the accuracy of payment information, supports real-time monitoring and early warning, solves the data silo problem, and improves the accuracy of wage payments and the efficiency of monitoring.
Smart Images
Figure CN120856768A_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the field of data transmission technology, and in particular to a method, apparatus and equipment for pushing payment information for infrastructure projects. Background Technology
[0002] Currently, power grid infrastructure projects involve multiple stakeholders, resulting in a lengthy wage payment chain. Information transmission is frequently hampered at each level, from the general contractor to the subcontractors. This not only leads to frequent wage calculation discrepancies and payment delays but also hinders the establishment of effective oversight mechanisms. For example, due to a lack of real-time and accurate data sharing, construction companies struggle to precisely control wage payment progress, and labor supervision departments lack real-time and effective oversight tools.
[0003] Furthermore, existing wage payment supervision methods mostly rely on periodic manual checks, which cannot achieve real-time monitoring and make it difficult to detect potential wage payment risks in a timely manner. Meanwhile, with the rapid development of digital technology, many wage settlement systems have emerged, but these systems suffer from data silos. That is, although data is stored in one system, when this data is sent to another system, it may result in unrecognized data or calculation errors. For example, data B in system A indicates that funds have been paid, but after data B is sent to system C, system C may read data B that indicates it has not paid, or it may be unable to read the result at all, easily leading to errors.
[0004] Therefore, there is an urgent need for a more accurate way to push payment information, avoid data silos between systems, and achieve accurate data interpretation. Summary of the Invention
[0005] This invention provides a method, apparatus, and device for pushing payment information for infrastructure projects, in order to solve the problem of data misinterpretation that easily occurs when data is transmitted between different systems, resolve data silos between different systems, and achieve accurate data interpretation.
[0006] In a first aspect, embodiments of the present invention provide a method for pushing payment information for infrastructure projects, including:
[0007] Obtain the target construction company's payment information and the identifier of the target construction company's payment system.
[0008] Based on the identifier of the payment system, determine the character encoding corresponding to the payment information.
[0009] The payment information is processed based on character encoding to obtain the standard string corresponding to the payment information; the standard string corresponding to the payment information is a binary string.
[0010] Generate a verification hash value based on the standard string corresponding to the payment information.
[0011] The standard string corresponding to the payment information and the verification hash value are sent to the contractor's payment system at the same time, so that the contractor's payment system can understand the meaning of the target construction unit's payment information based on the standard string corresponding to the payment information and the verification hash value.
[0012] In one possible implementation, obtaining the target construction unit's payment information includes:
[0013] Obtain the target construction unit's historical wage payment records, fund account information, business volume change data, and employee attendance records.
[0014] Based on historical payroll records, fund account information, business volume change data, and employee attendance records, multiple risk coefficients for historical payroll payments are calculated.
[0015] Based on multiple risk coefficients, the payment information of the target construction unit is obtained by calculating using the LSTM algorithm.
[0016] In one possible implementation, multiple risk coefficients for historical payroll payments are calculated based on historical payroll payment records, fund account information, business volume change data, and employee attendance records, including:
[0017] Based on historical wage payment records, multiple first-risk components are calculated.
[0018] Based on data on changes in business volume, multiple secondary risk components are calculated.
[0019] Based on fund account information and employee attendance records, multiple third risk components are calculated.
[0020] Multiple risk coefficients are calculated based on multiple first risk components, multiple second risk components, and multiple third risk components.
[0021] In one possible implementation, based on historical wage payment records, multiple first-risk components are calculated, including:
[0022] Get the timestamp of each historical salary payment record.
[0023] Based on the date in the timestamp of each historical wage payment record, each historical wage payment record is classified to obtain multiple datasets.
[0024] Based on the dataset corresponding to each historical wage payment record, the first risk component corresponding to each historical wage payment record is obtained; wherein, the first risk component corresponding to each dataset is different.
[0025] In one possible implementation, multiple second risk components are calculated based on business volume variation data, including:
[0026] Calculate the average of each business change data point.
[0027] Calculate the difference between each business change data point and the mean of the business change data points, and record it as the first difference.
[0028] Calculate the ratio of the first difference to the mean of the business change data to obtain the second risk component corresponding to each business change data.
[0029] In one possible implementation, multiple third-party risk components are calculated based on fund account information and employee attendance records, including:
[0030] The wages due are calculated based on employee attendance records.
[0031] The ratio of wages due to be paid to funds account information is recorded as the third risk component.
[0032] In one possible implementation, multiple risk coefficients are calculated based on multiple first risk components, multiple second risk components, and multiple third risk components, including:
[0033] The product of the first risk component and the first preset weight is denoted as the first result.
[0034] The product of the second risk component and the second preset weight is denoted as the second result.
[0035] The product of the third risk component and the third preset weight is denoted as the third result.
[0036] The sum of the first, second, and third results is denoted as the risk coefficient.
[0037] In one possible implementation, payment information for the target construction unit is obtained by calculating multiple risk coefficients using the LSTM algorithm, including:
[0038] Multiple risk coefficients are divided into multiple risk coefficient sequences.
[0039] For any given risk coefficient sequence, multiple calculation results are obtained by using the LSTM algorithm based on that risk coefficient sequence.
[0040] The average of multiple calculation results will be used as the payment information for the target construction unit.
[0041] Secondly, embodiments of the present invention provide a device for pushing payment information for infrastructure projects, comprising:
[0042] The first processing module is used to obtain the target construction unit's payment information and the identifier of the target construction unit's payment system.
[0043] The second processing module is used to determine the character encoding corresponding to the payment information based on the identifier of the payment system.
[0044] The third processing module is used to process the payment information based on character encoding to obtain the standard string corresponding to the payment information; wherein, the standard string corresponding to the payment information is a binary string.
[0045] The fourth processing module is used to generate a verification hash value based on the standard string corresponding to the payment information.
[0046] The fifth processing module is used to simultaneously send the standard string and verification hash value corresponding to the payment information to the contractor's payment system, so that the contractor's payment system can obtain the meaning expressed by the target construction unit's payment information based on the standard string and verification hash value corresponding to the payment information.
[0047] Thirdly, embodiments of the present invention provide an electronic device, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the method described in the first aspect or any possible implementation thereof.
[0048] In this embodiment of the invention, the character encoding corresponding to the payment information is determined by the identifier of the target construction unit's payment system. Then, the payment information is processed using this character encoding, transforming it into a standard binary string. This unifies the data format pushed to the contractor's payment system, enabling the contractor's payment system to directly convert the received data to obtain accurate payment information from the target construction unit. This process also includes generating a verification hash value based on the standard string and sending this hash value to the contractor's payment system, further ensuring the accuracy of the target construction unit's payment information (the data is considered correct only if the verification hash value corresponds to the target construction unit's payment information). Therefore, the contractor's payment system can accurately interpret the data and issue alerts or prompts based on the intended meaning of the target construction unit's payment information, resolving data silos between different systems and achieving supervision of wage payments. Attached Figure Description
[0049] Figure 1 This is a flowchart illustrating the implementation of the infrastructure project payment information push method provided in this embodiment of the invention.
[0050] Figure 2 This is a schematic diagram of the infrastructure project payment information push device provided in an embodiment of the present invention;
[0051] Figure 3 This is a schematic diagram of an electronic device provided in an embodiment of the present invention. Detailed Implementation
[0052] The embodiments of the present invention will now be described in detail with reference to the accompanying drawings.
[0053] See Figure 1 The document illustrates a flowchart of the implementation of the infrastructure project payment information push method provided in an embodiment of the present invention, which is described in detail below:
[0054] Step 101: Obtain the payment information of the target construction unit and the identifier of the target construction unit's payment system.
[0055] In one possible implementation, obtaining the target construction unit's payment information includes:
[0056] Obtain the target construction unit's historical wage payment records, fund account information, business volume change data, and employee attendance records.
[0057] Based on historical payroll records, fund account information, business volume change data, and employee attendance records, multiple risk coefficients for historical payroll payments are calculated.
[0058] Based on multiple risk coefficients, the payment information of the target construction unit is obtained by calculating using the LSTM algorithm.
[0059] In one possible implementation, multiple risk coefficients for historical payroll payments are calculated based on historical payroll payment records, fund account information, business volume change data, and employee attendance records, including:
[0060] Based on historical wage payment records, multiple first-risk components are calculated.
[0061] Based on data on changes in business volume, multiple secondary risk components are calculated.
[0062] Based on fund account information and employee attendance records, multiple third risk components are calculated.
[0063] Multiple risk coefficients are calculated based on multiple first risk components, multiple second risk components, and multiple third risk components.
[0064] For example, by comprehensively calculating the risk coefficient based on multiple perspectives such as historical wage payment records, fund account information, business volume change data, and employee attendance records, the risk of the target construction unit's work arrears can be calculated more accurately from multiple angles.
[0065] In one possible implementation, based on historical wage payment records, multiple first-risk components are calculated, including:
[0066] Get the timestamp of each historical salary payment record.
[0067] Based on the date in the timestamp of each historical wage payment record, each historical wage payment record is classified to obtain multiple datasets.
[0068] Based on the dataset corresponding to each historical wage payment record, the first risk component corresponding to each historical wage payment record is obtained; wherein, the first risk component corresponding to each dataset is different.
[0069] For example, based on the date in the timestamp of each historical payroll record, each historical payroll record is categorized to obtain multiple datasets, which may include:
[0070] The difference between the date in the timestamp of each historical wage payment record and the preset date is recorded as the date difference;
[0071] The set of historical wage payment records with a date difference of 0 is used as the first dataset; the first risk component corresponding to the first dataset can be 0.
[0072] The set of historical wage payment records with a date difference greater than 0 and less than or equal to 3 is used as the second dataset; the first risk component corresponding to the second dataset can be 0.5.
[0073] The set of historical wage payment records with a date difference greater than 3 is used as the third dataset; the first risk component corresponding to the third dataset can be 1.
[0074] For example, when the target construction unit's wage payment records are more irregular (the dates in the timestamps of historical wage payment records change frequently), it can be assumed that the target construction unit's funds fluctuate significantly, and there is a risk of wage arrears due to frequent shortages.
[0075] In one possible implementation, multiple second risk components are calculated based on business volume variation data, including:
[0076] Calculate the average of each business change data point.
[0077] Calculate the difference between each business change data point and the mean of the business change data points, and record it as the first difference.
[0078] Calculate the ratio of the first difference to the mean of the business change data to obtain the second risk component corresponding to each business change data.
[0079] For example, the larger the ratio of the first difference to the average of the business change data, the more drastic the current business changes of the target construction unit are, and there may be a risk that it will be unable to pay wages. Therefore, in order to ensure the accuracy of the calculation of the target construction unit's payment information, the ratio of the first difference to the average of the business change data is used as the second risk component.
[0080] In one possible implementation, multiple third-party risk components are calculated based on fund account information and employee attendance records, including:
[0081] The wages due are calculated based on employee attendance records.
[0082] The ratio of wages due to be paid to funds account information is recorded as the third risk component.
[0083] For example, in order to ensure the accuracy of the calculation of the target construction unit's payment information, the impact of the target construction unit's capital account information and employee attendance records is considered. The higher the ratio of wages to be paid to capital account information, the less funds are left in the capital account information. When the target construction unit is unable to pay wages for a long time, a large number of employees will strike, and there will be no employee attendance records.
[0084] In one possible implementation, multiple risk coefficients are calculated based on multiple first risk components, multiple second risk components, and multiple third risk components, including:
[0085] The product of the first risk component and the first preset weight is denoted as the first result.
[0086] The product of the second risk component and the second preset weight is denoted as the second result.
[0087] The product of the third risk component and the third preset weight is denoted as the third result.
[0088] The sum of the first, second, and third results is denoted as the risk coefficient.
[0089] For example, the first preset weight can be greater than the second preset weight, the second preset weight can be greater than the third preset weight, and the sum of the first preset weight, the second preset weight and the third preset weight is equal to 1.
[0090] In one possible implementation, payment information for the target construction unit is obtained by calculating multiple risk coefficients using the LSTM algorithm, including:
[0091] Multiple risk coefficients are divided into multiple risk coefficient sequences.
[0092] For any given risk coefficient sequence, multiple calculation results are obtained by using the LSTM algorithm based on that risk coefficient sequence.
[0093] The average of multiple calculation results will be used as the payment information for the target construction unit.
[0094] For example, the LSTM algorithm can fully capture the trend features in the time series. Therefore, in order to ensure the accuracy of the calculated payment information of the target construction unit, the calculated multiple risk coefficients can be divided into multiple sequences, and the LSTM algorithm can be used to calculate the risk coefficients of the target construction unit at this time. The average of the multiple risk coefficients of the target construction unit at this time is used as the payment information of the target construction unit.
[0095] Step 102: Determine the character encoding corresponding to the payment information based on the identifier of the payment system.
[0096] For example, each payment system has a unique identifier, and different payment systems share a common character encoding. For instance, payment system A might use UTF-8, GB2312, or GB18030. Different character encodings result in different meanings for the data.
[0097] Step 103: Process the payment information based on character encoding to obtain the standard string corresponding to the payment information; wherein, the standard string corresponding to the payment information is a binary string.
[0098] For example, in order to standardize the format of transmitted data, payment information needs to be processed according to character encoding, converting it into a corresponding standard string (binary string). This provides a unified standard for subsequent data transmission to the contractor's payment system, facilitating data verification and conversion within the contractor's payment system.
[0099] Step 104: Generate a verification hash value based on the standard string corresponding to the payment information.
[0100] For example, in order to ensure the accuracy of transmitted data, a verification hash value needs to be generated based on the content sent, so that the contractor's payment system can verify the data and receive the retransmitted data when the verification fails.
[0101] Step 105: The standard string and verification hash value corresponding to the payment information are sent to the contractor's payment system at the same time, so that the contractor's payment system can obtain the meaning of the target construction unit's payment information based on the standard string and verification hash value corresponding to the payment information.
[0102] For example, if the system receives feedback information from the contractor's payment system but does not receive feedback information from the contractor's payment system within a preset time, it resends the standard string and verification hash value corresponding to the payment information to the contractor's payment system until feedback information from the contractor's payment system is received within the preset time.
[0103] For example, when the contractor's payment system receives the standard string and the verification hash value, it will first perform a verification. It will generate a new hash value from the standard string and compare it with the verification hash value. If they are the same, it is considered that the standard string has been received accurately. At this time, the contractor's payment system sends feedback information to the target construction unit's payment system.
[0104] After the contractor's payment system confirms the accuracy of the standard string, it will also perform data conversion to convert the standard string into data that the contractor's payment system can recognize (simply put, converting the binary string into a string with the character encoding corresponding to the contractor's payment system). In this way, the contractor's payment system can accurately obtain the meaning expressed by the payment information of the target construction unit.
[0105] Specifically, the target construction company's payment information can be a specific data point, which represents the risk of the target construction company defaulting on wages. The higher the value, the greater the risk.
[0106] Once an anomaly is detected (when the value exceeds a fixed threshold), the contractor's payment system automatically invokes SMS sending interfaces, system message push programs, and email services to send warning messages to the contractor's staff, alerting them to a high risk of wage arrears from the target construction unit. The warning message may include details such as the target construction unit's bank account balance and the number of days overdue for wage payments, and provides links to relevant data reports for easy access to detailed information. Simultaneously, a warning log is generated in the contractor's payment system backend, recording the warning time, triggering reason, and the recipient (target construction unit) of the notification.
[0107] The aforementioned method for pushing payment information for infrastructure projects identifies the character code corresponding to the payment information through the identifier of the target construction unit's payment system. The payment information is then processed using this character code, transforming it into a standard binary string. This standardizes the data format pushed to the contractor's payment system, enabling it to directly convert the received data to obtain accurate payment information from the target construction unit. This process also includes generating a verification hash value based on the standard string and sending it to the contractor's payment system, further ensuring the accuracy of the target construction unit's payment information (the data is considered correct only if the verification hash value corresponds to the target construction unit's payment information). Therefore, the contractor's payment system can accurately interpret the data and issue alerts or prompts based on the intended meaning of the target construction unit's payment information, thus resolving data silos between different systems and enabling supervision of wage payments.
[0108] It should be understood that the sequence number of each step in the above embodiments does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present invention.
[0109] The following are device embodiments of the present invention. For details not described in detail, please refer to the corresponding method embodiments described above.
[0110] Figure 2 A schematic diagram of the infrastructure project payment information push device provided in an embodiment of the present invention is shown. For ease of explanation, only the parts related to the embodiment of the present invention are shown, and are described in detail below:
[0111] like Figure 2 As shown, the infrastructure project payment information push device includes:
[0112] The first processing module 201 is used to obtain the payment information of the target construction unit and the identifier of the target construction unit's payment system.
[0113] The second processing module 202 is used to determine the character encoding corresponding to the payment information based on the identifier of the payment system.
[0114] The third processing module 203 is used to process the payment information based on character encoding to obtain the standard string corresponding to the payment information; wherein, the standard string corresponding to the payment information is a binary string.
[0115] The fourth processing module 204 is used to generate a verification hash value based on the standard string corresponding to the payment information.
[0116] The fifth processing module 205 is used to simultaneously send the standard string and verification hash value corresponding to the payment information to the contractor's payment system, so that the contractor's payment system can obtain the meaning expressed by the target construction unit's payment information based on the standard string and verification hash value corresponding to the payment information.
[0117] In one possible implementation, the first processing module 201 can be used for:
[0118] Obtain the target construction unit's historical wage payment records, fund account information, business volume change data, and employee attendance records.
[0119] Based on historical payroll records, fund account information, business volume change data, and employee attendance records, multiple risk coefficients for historical payroll payments are calculated.
[0120] Based on multiple risk coefficients, the payment information of the target construction unit is obtained by calculating using the LSTM algorithm.
[0121] In one possible implementation, the first processing module 201 can be used for:
[0122] Based on historical wage payment records, multiple first-risk components are calculated.
[0123] Based on data on changes in business volume, multiple secondary risk components are calculated.
[0124] Based on fund account information and employee attendance records, multiple third risk components are calculated.
[0125] Multiple risk coefficients are calculated based on multiple first risk components, multiple second risk components, and multiple third risk components.
[0126] In one possible implementation, the first processing module 201 can be used for:
[0127] Get the timestamp of each historical salary payment record.
[0128] Based on the date in the timestamp of each historical wage payment record, each historical wage payment record is classified to obtain multiple datasets.
[0129] Based on the dataset corresponding to each historical wage payment record, the first risk component corresponding to each historical wage payment record is obtained; wherein, the first risk component corresponding to each dataset is different.
[0130] In one possible implementation, the first processing module 201 can be used for:
[0131] Calculate the average of each business change data point.
[0132] Calculate the difference between each business change data point and the mean of the business change data points, and record it as the first difference.
[0133] Calculate the ratio of the first difference to the mean of the business change data to obtain the second risk component corresponding to each business change data.
[0134] In one possible implementation, the first processing module 201 can be used for:
[0135] The wages due are calculated based on employee attendance records.
[0136] The ratio of wages due to be paid to funds account information is recorded as the third risk component.
[0137] In one possible implementation, the first processing module 201 can be used for:
[0138] The product of the first risk component and the first preset weight is denoted as the first result.
[0139] The product of the second risk component and the second preset weight is denoted as the second result.
[0140] The product of the third risk component and the third preset weight is denoted as the third result.
[0141] The sum of the first, second, and third results is denoted as the risk coefficient.
[0142] In one possible implementation, the first processing module 201 can be used for:
[0143] Multiple risk coefficients are divided into multiple risk coefficient sequences.
[0144] For any given risk coefficient sequence, multiple calculation results are obtained by using the LSTM algorithm based on that risk coefficient sequence.
[0145] The average of multiple calculation results will be used as the payment information for the target construction unit.
[0146] Figure 3 This is a schematic diagram of an electronic device provided in an embodiment of the present invention. Figure 3 As shown, the electronic device 3 of this embodiment includes a processor 30 and a memory 31. The memory 31 stores a computer program 32. When the processor 30 executes the computer program 32, it implements the steps in the various method embodiments described above. Alternatively, when the processor 30 executes the computer program 32, it implements the functions of each module / unit in the various device embodiments described above.
[0147] For example, computer program 32 may be divided into one or more modules / units, which are stored in memory 31 and executed by processor 30 to complete the present invention. The one or more modules / units may be a series of computer program instruction segments capable of performing a specific function, which describe the execution process of computer program 32 in electronic device 3.
[0148] Electronic device 3 may include, but is not limited to, processor 30 and memory 31. Those skilled in the art will understand that... Figure 3 This is merely an example of electronic device 3 and does not constitute a limitation on electronic device 3. It may include more or fewer components than shown, or combine certain components, or different components. For example, electronic device 3 may also include input / output devices, network access devices, buses, etc.
[0149] For the sake of simplicity and clarity, only the above-described functional modules / units are used as examples. In practical applications, the functions described above can be assigned to different functional modules / units as needed. These modules / units can be implemented in hardware, software, or a combination of both.
[0150] In the above embodiments, the descriptions of each embodiment have their own emphasis. Parts not detailed or described in a particular embodiment can be referred to in the relevant descriptions of other embodiments. Unless otherwise specified or in conflict with logic, the terminology and / or descriptions between different embodiments are consistent and can be referenced interchangeably. Technical features in different embodiments can be combined to form new embodiments based on their inherent logical relationships.
[0151] The above-described embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit it. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention, and should all be included within the protection scope of the present invention.
Claims
1. A method for pushing payment information for infrastructure projects, characterized in that, include: Obtain the target construction company's payment information and the identifier of the target construction company's payment system; Based on the identifier of the payment system, the character encoding corresponding to the payment information is determined; The payment information is processed based on the character encoding to obtain a standard string corresponding to the payment information; wherein, the standard string corresponding to the payment information is a binary string; Generate a verification hash value based on the standard string corresponding to the payment information; The standard string corresponding to the payment information and the verification hash value are sent simultaneously to the contractor's payment system, so that the contractor's payment system can obtain the meaning expressed by the target construction unit's payment information based on the standard string corresponding to the payment information and the verification hash value.
2. The method for pushing payment information for infrastructure projects according to claim 1, characterized in that, The acquisition of the target construction unit's payment information includes: Obtain the target construction company's historical wage payment records, fund account information, business volume change data, and employee attendance records; Based on the historical payroll records, fund account information, business volume change data, and employee attendance records, multiple risk coefficients for historical payroll payments are calculated. Based on the aforementioned multiple risk coefficients, the payment information for the target construction unit is obtained through calculation using the LSTM algorithm.
3. The method for pushing payment information for infrastructure projects according to claim 2, characterized in that, The calculation of multiple risk coefficients for historical wage payments based on the historical wage payment records, fund account information, business volume change data, and employee attendance records includes: Based on the historical wage payment records, multiple first risk components are calculated; Based on the aforementioned business volume change data, multiple second risk components are calculated; Based on the fund account information and the employee attendance records, multiple third risk components are calculated; Based on the multiple first risk components, the multiple second risk components, and the multiple third risk components, multiple risk coefficients are calculated.
4. The method for pushing payment information for infrastructure projects according to claim 3, characterized in that, The calculation of multiple first risk components based on the historical wage payment records includes: Obtain the timestamp of each of the aforementioned historical wage payment records; Based on the date in the timestamp of each historical wage payment record, each historical wage payment record is classified to obtain multiple datasets; Based on the dataset corresponding to each historical wage payment record, the first risk component corresponding to each historical wage payment record is obtained; wherein, the first risk component corresponding to each dataset is different.
5. The method for pushing payment information for infrastructure projects according to claim 3, characterized in that, The calculation of multiple second risk components based on the business volume change data includes: Calculate the average value of the business change data based on each of the aforementioned business change data; Calculate the difference between each business change data point and the mean of the business change data points, and record it as the first difference; Calculate the ratio of the first difference to the mean of the business change data to obtain the second risk component corresponding to each business change data.
6. The method for pushing payment information for infrastructure projects according to claim 3, characterized in that, The calculation of multiple third-party risk components based on the fund account information and the employee attendance records includes: Based on the employee attendance records, the wages to be paid are calculated. The ratio of the wages to be paid to the information in the fund account is recorded as the third risk component.
7. The method for pushing payment information for infrastructure projects according to claim 3, characterized in that, Based on the plurality of first risk components, the plurality of second risk components, and the plurality of third risk components, a plurality of risk coefficients are calculated, including: The product of the first risk component and the first preset weight is recorded as the first result; The product of the second risk component and the second preset weight is recorded as the second result; The product of the third risk component and the third preset weight is denoted as the third result; The sum of the first result, the second result, and the third result is denoted as the risk coefficient.
8. The method for pushing payment information for infrastructure projects according to claim 2, characterized in that, The payment information for the target construction unit is obtained by calculating using the LSTM algorithm based on the multiple risk coefficients, including: The multiple risk coefficients are divided into multiple risk coefficient sequences; For any given risk coefficient sequence, multiple calculation results are obtained by using the LSTM algorithm based on that risk coefficient sequence. The average of the multiple calculation results is used as the payment information for the target construction unit.
9. A payment information push device for infrastructure projects, characterized in that, include: The first processing module is used to obtain the payment information of the target construction unit and the identifier of the target construction unit's payment system; The second processing module is used to determine the character encoding corresponding to the payment information based on the identifier of the payment system; The third processing module is used to process the payment information based on the character encoding to obtain a standard string corresponding to the payment information; wherein, the standard string corresponding to the payment information is a binary string; The fourth processing module is used to generate a verification hash value based on the standard string corresponding to the payment information; The fifth processing module is used to simultaneously send the standard string corresponding to the payment information and the verification hash value to the contractor's payment system, so that the contractor's payment system can obtain the meaning expressed by the target construction unit's payment information based on the standard string corresponding to the payment information and the verification hash value.
10. An electronic device, characterized in that, It includes a memory and a processor, the memory storing a computer program, and the processor executing the computer program to implement the method as described in any one of claims 1 to 8.