Intelligent Generation Method for Enterprise Final Settlement Report

Abstract

The present invention provides an intelligent generation method for enterprise final settlement reports, which relates to data processing technology. The server receives the initial final settlement data input by the enterprise, and based on the customized information, grabs the financial and tax information in the final settlement data according to the information dimension, and after obtaining the financial and tax information of different information dimensions, groups and inputs it into a topology calculator with a preset value; different operation units of the topology calculator perform decomposition operations on the financial and tax information according to the preset operation topology structure to obtain the corresponding first financial and tax sub-information; if it is determined that there is a first node connected to the graphic rendering generation node in the operation topology structure, after the first node has the first financial and tax sub-information, it is input to the graphic rendering generation node; the graphic rendering generation node determines the second financial and tax sub-information corresponding to the first financial and tax sub-information based on the historical interaction data with the first node, and generates a final settlement report based on the second financial and tax sub-information and the report generation habits of each graphic rendering generation node.

Description

Technical Field

[0001] The present invention relates to data technology, and in particular to an intelligent generation method for enterprise final settlement and payment reports. Background Art

[0002] In today's digital information management system, the importance of the enterprise year-end final settlement and payment work is self-evident. The final settlement and payment is for the enterprise to summarize and audit the financial data of the previous year in order to submit an accurate tax report to the tax authorities.

[0003] However, the traditional process of generating final settlement and payment reports often relies on manual input and data classification, which is not only time-consuming and laborious, but also prone to inaccurate final settlement due to human errors. With the increasing demand for enterprise informatization, there is an urgent need for a solution that is automated, intelligent and can quickly generate accurate final settlement and payment reports.

[0004] Therefore, how to intelligently generate corresponding final settlement and payment reports according to the actual financial and tax situations of each enterprise, and improve the efficiency and accuracy of the final settlement and payment work has become an urgent problem to be solved. Summary of the Invention

[0005] An embodiment of the present invention provides an intelligent generation method for enterprise final settlement and payment reports, which can intelligently generate corresponding final settlement and payment reports according to the actual financial and tax situations of each enterprise, and improve the efficiency and accuracy of the final settlement and payment work.

[0006] In a first aspect of an embodiment of the present invention, an intelligent generation method for enterprise final settlement and payment reports is provided, including:

[0007] The server grabs the financial and tax information in the final settlement and payment data according to the customized information by information dimension, and after obtaining the financial and tax information of different information dimensions, groups and inputs it into a topological operator with a preset value;

[0008] Different operation units of the topological operator perform decomposition operations on the financial and tax information according to the operation topological structure with a preset value to obtain corresponding first financial and tax sub-information, and the operation topological structure at least includes an input node, an operation node and an output node;

[0009] If it is determined that there is a first node connected to the graphic rendering generation node in the operation topological structure, after the first node has the first financial and tax sub-information, it is input to the graphic rendering generation node;

[0010] The graphic rendering generation node determines the second financial and tax sub-information corresponding to the first financial and tax sub-information based on the historical interaction data with the first node, and generates a final settlement and payment report based on the second financial and tax sub-information and the report generation habits of each graphic rendering generation node.

[0011] Optionally, in a possible implementation of the first aspect, the server grabs the financial and tax information in the final settlement data according to the information dimension based on the customization information, and after obtaining the financial and tax information of different information dimensions, groups and inputs it into a topological operator with a preset value, including:

[0012] The server receives the final settlement data in the form of an initial table file input by the enterprise, and the final settlement data in the form of the table file includes at least the information dimension and the information value;

[0013] The server receives at least one final settlement target through the customization interaction module, and each final settlement target corresponds to the information value of at least one information dimension;

[0014] The server grabs the financial and tax information of different information dimensions from the final settlement data in the form of a table file based on the information dimensions corresponding to all final settlement targets;

[0015] The server adjusts the topological operator with a preset value based on the final settlement target to obtain the operation link of the topological operator during this final settlement.

[0016] Optionally, in a possible implementation of the first aspect, the server adjusts the topological operator with a preset value based on the final settlement target to obtain the operation link of the topological operator during this final settlement, including:

[0017] Determine the output node corresponding to the final settlement target in the topological operator as the first output node;

[0018] Based on the first output node and the connection path of the first output node, perform link backtracking in the topological operator to obtain the backtracking start node and the backtracking link;

[0019] Perform summary statistics on the backtracking start node and the backtracking link to obtain the operation link of the topological operator during this final settlement and the operation link table of this time, deactivate the nodes in the non-operation link, and reverse the path of the backtracking link to obtain the operation link.

[0020] Optionally, in a possible implementation of the first aspect, the performing link backtracking in the topological operator based on the first output node and the connection path of the first output node to obtain the backtracking start node and the backtracking link includes:

[0021] Take each first output node as the corresponding backtracking start node, and establish an operation link cell corresponding to each backtracking start node in the initial operation link table;

[0022] Determine the first information dimension corresponding to the final settlement target of each first output node, and determine the input node corresponding to the first information dimension as the first input node, and determine the first input node as the backtracking termination node;

[0023] Generate a corresponding backtracking link based on the backtracking start node, the backtracking termination node, and a preset backtracking strategy.

[0024] Optionally, in a possible implementation manner of the first aspect, the generating a corresponding backtracking link based on the backtracking start node, the backtracking termination node, and a preset backtracking strategy includes:

[0025] Taking the backtracking start node as the starting point, respectively determine the operation nodes and / or input nodes in the upper dimension that are directly connected and / or indirectly connected until all backtracking termination nodes are determined, and then stop the link backtracking;

[0026] Count the directly connected operation nodes and / or output nodes, and / or indirectly connected operation nodes and / or output nodes located between the backtracking start node and the backtracking termination node, and generate a backtracking link.

[0027] Optionally, in a possible implementation manner of the first aspect, different operation units of the topology operation unit decompose and operate on the fiscal and tax information according to a preset operation topology structure to obtain corresponding first fiscal and tax sub-information. The operation topology structure at least includes input nodes, operation nodes, and output nodes, including:

[0028] Traverse each operation link cell in the operation link table in sequence, determine the corresponding input nodes according to the operation links in the operation link cell, and input the corresponding fiscal and tax information based on the types of the input nodes;

[0029] Calculate based on all the nodes in the operation link and the connection relationships between the nodes to obtain the first fiscal and tax sub-information after calculation and processing by the operation nodes and / or output nodes.

[0030] Optionally, in a possible implementation manner of the first aspect, if it is determined that there is a first node connected to the graphic rendering generation node in the operation topology structure, then input it to the graphic rendering generation node after the first node has the first fiscal and tax sub-information, including:

[0031] Take all non-deactivated nodes in the operation link of the operation topology structure as the first nodes;

[0032] Determine the rendering quantity of the graphic rendering generation nodes connected by each first node;

[0033] If the rendering quantity is 1, then input it to the graphic rendering generation node after the first node has the first fiscal and tax sub-information;

[0034] If the number of renderings is multiple, corresponding graphic rendering generation nodes are determined based on the current final settlement target, and the first fiscal and tax sub-information is input. Each final settlement target has a preset graphic rendering generation node.

[0035] Optionally, in a possible implementation manner of the first aspect, the graphic rendering generation node determines the second fiscal and tax sub-information corresponding to the first fiscal and tax sub-information based on the historical interaction data with the first node, and generates a final settlement report based on the second fiscal and tax sub-information and the report generation habits of each graphic rendering generation node, including:

[0036] The graphic rendering generation node grabs the historical interaction data of the first node based on the enterprise label of the enterprise. The historical interaction data includes the historical time and historical fiscal and tax sub-information of each previous generation of the first fiscal and tax sub-information.

[0037] If the graphic rendering generation node determines that the enterprise does not actively configure the report time dimension this time, it obtains the habitual time dimension based on the report generation habits of the previous graphic rendering generation node.

[0038] If the graphic rendering generation node determines that the enterprise actively configures the report time dimension this time, it extracts the corresponding active time dimension.

[0039] Based on the habitual time dimension or the active time dimension, the historical fiscal and tax sub-information at the historical time is screened in the database to obtain the second fiscal and tax sub-information, the graphic habits of each graphic rendering generation node are obtained, and a final settlement report is generated based on the graphic habits and the second fiscal and tax sub-information.

[0040] Optionally, in a possible implementation manner of the first aspect, if the graphic rendering generation node determines that the enterprise does not actively configure the report time dimension this time, it obtains the habitual time dimension based on the report generation habits of the previous graphic rendering generation node, including:

[0041] Obtain the historical time dimensions of all reports of all previous graphic rendering generation nodes, take the average of all historical time dimensions and round up to obtain the habitual time dimension.

[0042] Optionally, in a possible implementation manner of the first aspect, the step of screening the historical fiscal and tax sub-information at the historical time in the database based on the habitual time dimension or the active time dimension to obtain the second fiscal and tax sub-information, obtaining the graphic habits of each graphic rendering generation node, and generating a final settlement report based on the graphic habits and the second fiscal and tax sub-information includes:

[0043] Based on the habitual time dimension or the active time dimension, historical fiscal and tax sub-information at a historical moment is determined, and the second fiscal and tax sub-information is screened out. The habitual time dimension or the active time dimension respectively includes corresponding time periods.

[0044] Obtain the graphic habits of each graphic rendering generation node, and obtain the corresponding graphic templates based on the graphic habits. Each graphic habit has a preset graphic template.

[0045] The graphic rendering generation node performs fusion rendering based on the graphic template, the first fiscal and tax sub-information, and the second fiscal and tax sub-information respectively, and generates a sub-report for a corresponding graphic rendering generation node.

[0046] Combine all the sub-reports in the order of priority to generate a finalized final settlement report.

[0047] Optionally, in a possible implementation manner of the first aspect, the obtaining the graphic habits of each graphic rendering generation node, and obtaining the corresponding graphic templates based on the graphic habits. Each graphic habit has a preset graphic template, includes:

[0048] Obtain the historical time dimensions of all sub-reports of all previous graphic rendering generation nodes, count the graphic types of all the historical time dimensions, and obtain the graphic type with the largest quantity as the graphic template.

[0049] Optionally, in a possible implementation manner of the first aspect, the graphic rendering generation node performs fusion rendering based on the graphic template, the first fiscal and tax sub-information, and the second fiscal and tax sub-information respectively, and generates a sub-report for a corresponding graphic rendering generation node, includes:

[0050] The graphic rendering generation node determines the graphics to be rendered in the graphic template, and selects the corresponding slots to be rendered in the graphics to be rendered based on the first fiscal and tax sub-information and the second fiscal and tax sub-information.

[0051] Based on the sequence numbers of the slots to be rendered, the time numbers of the first fiscal and tax sub-information and the second fiscal and tax sub-information, the slots to be rendered are respectively processed corresponding to the first fiscal and tax sub-information or the second fiscal and tax sub-information.

[0052] Based on the numerical values of the first fiscal and tax sub-information or the second fiscal and tax sub-information, determine the rendering pixel points and rendering pixel values of the first fiscal and tax sub-information and the second fiscal and tax sub-information, and generate a sub-report for the graphic rendering generation node based on the rendering pixel points and the rendering pixel values.

[0053] In the fourth aspect of the present invention, a storage medium is provided. A computer program is stored in the storage medium, and when the computer program is executed by a processor, it is used to implement the methods of the first aspect and various possible designs of the first aspect of the present invention.

[0054] The beneficial effects of the present invention are as follows:

[0055] 1. The present invention can intelligently generate corresponding final settlement reports according to the actual financial and tax situations of each enterprise, improving the efficiency and accuracy of the final settlement work. The present invention can automatically capture and integrate the financial and tax data uploaded by enterprises through the server, and use a preset topology calculator for efficient operation, realizing the rapid processing and accurate calculation of financial and tax information. It can not only automatically generate the required financial and tax sub-information, but also has the ability of graphic rendering, presenting the data results intuitively, thereby enhancing the intelligent level of generating final settlement reports.

[0056] 2. The present invention receives the initial final settlement data uploaded by enterprises through the server, automatically captures and groups the data based on customized information, and then uses a topology calculator with preset values to efficiently integrate the financial and tax information in different information dimensions, realizing the full-process automation from input to output. At the same time, with the flexibility of the topology structure, the operation link can be dynamically adjusted according to the final settlement target to ensure the pertinence and efficiency of data processing, thereby significantly improving the generation speed and accuracy of the final settlement report. Among them, using the topology calculator to decompose and calculate the financial and tax information is one of the core advantages of the present invention. By traversing the operation link table, the financial and tax sub-information of the operation node and the output node are calculated in turn. During this process, the financial and tax sub-information in multiple information dimensions can be quickly generated according to the type of input node and the associated operation link. Through the optimization of the operation link and the accuracy of node calculation, it is ensured that the system can still maintain high operation ability and accurate calculation results in a complex data environment.

[0057] 3. The present invention also provides a function of generating graphic rendering, which can automatically generate a final settlement report with a highly visual effect based on historical interaction data and generation habits. The present invention can automatically select a suitable graphic template according to different final settlement targets, fuse and render the data to generate an intuitive sub-report. Finally, through the priority sorting and integration of all sub-reports, a finalized final settlement report is formed to improve the readability and comprehensibility of the report. BRIEF DESCRIPTION OF THE DRAWINGS

[0058] Figure 1 is a flowchart of an intelligent generation method for an enterprise final settlement report provided by the present invention;

[0059] Figure 2 is a schematic diagram of an operation topology structure provided by the present invention;

[0060] Figure 3 is a schematic diagram of a graphic rendering provided by the present invention. DETAILED DESCRIPTION OF THE INVENTION

[0061] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part rather than all of the embodiments of the present invention. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0062] Terms such as "first", "second", "third", "fourth", etc. (if any) in the specification, claims, and the above-mentioned accompanying drawings of the present invention are used to distinguish similar objects and do not necessarily describe a specific order or sequence. It should be understood that such data can be interchanged under appropriate circumstances so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein.

[0063] It should be understood that in various embodiments of the present invention, the magnitude of the sequence numbers of the processes does not mean the order of execution is prior or subsequent. The order of execution of each process should be determined by its function and internal logic and should not constitute any limitation to the implementation process of the embodiments of the present invention.

[0064] It should be understood that in the present invention, "including" and "having" and any variations thereof are intended to cover non-exclusive inclusion. For example, a process, method, system, product, or device that includes a series of steps or units does not necessarily limit to those steps or units clearly listed, but may include other steps or units not clearly listed or inherent to these processes, methods, products, or devices.

[0065] It should be understood that in the present invention, "a plurality of" means two or more. "And / or" is only a description of the association relationship of associated objects, indicating that there can be three relationships. For example, A and / or B can represent: A exists alone, A and B exist simultaneously, and B exists alone. The character " / " generally represents an "or" relationship between the associated objects before and after. "Including A, B, and C", "including A, B, C" means that all of A, B, and C are included. "Including A, B, or C" means including one of A, B, and C. "Including A, B, and / or C" means including any one or any two or all three of A, B, and C.

[0066] It should be understood that in the present invention, "B corresponding to A", "B corresponding to A relatively", "A corresponding to B relatively", or "B corresponding to A relatively" means that B is associated with A, and B can be determined according to A. Determining B according to A does not mean determining B only according to A. B can also be determined according to A and / or other information. The matching of A and B means that the similarity between A and B is greater than or equal to a preset threshold.

[0067] Depending on the context, as used herein, "if" can be interpreted as "when", or "while", or "in response to determining", or "in response to detecting".

[0068] The technical solution of the present invention will be described in detail below with specific embodiments. These specific embodiments can be combined with each other, and the same or similar concepts or processes may not be repeated in some embodiments.

[0069] As Figure 1 shown, the present invention provides an intelligent method for generating an enterprise final settlement and payment report, including:

[0070] S1, the server grabs the financial and tax information in the final settlement and payment data according to the information dimension based on the customization information, and after obtaining the financial and tax information of different information dimensions, groups and inputs it into a topological arithmetic unit with a preset value.

[0071] It should be noted that in the existing tax processing methods, a large part is still manually processed, and there is no comprehensive application of information technology with an electronic computer as the main body in tax work. The data information about final settlement and payment usually requires manual entry and classification of information, and the automation of data processing has not been realized. However, the present invention can automatically extract and integrate the uploaded data to facilitate subsequent calculation of the data, thereby accelerating the generation of the final settlement and payment report.

[0072] It can be understood that the server can receive the initial final settlement and payment data uploaded by the enterprise, such as an information form containing financial information, which contains various content data. Therefore, it is necessary to extract the financial and tax information in the form according to the customization information required by the final settlement and payment report. Then, after obtaining various financial and tax information of different dimensions, it can be grouped and input into the topological arithmetic unit with a preset value to quickly realize data operation subsequently, thereby improving the generation efficiency of the final settlement and payment report.

[0073] Among them, the final settlement and payment data is a form with the data required to generate the final settlement and payment report, the customization information is the pre-set data type information, such as expenditure data, income data, etc., the financial and tax information is the data information related to financial taxation, such as including various information such as income and expenditure, and the topological arithmetic unit is an arithmetic unit that performs information calculation using a topological structure.

[0074] In some embodiments, the specific implementation manner in step S1 (the server grabs the financial and tax information in the final settlement and payment data according to the information dimension based on the customization information, and after obtaining the financial and tax information of different information dimensions, groups and inputs it into a topological arithmetic unit with a preset value) includes:

[0075] S11, The server receives the final settlement data in the form of an initial tabular file input by an enterprise, and the final settlement data in the form of the tabular file includes at least information dimensions and information values.

[0076] It can be understood that the server receives the final settlement data input by the enterprise, and these data appear in the form of a tabular file, similar to a common spreadsheet (such as an Excel file). Among them, the information dimension is the dimension information related to finance and taxation, such as operating income, cost, etc., and the information value is the specific value corresponding to the information dimension.

[0077] S12, The server receives at least one final settlement target through a customized interaction module, and each final settlement target corresponds to the information value of at least one information dimension.

[0078] It can be understood that the server receives at least one final settlement target through a customized interaction module, and moreover, each final settlement target is associated with one or more information dimensions.

[0079] Among them, the customized interaction module is a pre-customized module for information interaction, and the final settlement target is the target information that needs to be displayed, such as the tax rate, tax profit information, etc. that need to be displayed.

[0080] It is not difficult to understand that there can be multiple final settlement targets, and among them, obtaining the final settlement targets needs to be calculated through the information values of the original relevant information dimensions.

[0081] S13, The server performs information scraping on the final settlement data in the form of a tabular file based on the information dimensions corresponding to all final settlement targets, and obtains the finance and taxation information of different information dimensions.

[0082] It can be understood that the server determines the information dimensions corresponding to the final settlement targets, so that it can identify and extract the information from the final settlement data in the form of a tabular file, and thus obtain the finance and taxation information of multiple information dimensions.

[0083] It is not difficult to understand that through information scraping, it can ensure that the server only focuses on the data related to the final settlement targets, improve the processing efficiency, and moreover, prepare the finance and taxation information data of different information dimensions for subsequent analysis and use.

[0084] S14, The server adjusts the preset topological operator based on the final settlement target, and obtains the operation link of the topological operator during this final settlement.

[0085] It can be understood that the server can adjust the settings of the preset topological operator according to the final settlement target, and this adjustment includes determining the operation link suitable for this final settlement, that is, optimizing the data flow path and calculation logic.

[0086] Among them, the operation link is the information link for data operation, such as the operation link corresponding to expenditure - income - profit.

[0087] Through the above - mentioned implementation manners, the adjustment of the topology calculator is realized, ensuring the pertinence and effectiveness of the calculation process. Through the optimized operation link, more efficient data processing and result generation are achieved.

[0088] In some embodiments, the specific implementation manner in step S14 (wherein the server adjusts the preset topology calculator based on the final settlement target to obtain the operation link of the topology calculator during this final settlement) includes:

[0089] S141, determine the output node corresponding to the final settlement target in the topology calculator as the first output node.

[0090] It can be understood that the output node is the node that outputs information results in the topology calculator, and the first output node is the output node corresponding to the final settlement target in the topology calculator, that is, the output node corresponding to the required information.

[0091] It is not difficult to understand that there are multiple output nodes in the topology calculator, and each node is responsible for outputting different information results. Clearly defining the target output node can ensure that the end point of the operation link is consistent with the final settlement target, improving the pertinence and effectiveness of the calculation. In a complex topology network, accurately positioning the output node is the key to effective data processing.

[0092] S142, based on the first output node and the connection path of the first output node, perform link backtracking in the topology calculator to obtain the backtracking start node and the backtracking link.

[0093] It can be understood that starting from the first output node, through its connection path for link backtracking, the start node of the operation link and the operation nodes along the way are found to form a backtracking link. The backtracking process is actually to trace forward the path of data flow to identify all nodes participating in the calculation, so as to optimize the irrelevant links and nodes subsequently, in order to obtain the operation link that conforms to the corresponding enterprise, thereby improving the generation efficiency of the final settlement report.

[0094] Among them, the connection path is the path connected between nodes, the backtracking start node is the node for link backtracking, and the backtracking link is the connection link between the backtracking start node and the first output node.

[0095] It is not difficult to understand that link backtracking helps to clarify the complete path of data processing, ensuring that all relevant nodes are considered, and laying a foundation for subsequent link optimization and path adjustment.

[0096] In some embodiments, the specific implementation of step S142 (performing link backtracking in the topology operator based on the first output node and the connection path of the first output node to obtain the backtracking start node and the backtracking link) includes:

[0097] S1421. Take each first output node as the corresponding backtracking start node, and establish an operation link cell corresponding to each backtracking start node in the initial operation link table.

[0098] It can be understood that by taking each first output node as the corresponding backtracking start node, in the initial operation link table, a dedicated operation link cell is created for each backtracking start node to store and organize the link information starting from this node.

[0099] Among them, the initial operation link table is a blank form, and the operation link cell is a cell used to fill and store the operation link.

[0100] It is not difficult to understand that starting from the output node, the link analysis is carried out one by one, and the operation paths with distinct levels are sorted out layer by layer. The operation link cell helps to systematically manage each path, facilitating subsequent analysis and adjustment.

[0101] S1422. Determine the first information dimension corresponding to the final settlement target of each first output node, and determine the input node corresponding to the first information dimension as the first input node, and determine the first input node as the backtracking termination node.

[0102] It can be understood that based on the final settlement target of each first output node, the relevant first information dimension is determined, and the input node corresponding to this dimension is identified, which is called the first input node, and it is determined as the backtracking termination node.

[0103] Among them, the first information dimension is the information dimension corresponding to the final settlement target of the first output node. For example, when the final settlement target is tax profit, the first information dimension obtained for tax profit can be enterprise revenue. That is, the input node corresponding to enterprise revenue is taken as the first input node, and the first input node is determined as the backtracking termination node, so that when performing link backtracking subsequently, the link backtracking stops when reaching the backtracking termination node.

[0104] Through the above implementation, the relevant information dimension and input node can be accurately located to ensure that each operation link accurately reflects the business target.

[0105] S1423. Generate the corresponding backtracking link based on the backtracking start node, the backtracking termination node, and the preset backtracking strategy.

[0106] It is understandable that a specific backtracking link is generated using the backtracking start node, the backtracking end node and the preset backtracking strategy, wherein the backtracking strategy may include rules such as path priority and resource restriction, which affect the way of link selection.

[0107] It is not difficult to understand that the introduction of the backtracking strategy makes the link generation process more flexible and intelligent, adapting to different business needs and resource allocations. The generated backtracking link clearly shows the overall picture of data flow and provides a basis for calculation and analysis.

[0108] In some embodiments, a specific implementation of step S1423 (generating a corresponding backtracking link based on the backtracking start node, the backtracking end node and a preset backtracking strategy) includes:

[0109] Taking the backtracking start node as the starting point, directly connected and / or indirectly connected upper dimension operation nodes and / or input nodes are determined respectively, and link backtracking is stopped after all backtracking termination nodes are determined.

[0110] It can be understood that starting from the backtracking start node, the operation node and / or input node of the upper dimension directly or indirectly connected to it is searched, and this process is continued until all the backtracking end nodes are identified and connected.

[0111] It is not difficult to understand that by gradually identifying the connection path, the integrity and accuracy of the link can be ensured. This step traces back layer by layer to clarify the source and path of each computing node, helping to achieve refined data tracking.

[0112] The directly connected operation nodes and / or output nodes, and / or the indirectly connected operation nodes and / or output nodes determined between the backtracking start node and the backtracking end node are counted to generate a backtracking link.

[0113] It can be understood that all directly and / or indirectly connected operation nodes and output nodes determined between the backtracking start node and the backtracking end node are counted, and a complete backtracking link is generated according to the statistical result.

[0114] It is not difficult to understand that the statistical process ensures that all relevant nodes are taken into account, and the generated back-tracking link shows the full link path from input to output, providing a complete basis for analysis, optimization and decision-making.

[0115] S143, summarize and count the backtracking start nodes and backtracking links, obtain the operation links of the topology operator during the current tax settlement and the operation link table of this time, disable the nodes in the non-operation links, and reverse the path of the backtracking link to obtain the operation link.

[0116] It can be understood that the starting nodes and links obtained by backtracking are summarized and statistically analyzed to identify the complete operation link required for this final settlement and payment. Nodes not within the operation link are deactivated to optimize resource utilization. By reverse-processing the backtracking link, the final operation link is obtained, that is, the order of data flow is from the starting point to the end point.

[0117] Among them, the operation link is the connection link for data operations during final settlement and payment, and the operation link table is a form showing each operation link.

[0118] Through the above implementation method, an operation link table corresponding to the output result can be obtained, ensuring that subsequent calculations are only carried out on necessary nodes and paths, improving efficiency. Reverse processing ensures that data flows along the optimal path, reducing latency and resource waste.

[0119] S2. Different operation units of the topology calculator decompose and calculate the fiscal and tax information according to the preset operation topology structure to obtain corresponding first fiscal and tax sub-information. The operation topology structure at least includes an input node, an operation node, and an output node.

[0120] It can be understood that there are multiple different operation units in the topology calculator, so that the corresponding operation units can decompose and calculate the fiscal and tax information according to the preset operation topology structure to obtain corresponding first fiscal and tax sub-information, providing data results for the subsequent generation of the final settlement and payment report.

[0121] Among them, the operation topology structure is the logical structure for operations in the topology calculator, such as Figure 2 shown, similar to a neural network, at least including an input node, an operation node, and an output node. The input node is the node for inputting information, the operation node is the node for performing data operations, and the output node is the node for outputting information.

[0122] In some embodiments, the specific implementation manner in step S2 (where different operation units of the topology calculator decompose and calculate the fiscal and tax information according to the preset operation topology structure to obtain corresponding first fiscal and tax sub-information, and the operation topology structure at least includes an input node, an operation node, and an output node) includes:

[0123] S21. Traverse each operation link cell in the operation link table in sequence, determine the corresponding input node according to the operation link in the operation link cell, and input the corresponding fiscal and tax information based on the type of the input node.

[0124] It can be understood that each operation link cell in the operation link table is traversed in sequence. According to the operation link filled in each cell, the relevant input nodes are determined one by one. According to the type of the input node, the corresponding fiscal and tax information is identified and obtained for system input.

[0125] Through the above embodiments, by traversing the operation link table and identifying the input nodes, it is ensured that in the entire topological structure, each operation unit can accurately identify and obtain the required fiscal and tax information. Among them, the automatic traversal and identification of the operation link table reduce manual intervention and improve the accuracy and efficiency of information input.

[0126] S22, based on all the nodes in the operation link and the connection relationships between the nodes, calculate to obtain the first fiscal and tax sub-information after calculation and processing by the operation nodes and / or output nodes.

[0127] It can be understood that according to the various nodes in the operation link and the connection relationships between them, calculations are performed. Starting from the input nodes, the first fiscal and tax sub-information corresponding to the operation nodes and / or output nodes is generated.

[0128] Among them, the first fiscal and tax sub-information is the fiscal and tax information output corresponding to each node. This node can be an operation node or an output node. For example, when the input revenue and cost are transmitted to the operation node, the profit is obtained through difference calculation. Then, the profit is multiplied by the corresponding tax rate to obtain the tax amount value corresponding to the output node of the payable tax amount. At the same time, the profit at the operation node may also have the need to generate a corresponding table. Then, the intermediate operation node can have the corresponding first fiscal and tax sub-information, such as profit.

[0129] It is not difficult to understand that through a reasonable topological structure and calculations, it is ensured that the generated fiscal and tax sub-information is accurate and reliable, providing high-quality basic data for subsequent integration and analysis of fiscal and tax information.

[0130] S3, if it is determined that there is a first node connected to the graphic rendering generation node in the operation topological structure, then after the first node has the first fiscal and tax sub-information, it is input to the graphic rendering generation node.

[0131] It can be understood that the graphic rendering generation node is a node that can generate and render graphics according to data information.

[0132] It is not difficult to understand that different nodes in the operation topological structure can all have corresponding connected graphic rendering generation nodes, so as to receive the data information of the corresponding connected nodes for graphic generation, facilitating intuitive viewing of the corresponding data information.

[0133] In some embodiments, the specific implementation manner in step S3 (wherein if it is determined that there is a first node connected to the graphic rendering generation node in the operation topological structure, then after the first node has the first fiscal and tax sub-information, it is input to the graphic rendering generation node) includes:

[0134] S31. Take all non-disabled nodes in the operation links of the operation topology structure as the first nodes.

[0135] It can be understood that the first nodes are the nodes in the operation links of the operation topology structure that participate in data operation or output, and the non-disabled nodes are the nodes that participate in information operation.

[0136] It is not difficult to understand that ensuring that only the valid nodes that participate in data operation or output are the first nodes is for subsequent data operation and transmission, so as to improve the efficiency of data processing.

[0137] S32. Determine the rendering quantity of the graphics rendering generation nodes connected to each first node.

[0138] It can be understood that the quantity requirement of the graphics generated by each node can be single or multiple, so that the rendering quantity corresponding to each first node can be obtained, so as to perform data analysis and graphics generation according to the corresponding rendering quantity subsequently.

[0139] Among them, the rendering quantity is the quantity of the graphics rendering generation nodes connected to each first node.

[0140] S33. If the rendering quantity is 1, input it to the graphics rendering generation node after the first node has the first fiscal and tax sub-information.

[0141] It can be understood that when the rendering quantity is 1, after obtaining the corresponding first fiscal and tax sub-information at the first node, it can be input to the image rendering generation node, so as to generate the corresponding graphics and perform rendering subsequently.

[0142] It is not difficult to understand that when there is only one rendering node, a rendering method is selected to simplify the processing logic, directly transmit data, and reduce latency.

[0143] S34. If the rendering quantity is multiple, determine the corresponding graphics rendering generation nodes based on the current final settlement and payment target and input the first fiscal and tax sub-information. Each final settlement and payment target has a preset graphics rendering generation node.

[0144] It can be understood that when the rendering quantity is multiple, appropriate graphics rendering generation nodes are selected for data input according to the current final settlement and payment target. Among them, each final settlement and payment target is pre-configured with a corresponding graphics rendering node.

[0145] Through the above implementation manner, the present invention can input the first fiscal and tax sub-information corresponding to the final settlement and payment target to the corresponding graphics rendering node, so as to generate the corresponding graphics and perform graphics rendering subsequently, realizing the visualization of data.

[0146] S4. The graphics rendering and generation node determines the second fiscal and tax sub-information corresponding to the first fiscal and tax sub-information based on the historical interaction data with the first node, and generates a final settlement and payment report based on the second fiscal and tax sub-information and the report generation habits of each graphics rendering and generation node.

[0147] It can be understood that the graphics rendering and generation node refers to the historical interaction data with the first node to determine the second fiscal and tax sub-information corresponding to the first fiscal and tax sub-information, and generates the final settlement and payment report according to the second fiscal and tax sub-information and the report generation habits of the graphics rendering and generation node.

[0148] Among them, the historical interaction data is the information data calculated corresponding to the historical time period, and the second fiscal and tax sub-information is the fiscal and tax information of the historical time corresponding to the first fiscal and tax sub-information.

[0149] It is not difficult to understand that through the graphics rendering and generation node, an intuitive report display method is provided, which is easier to understand and apply.

[0150] In some embodiments, the specific implementation manner in step S4 (the graphics rendering and generation node determines the second fiscal and tax sub-information corresponding to the first fiscal and tax sub-information based on the historical interaction data with the first node, and generates a final settlement and payment report based on the second fiscal and tax sub-information and the report generation habits of each graphics rendering and generation node) includes:

[0151] S41. The graphics rendering and generation node grabs the historical interaction data of the first node based on the enterprise label of the enterprise. The historical interaction data includes the historical time and historical fiscal and tax sub-information when the first fiscal and tax sub-information was generated each time previously.

[0152] It can be understood that this final settlement and payment can be for the tax situation of this year or a quarter. Therefore, the historical interaction data of the previous year or the previous quarter corresponding to the first node can be extracted according to the enterprise label of the enterprise, so as to analyze the current fiscal and tax sub-information and generate the current final settlement and payment report according to the historical interaction data and the corresponding report generation logic and method.

[0153] Among them, the enterprise label is a label indicating enterprise information, such as the enterprise type corresponding to the enterprise, or the enterprise name, etc. The historical time is the time when the first fiscal and tax sub-information was generated in the historical interaction data, and the historical fiscal and tax sub-information is the fiscal and tax sub-information generated corresponding to the historical time, such as the payable tax amount corresponding to the previous year.

[0154] S42. If the graphics rendering and generation node determines that the enterprise has not actively configured the report time dimension this time, it obtains the habitual time dimension based on the report generation habits of the previous graphics rendering and generation node.

[0155] It can be understood that if the enterprise does not actively configure the reporting time dimension this time, the system will determine a habitual time dimension based on the previous reporting generation habits, so as to ensure that even when the enterprise does not provide time dimension preferences, reports conforming to the enterprise's habits can still be generated through experience and historical data.

[0156] For example, when the graphic rendering generation node generates a report and does not receive the reporting time configured by the enterprise, the time of the reports generated within the historical time period can be referred to. When the reports generated within the historical time period usually refer to the reports of the previous three months for generating reports, then when generating reports this time, the reports generated within the previous three months can also be referred to, so as to obtain the corresponding habitual time dimension according to historical habits, which is convenient for configuring the time for the generated final settlement and payment report.

[0157] Among them, the reporting time dimension is the time dimension for generating the final settlement and payment report, and the habitual time dimension is the time dimension configured for the habitual preference report obtained by analyzing the reporting time corresponding to the historical time period.

[0158] In some embodiments, the specific implementation manner in step S42 (if the graphic rendering generation node determines that the enterprise does not actively configure the reporting time dimension this time, the habitual time dimension is obtained based on the reporting generation habits of the previous graphic rendering generation node) includes:

[0159] S421, obtain the historical time dimensions of all reports of all previous graphic rendering generation nodes, take the average value of all historical time dimensions and round up to obtain the habitual time dimension.

[0160] It can be understood that the time of the data referred to in the reports generated at historical moments can be 2 months, 3 months, etc., and the reference time dimensions of the reports generated within the historical time period can be inconsistent. Therefore, the average value of all historical time dimensions can be processed and rounded up to obtain the final habitual time dimension. For example, when the obtained historical time dimension is 2 - 3 months, the habitual time dimension obtained after rounding up is 3 months.

[0161] Among them, the historical time dimension is the time dimension of the report corresponding to the historical time.

[0162] It is worth mentioning that through the statistical analysis of historical data, a representative time dimension is generated to ensure that even if the enterprise does not actively configure, the system can still provide a reasonable time framework based on historical habits.

[0163] S43, if the graphic rendering generation node determines that the enterprise actively configures the reporting time dimension this time, extract the corresponding active time dimension.

[0164] It is understandable that when an enterprise actively configures the time dimension of the report, the system can directly extract the configured report time dimension to meet the requirements of the corresponding enterprise.

[0165] Among them, the active time dimension is the time dimension actively configured by the enterprise.

[0166] S44. Based on the habitual time dimension or the active time dimension, screen the historical fiscal and tax sub-information of historical moments in the database to obtain the second fiscal and tax sub-information, obtain the graphic habits of each graphic rendering generation node, and generate a final settlement and payment report based on the graphic habits and the second fiscal and tax sub-information.

[0167] It is understandable that according to the obtained habitual time dimension or active time dimension, screen the historical fiscal and tax sub-information corresponding to historical moments in the database, so as to use the screened historical fiscal and tax sub-information as the second fiscal and tax sub-information, and obtain the graphic habits of each graphic rendering generation node, so that the final settlement and payment report can be generated according to the graphic habits and the second fiscal and tax sub-information.

[0168] Among them, the second fiscal and tax sub-information is the historical fiscal and tax sub-information selected from the data according to the habitual time dimension or the active time dimension, and the graphic habit is the habit of generating graphics. For example, histograms or tree diagrams are usually generated, etc.

[0169] It is not difficult to understand that by screening relevant data and applying graphic habits, personalized and visual reports are generated to help enterprises more intuitively understand their financial status.

[0170] In some embodiments, the specific implementation manner in step S44 (screening the historical fiscal and tax sub-information of historical moments in the database based on the habitual time dimension or the active time dimension to obtain the second fiscal and tax sub-information, obtaining the graphic habits of each graphic rendering generation node, and generating a final settlement and payment report based on the graphic habits and the second fiscal and tax sub-information) includes:

[0171] S441. Based on the habitual time dimension or the active time dimension, determine the historical fiscal and tax sub-information of historical moments to screen and obtain the second fiscal and tax sub-information. The habitual time dimension or the active time dimension respectively includes corresponding time periods.

[0172] It is understandable that the habitual time dimension or the active time dimension respectively includes corresponding time periods to ensure that the fiscal and tax sub-information included in the report accurately reflects the financial and tax conditions during the defined time period according to the defined time dimension.

[0173] S442. Obtain the graphic habits of each graphic rendering generation node, and obtain the corresponding graphic templates based on the graphic habits. Each graphic habit has a preset graphic template.

[0174] It is understandable that the graphical habits of each graph rendering generation node are obtained, so as to obtain the corresponding graph template according to the graphical habits, which is convenient for subsequent rendering of the corresponding graph template according to the financial and tax sub-information.

[0175] Among them, the graphical habit has a preset graph template, and the graph template is a template for different data analysis graphs, such as a bar chart template without data, a pie chart template, etc.

[0176] In some embodiments, the specific implementation manner in step S442 (obtaining the graphical habits of each graph rendering generation node, obtaining the corresponding graph template based on the graphical habits, and each graphical habit has a preset graph template) includes:

[0177] S4421, obtaining the historical time dimension of all sub-reports of all previous graph rendering generation nodes, counting the graph types of all historical time dimensions, and obtaining the graph type with the largest quantity as the graph template.

[0178] It is understandable that the graph information of the historical report, including the time dimension and the graph type, is extracted from the database, the extracted data is analyzed, the usage frequency of each graph type is counted, and according to the statistical result, the graph type with the most occurrences is selected as the graph template.

[0179] Among them, the graph type is the type to which the data graph belongs, such as a tree diagram, a histogram, a pie chart, etc.

[0180] It is not difficult to understand that through the analysis of historical data, the most commonly used and user-friendly graph template is automatically selected to ensure that the selected graph template is consistent with the user's historical usage habits, so as to optimize the presentation effect and user satisfaction of the report, which not only improves the efficiency of generating the report, but also ensures the report quality and consistency.

[0181] S443, the graph rendering generation node performs fusion rendering based on the graph template, the first financial and tax sub-information, and the second financial and tax sub-information respectively, corresponding to a sub-report of a graph rendering generation node.

[0182] It is understandable that when there are multiple graph rendering generation nodes, fusion rendering is performed based on the graph template, the first financial and tax sub-information, and the second financial and tax sub-information respectively to obtain sub-reports corresponding to each graph generation node, so as to perform sorting and combination subsequently to obtain the final settlement report.

[0183] In some embodiments, the specific implementation manner in step S443 (the graph rendering generation node performs fusion rendering based on the graph template, the first financial and tax sub-information, and the second financial and tax sub-information respectively, corresponding to a sub-report of a graph rendering generation node) includes:

[0184] S4431. The graphics rendering generation node determines the graphics to be rendered in the graphics template, and selects the corresponding slots to be rendered in the graphics to be rendered based on the first fiscal and tax sub-information and the second fiscal and tax sub-information.

[0185] It can be understood that some graphics templates are standard, and their bottom plates have color displays and do not require color rendering. However, some graphics models are data-related. Therefore, color rendering needs to be performed according to the corresponding data, so that the graphics to be rendered that require color rendering can be determined, and the corresponding slots to be rendered can be selected according to the quantity of data corresponding to the first fiscal and tax sub-information and the second fiscal and tax sub-information.

[0186] For example, when the graphics template is a histogram, and the corresponding first fiscal and tax sub-information is the tax amount in June, and the second fiscal and tax sub-information includes the tax amounts in March, April, and May, then 4 slots can be selected in the histogram as the slots to be selected for rendering, so as to perform color rendering subsequently.

[0187] Among them, the graphics to be rendered are the graphics that require color rendering, and the slots to be rendered are the slots that require color rendering.

[0188] Through the above implementation method, the corresponding graphics to be rendered and the slots to be rendered are determined, so as to perform color rendering subsequently, ensuring the accurate and effective presentation of fiscal and tax information in the report.

[0189] S4432. Based on the sequence numbers of the slots to be rendered, the time numbers of the first fiscal and tax sub-information and the second fiscal and tax sub-information, the slots to be rendered are respectively processed corresponding to the first fiscal and tax sub-information or the second fiscal and tax sub-information.

[0190] It can be understood that the slots to be rendered are numbered in the order from left to right, and the time when the first fiscal and tax sub-information and the second fiscal and tax sub-information obtain the corresponding data is numbered in the order from early to late, so that the sequence numbers can be corresponding to the time numbers, so as to render the corresponding slots according to the fiscal and tax data at the corresponding time subsequently.

[0191] Among them, the sequence number is the number corresponding to the sequential arrangement of the slots to be rendered, such as the 1st, the 2nd, the 3rd, etc., and the time number is the sequential arrangement number for time, such as March, April, May, etc.

[0192] For example, when the second fiscal and tax sub-information corresponds to March, April, and May, and the first fiscal and tax sub-information corresponds to June, then the 1st slot to be rendered can be corresponding to the second fiscal and tax sub-information in March, the 2nd slot to be rendered can be corresponding to the second fiscal and tax sub-information in April, the 3rd slot to be rendered can be corresponding to the second fiscal and tax sub-information in May, and the 4th slot to be rendered can be corresponding to the second fiscal and tax sub-information in June.

[0193] It is not difficult to understand that through orderly arrangement and correspondence, it is ensured that information is accurately filled into the correct positions of the graphic template.

[0194] S4433, determine the rendering pixel points and rendering pixel values of the first fiscal sub-information and the second fiscal sub-information based on the values of the first fiscal sub-information or the second fiscal sub-information, and generate a sub-report of the node for graphic rendering based on the rendering pixel points and rendering pixel values.

[0195] It can be understood that different values have corresponding rendering pixel points, so that the rendering pixel points of the first fiscal sub-information and the second fiscal sub-information can be determined according to the values of the first fiscal sub-information or the second fiscal sub-information, so as to perform pixel rendering on the corresponding rendering pixel points.

[0196] Among them, the rendering pixel point is the pixel point for color rendering, and the rendering pixel value is the pixel value for rendering, such as it can be red, blue, etc.

[0197] Moreover, the total number of pixel points in the slot to be rendered can be counted, and the largest value among the first fiscal sub-information and the second fiscal sub-information is selected as the total value. The reference rendering pixel point number is obtained according to the ratio of the total number of pixel points to the total value, which is convenient for subsequently calculating the ratio of the values of each first fiscal sub-information and the second fiscal sub-information to the total value to obtain the quantity proportion, so that the rendering pixel points corresponding to the values of each fiscal sub-information can be determined by multiplying according to the quantity proportion and the reference rendering pixel point number.

[0198] Among them, the total number of pixel points is the sum of the pixel points in the slot to be rendered, and the total value is the largest value among the first fiscal sub-information and the second fiscal sub-information. For example, the value corresponding to March is 400,000, the value corresponding to April is 200,000, the value corresponding to May is 600,000, and the value corresponding to June is 1,000,000, then the total value is the largest 1,000,000, and the reference rendering pixel point number is the number of pixel points corresponding to the unit value. For example, when the total number of pixel points is 1000 and the total value is 1,000,000, the corresponding reference rendering pixel point number is 10, that is, a value of 10,000 corresponds to rendering 1 pixel point.

[0199] At the same time, the quantity proportion is the proportion of the number of pixel points rendered for the slot to be rendered by the values corresponding to each fiscal sub-information. For example, when the value corresponding to March of the second fiscal sub-information is 400,000, the quantity proportion can be obtained as 40÷100 = 2 / 5, and then the rendering pixel points corresponding to March can be obtained as 2 / 5×1000 = 400.

[0200] It is worth mentioning that when performing pixel point rendering, pixel differentiation can be carried out according to the value size. For example, Figure 3As shown, a value of 500,000 can be set artificially in advance. When the value of the corresponding financial and tax sub - information is less than or equal to 50, the corresponding rendering pixel points can be rendered yellow. When the value of the corresponding financial and tax sub - information is greater than 50, the corresponding rendering pixel points can be rendered red, so as to make an obvious distinction and facilitate observing the size of the value, thereby intuitively reflecting the financial and tax situation of the enterprise.

[0201] S444. Combine all sub - reports in the order of priority to generate the finalized annual settlement and payment report.

[0202] It can be understood that all sub - reports are combined in the preset order of priority to generate the final finalized annual settlement and payment report.

[0203] It is not difficult to understand that through the order of priority, it is ensured that the most important information is presented first, optimizing the logical structure and information transmission of the report.

[0204] The present invention also provides a storage medium in which a computer program is stored. When the computer program is executed by a processor, it is used to implement the methods provided by the above - mentioned various embodiments.

[0205] Among them, the storage medium can be a computer storage medium or a communication medium. The communication medium includes any medium that facilitates the transmission of a computer program from one place to another. The computer storage medium can be any available medium that can be accessed by a general - purpose or special - purpose computer. For example, the storage medium is coupled to the processor so that the processor can read information from the storage medium and write information to the storage medium. Of course, the storage medium can also be a component of the processor. The processor and the storage medium can be located in an application - specific integrated circuit (ASIC). In addition, the ASIC can be located in the user equipment. Of course, the processor and the storage medium can also exist as discrete components in the communication device. The storage medium can be a read - only memory (ROM), a random - access memory (RAM), a CD - ROM, a magnetic tape, a floppy disk, and an optical data storage device, etc.

[0206] The present invention also provides a program product. The program product includes execution instructions that are stored in the storage medium. At least one processor of the device can read the execution instructions from the storage medium, and at least one processor executes the execution instructions so that the device implements the methods provided by the above - mentioned various embodiments.

[0207] In the above embodiments of the terminal or the server, it should be understood that the processor may be a central processing unit (Central Processing Unit, CPU for short), or may also be other general-purpose processors, digital signal processors (Digital Signal Processor, DSP for short), application specific integrated circuits (Application Specific Integrated Circuit, ASIC for short), etc. The general-purpose processor may be a microprocessor or the processor may also be any conventional processor, etc. The steps of the method disclosed in conjunction with the present invention may be directly embodied as being executed by a hardware processor, or executed by a combination of hardware and software modules in the processor.

[0208] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that they can still modify the technical solutions described in the foregoing embodiments, or perform equivalent replacements for some or all of the technical features; and these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. The intelligent generation method of enterprise tax settlement report is characterized by: include: The server captures the fiscal and tax information in the tax settlement data according to the information dimension based on the customized information, obtains the fiscal and tax information of different information dimensions, and then groups them and inputs them into the topological operator with preset values; Different operation units of the topological operator perform decomposition operation on the financial and tax information according to the operation topological structure of the preset value to obtain the corresponding first financial and tax sub-information, wherein the operation topological structure at least includes an input node, an operation node and an output node; If it is determined that there is a first node connected to the graphics rendering generation node in the computational topology structure, then after the first node has the first finance and taxation sub-information, the first node is input to the graphics rendering generation node; The graphic rendering generation node determines the second financial and taxation sub-information corresponding to the first financial and taxation sub-information based on the historical interaction data with the first node, and generates a final settlement report based on the second financial and taxation sub-information and the report generation habits of each graphic rendering generation node.

2. The intelligent generation method of enterprise tax settlement report according to claim 1 is characterized in that: The server captures the fiscal and tax information in the tax settlement data according to the information dimension based on the customized information, obtains the fiscal and tax information of different information dimensions, and then groups and inputs them into the topological operator of the preset value, including: The server receives the tax settlement data in the form of an initial table file input by the enterprise, wherein the tax settlement data in the form of a table file at least includes information dimensions and information values; The server receives at least one tax settlement target through a customized interaction module, and each tax settlement target corresponds to an information value of at least one information dimension; Based on the information dimensions corresponding to all tax settlement targets, the server captures tax settlement data in the form of table files to obtain financial and tax information in different information dimensions; The server adjusts the preset topology operator based on the tax settlement target to obtain the calculation link of the topology operator for this tax settlement.

3. The intelligent generation method of enterprise tax settlement report according to claim 2 is characterized in that: The server adjusts the topological operator of the preset value based on the final settlement target to obtain the operation link of the topological operator during the final settlement, including: Determine the output node corresponding to the tax settlement target in the topological operator as the first output node; Perform link backtracking in a topology operator based on the first output node and the connection path of the first output node to obtain a backtracking start node and a backtracking link; The backtracking start node and the backtracking link are summarized and counted to obtain the operation link of the topology operator during this tax settlement and the operation link table of this time, deactivate the nodes in the non-operation link, and reverse the path of the backtracking link to obtain the operation link.

4. The intelligent generation method of enterprise tax settlement report according to claim 3 is characterized in that: The step of performing link backtracking in a topology operator based on the first output node and the connection path of the first output node to obtain a backtracking start node and a backtracking link includes: Taking each first output node as a corresponding backtracking start node, establishing a calculation link cell corresponding to each backtracking start node in the initial calculation link table; Determine a first information dimension corresponding to the tax settlement target of each first output node, and determine an input node corresponding to the first information dimension as a first input node, and determine the first input node as a backtracking termination node; A corresponding backtracking link is generated based on the backtracking start node, the backtracking end node and the preset backtracking strategy.

5. The intelligent generation method of enterprise tax settlement report according to claim 4 is characterized in that: The generating of a corresponding backtracking link based on the backtracking start node, the backtracking end node and a preset backtracking strategy includes: Taking the backtracking start node as the starting point, respectively determine the upper dimension operation nodes and / or input nodes that are directly connected and / or indirectly connected, until all the backtracking end nodes are determined, and then stop the link backtracking; The directly connected operation nodes and / or output nodes, and / or the indirectly connected operation nodes and / or output nodes determined between the backtracking start node and the backtracking end node are counted to generate a backtracking link.

6. The intelligent generation method of enterprise tax settlement report according to claim 4 is characterized in that: Different operation units of the topological operator perform decomposition operation on the fiscal and tax information according to the operation topological structure of the preset value to obtain the corresponding first fiscal and tax sub-information, wherein the operation topological structure at least includes an input node, an operation node and an output node, including: Traversing each operation link cell in the operation link table in turn, determining the corresponding input node in turn according to the operation link in the operation link cell, and determining and inputting the corresponding financial and tax information based on the type of the input node; Based on the calculation of all nodes in the operation link and the connection relationship between nodes, the first financial and taxation sub-information after the operation node and / or output node is calculated and processed is obtained.

7. The method for intelligently generating enterprise tax settlement report according to claim 6 is characterized in that: If it is determined that there is a first node connected to the graphics rendering generation node in the computing topology structure, then after the first node has the first finance and taxation sub-information, the first node is inputted into the graphics rendering generation node, including: All non-deactivated nodes of the computing links in the computing topology are used as first nodes; Determine the rendering quantity of the graphics rendering generation nodes connected to each first node; If the rendering quantity is 1, then after the first node has the first finance and taxation sub-information, it is input to the graphics rendering generation node; If the number of renderings is multiple, the corresponding graphic rendering generation node is determined based on the current tax settlement target and the first financial and tax sub-information is input. Each tax settlement target has a preset graphic rendering generation node.

8. The method for intelligently generating enterprise tax settlement report according to claim 1 is characterized in that: The graphic rendering generation node determines the second financial and taxation sub-information corresponding to the first financial and taxation sub-information based on the historical interaction data with the first node, and generates a final settlement report based on the second financial and taxation sub-information and the report generation habit of each graphic rendering generation node, including: The graphic rendering generation node captures historical interaction data of the first node based on the enterprise tag of the enterprise, wherein the historical interaction data includes the historical moment and historical finance and taxation sub-information of each previous generation of the first finance and taxation sub-information; If the graphic rendering generation node determines that the enterprise has not actively configured the report time dimension this time, it obtains the custom time dimension based on the report generation habit of the previous graphic rendering generation node; If the graphics rendering generation node determines that the enterprise actively configures the report time dimension this time, it extracts the corresponding active time dimension; Based on the customary time dimension or the active time dimension, the historical fiscal and taxation sub-information at the historical moment is filtered in the database to obtain the second fiscal and taxation sub-information, the graphic habit of each graphic rendering generation node is obtained, and the reconciliation and settlement report is generated based on the graphic habit and the second fiscal and taxation sub-information.

9. The method for intelligently generating enterprise tax settlement report according to claim 8 is characterized in that: If the graphic rendering generation node determines that the enterprise has not actively configured the report time dimension this time, the custom time dimension is obtained based on the report generation habit of the previous graphic rendering generation node, including: The historical time dimensions of all reports of all previous graphics rendering generation nodes are obtained, and the average of all historical time dimensions is rounded up to obtain the customary time dimension.

10. The method for intelligently generating enterprise tax settlement report according to claim 8 is characterized in that: The step of filtering the historical fiscal and taxation sub-information at the historical moment in the database based on the customary time dimension or the active time dimension to obtain the second fiscal and taxation sub-information, obtaining the graphic habit of each graphic rendering generation node, and generating a final settlement report based on the graphic habit and the second fiscal and taxation sub-information includes: The second financial and tax sub-information is obtained by filtering the historical financial and tax sub-information at the historical moment based on the customary time dimension or the active time dimension, wherein the customary time dimension or the active time dimension respectively includes a corresponding time period; Obtaining a graphic habit of each graphic rendering generation node, and obtaining a corresponding graphic template based on the graphic habit, wherein each graphic habit has a preset graphic template; The graphic rendering generation node performs fusion rendering based on the graphic template, the first fiscal and taxation sub-information and the second fiscal and taxation sub-information, respectively, and a sub-report of the corresponding graphic rendering generation node is generated; All sub-reports are combined in order of priority to generate a final settlement report.

11. The method for intelligently generating enterprise tax settlement report according to claim 10 is characterized in that: The step of obtaining the graphic habit of each graphic rendering generation node and obtaining a corresponding graphic template based on the graphic habit, wherein each graphic habit has a preset graphic template, includes: Obtain the historical time dimensions of all sub-reports of all previous graphics rendering generation nodes, count the graphics types of all historical time dimensions, and obtain the graphics template by obtaining the graphics type with the largest number.

12. The method for intelligently generating enterprise tax settlement report according to claim 10 is characterized in that: The graphic rendering generation node performs fusion rendering based on the graphic template, the first fiscal and taxation sub-information, and the second fiscal and taxation sub-information, respectively. A sub-report of a corresponding graphic rendering generation node includes: The graphic rendering generation node determines the graphic to be rendered in the graphic template, and selects a corresponding slot to be rendered in the graphic to be rendered based on the first financial and taxation sub-information and the second financial and taxation sub-information; Based on the sequence number of the slot to be rendered, the time number of the first fiscal and taxation sub-information and the second fiscal and taxation sub-information, the slot to be rendered is processed correspondingly to the first fiscal and taxation sub-information or the second fiscal and taxation sub-information; The rendering pixel points and rendering pixel values ​​of the first fiscal and taxation sub-information and the second fiscal and taxation sub-information are determined based on the numerical value of the first fiscal and taxation sub-information or the second fiscal and taxation sub-information, and a sub-report of the node is generated for graphics rendering based on the rendering pixel points and rendering pixel values.

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