Modular mathematical calculation model combination system and method and electronic equipment

Abstract

The invention relates to the technical field of intelligence, and provides a modular mathematical calculation model combination system, through modular calculation models, such as a basic model, a combination model and a scene model, each calculation model comprises a multi-parameter input interface and a multi-parameter output interface, and a plurality of calculation models can be combined in series or in parallel so as to realize multi-parameter input and multi-parameter output. The output parameters of the preposed calculation model can be used as the input parameters of the subsequent calculation model. The invention further discloses a method, a plurality of calculation models can be visually combined in the steps S1 to S3 in a series connection or parallel connection mode to form a working process, data interaction is carried out through the independent calculation models and an interface, and finally the whole calculation task is completed. The whole calculation efficiency is improved, the reusability, expandability and maintainability of software are improved, personalized engineering calculation tasks can be met quickly through combination of calculation models, the engineering task processing efficiency is improved, and the software operation complexity is reduced.

Description

Technical Field

[0001] The present invention relates to the field of intelligent technology, and in particular to a modular mathematical calculation model combination system and method, and electronic equipment. Background Art

[0002] Mathematical computing models refer to models that use mathematical and computer methods for modeling, analysis and prediction. At present, mathematical computing models are widely used in various fields, including natural sciences, engineering technology, social sciences, etc. For example, mathematical computing models have been widely used in modeling and analysis in natural science fields such as physics, chemistry, and biology, such as weather forecasting, climate change, molecular simulation, protein structure prediction, building structure analysis, traffic flow simulation, power system optimization, robot control, etc.

[0003] CN115604262A discloses a multi-party computing method and electronic device, which are applied to computing nodes, including: receiving multiple computing modules sent by an algorithm providing node in sequence, the multiple computing modules can form a computing module combination according to the algorithm dependency relationship corresponding to the target algorithm, the computing module combination is used for executing the target algorithm on the computing node, the multiple computing modules are sent in sequence by the algorithm providing node according to the algorithm dependency relationship; in the process of receiving the multiple computing modules, executing the computing steps in the target algorithm corresponding to the received computing modules.

[0004] In the prior art, mathematical calculation software is complicated to operate, and its operation is more complicated than general software, and it is difficult to quickly perform operations such as formula input, data input, and script writing. Summary of the invention

[0005] After long-term practice, it is found that due to the high degree of professionalism of mathematical calculation software, it requires complex formula input, the operation interface is relatively complex and difficult, a large amount of data needs to be input during the operation, the input workload is large, and data input may often be wrong, and even lead to technical problems such as the collapse of the entire system. In particular, when encountering a complex personalized engineering calculation task, it often requires a highly professional model building process, and the calculation efficiency is low and the complexity is high.

[0006] In view of this, the present invention provides a modular mathematical computing model combination system, the modular mathematical computing model combination system includes a plurality of modular computing models, the computing models at least include a basic model, a combination model and a scenario model, the computing models include an interface for multi-parameter input and multi-parameter output; the plurality of computing models can be combined in series or in parallel; The basic models include statistical models, planning models, and differential models; The combination model includes factor analysis and decision combination model; The scenario model includes a product performance factor analysis model; When a plurality of the calculation models are connected in series, the output parameters of the preceding calculation model can be used as input parameters of the subsequent calculation model.

[0007] In one embodiment, the output parameter A of the computing model can be preprocessed by a function mapping f and then used as the input parameter B of other computing models; B=f(A)

[0008] Among them, A or B includes numerical data, vector data, and image data.

[0009] In one embodiment, the modular mathematical computing model combination system further includes a configuration module, which is used for associative connection during the series or parallel combination of multiple computing models.

[0010] In one embodiment, the configuration module is also used to set the output parameters, input parameter types and precision of the calculation model.

[0011] In one embodiment, the modular mathematical computing model combination system further includes a permission configuration module, which is used for establishing, modifying and updating the computing model, as well as the permission control of a combination of multiple computing models.

[0012] In one embodiment, the modular mathematical calculation model combination system also includes a start module and a stop module; the start module is used to start the calculation model process of the series or parallel combination; the stop module is used to stop the calculation model process of the series or parallel combination.

[0013] The present invention also discloses a method for the modular mathematical computing model combination system as described above, the method comprising: Step S1, select a modular calculation model from the candidate library, and set the type, format and precision of the input parameters; Step S2, multiple calculation models are combined in series or in parallel to form a workflow, wherein input parameters and output parameters in the calculation models are associated and connected; Step S3, displaying the logical connection relationship between the multiple calculation models and the output parameters of each calculation model through a display module.

[0014] In one embodiment, output parameters generated by multiple computing models can be input into other computing models as input parameters after preprocessing.

[0015] The present invention also discloses an electronic device, comprising a memory and a processor: the memory is used to store a computer program; the processor is used to implement the above method when executing the computer program.

[0016] The present invention also discloses a machine-readable storage medium, on which instructions are stored, and the instructions are used to enable a machine to execute the method of the present application as described above.

[0017] Compared with the prior art, the modular mathematical calculation model combination system provided by the present invention, through modular calculation models, for example, basic models, combination models and scenario models, the calculation model includes interfaces for multi-parameter input and multi-parameter output, and multiple calculation models can be combined in series or in parallel, and the output parameters of the preceding calculation model can be used as input parameters of the subsequent calculation model. The present invention also discloses a method for a modular mathematical calculation model combination system, in which steps S1 to S3 can visually combine multiple calculation models in series or in parallel to form a workflow, and the independent calculation models are used to perform data interaction through interfaces to finally complete the entire calculation task. The overall calculation efficiency is improved, the reusability, scalability and maintainability of the software are improved, and the personalized engineering calculation tasks can be quickly met through the combination of calculation models, the efficiency of engineering task processing is improved, and the complexity of software operation is reduced.

[0018] Other features and advantages of the present invention will be described in detail in the following detailed description. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] The accompanying drawings constituting a part of the present invention are used to provide a further understanding of the present invention. The exemplary embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute an improper limitation of the present invention. In the accompanying drawings: Figure 1 A schematic diagram of each module of a modular mathematical computing model combination system according to an embodiment of the present invention; Figure 2 A schematic diagram of a modular mathematical computing model definition interface according to an embodiment of the present invention; Figure 3 A schematic diagram of a module combination interface in a modular mathematical computing model according to an embodiment of the present invention; Figure 4 A schematic diagram of a specific configuration of modules in a modular mathematical computing model according to an embodiment of the present invention; Figure 5 A schematic diagram of authority settings in a modular mathematical computing model according to an embodiment of the present invention; Figure 6 A schematic diagram of a modular mathematical computing model designer and executor according to an embodiment of the present invention. DETAILED DESCRIPTION

[0020] The specific implementation of the present invention is described in detail below in conjunction with the accompanying drawings. It should be understood that the specific implementation described here is only used to illustrate and explain the present invention, and is not used to limit the present invention.

[0021] In order to enable those skilled in the art to better understand the scheme of the present invention, the technical scheme in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present invention.

[0022] It should be noted that the terms "first", "second", "third", "fourth", etc. in the specification and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged where appropriate, so as to describe the embodiments of the present invention described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0023] In the prior art, mathematical calculation software is highly professional and requires complex formula input. The operation interface is relatively complex and difficult. A large amount of data needs to be input during operation, which results in a large input workload. In addition, data input may often lead to errors, and even cause the entire system to crash. In particular, when encountering a complex personalized engineering calculation task, a highly professional model building process is often required, and the calculation efficiency is low and the complexity is high. Figure 1-2 As shown, the present invention provides a modular mathematical computing model combination system comprising: A plurality of modular computing models, wherein the computing models at least include a basic model, a combination model and a scenario model, and the computing models include interfaces for multi-parameter input and multi-parameter output; the plurality of computing models can be combined in series or in parallel; The basic models include statistical models, planning models, and differential models; The combination model includes factor analysis and decision combination model; The scenario model includes a product performance factor analysis model; When a plurality of the calculation models are connected in series, the output parameters of the preceding calculation model can be used as input parameters of the subsequent calculation model.

[0024] The modular mathematical calculation model combination system provided by the present invention, through modular calculation models, for example, basic models, combination models and scenario models, the calculation model includes an interface for multi-parameter input and multi-parameter output, and multiple calculation models can be combined in series or in parallel, and the output parameters of the preceding calculation model can be used as the input parameters of the subsequent calculation model. It is possible to visually combine multiple calculation models in series or in parallel to form a workflow, and to perform data interaction through the interface through the independent calculation models, and finally complete the entire calculation task. Improve the overall calculation efficiency, improve the reusability, scalability and maintainability of the software, and can quickly meet personalized engineering calculation tasks through the combination of calculation models, improve the efficiency of engineering task processing, and reduce the complexity of software operation. The calculation model generally refers to an independent calculation processing module including input and output interfaces, and certain operation rules encapsulated inside. The calculation model can process engineering calculation tasks alone, and can also be combined in series, parallel and mixed connection to form a complete engineering calculation task processing workflow.

[0025] The computing model includes but is not limited to a statistical model, a planning model, and a differential model, and can establish a computing model based on input and output parameters and functional relationships required in practice.

[0026] The basic model includes but is not limited to a statistical model, a planning model, and a differential model, which are divided according to specific computing units, and the models are packaged and combined to form a specific basic model.

[0027] A combined model is a model that is composed of basic models. For example, a model that contains processes is composed of basic models. A combined model can contain multiple combined models.

[0028] The scenario model is an extension of the combination model, which is oriented to specific engineering applications and problems, generally to specific links of specific industries or enterprises, re-identifies the technical terms on the combination model, and adds data preprocessing links and industry-specific process links. For example, A product performance factor analysis model or B process stability factor analysis model.

[0029] like Figure 2As shown in the figure, for example, users can encapsulate the integer linear programming model as one of the linear programming models in the basic model according to the actual needs of the project, define the input parameters including known constraints, and output objective functions and values. Among them, the input parameter and output parameter types, precision, and specifications can be defined according to specific actual conditions. Different types of user roles are set in the modular mathematical calculation model combination system, such as Figure 5-Figure 6 For example, user roles include users, application designers, and basic model designers. In the designer, the basic model designer defines the calculation model according to the above-defined method. Users only need to drag the calculation model in the executor to quickly build a personalized combined calculation model for specific engineering calculation tasks, which can greatly improve the efficiency of engineering task processing.

[0030] In order to better use all or part of the output parameters of a certain computing model as input parameters of another computing model, or to use additional parameters as input parameters of a computing model, in another embodiment of the present invention, the output parameter A of the computing model can be preprocessed by function mapping f and used as input parameter B of other computing models; B=f(A)

[0031] Among them, A and B include numerical data, vector data, and image data.

[0032] In the function mapping f preprocessing process, the function mapping f preprocessing also includes data cleaning, data integration, data reduction and data transformation. For example, when image data is used in the multi-source data fusion operation, it is necessary to digitize the image data and form standard vector data with other numerical data for calculating the input of the model.

[0033] In order to better modularize the computing model so as to enable packaging and combination, in another embodiment of the present invention, the modular mathematical computing model combination system further includes a configuration module, which is used for associating and connecting multiple computing models in series or parallel combination. Figure 3 As shown, for example, the configuration module connects multiple computing models in series or in parallel. And it can be configured in a specific manner, such as Figure 4As shown, for example, factor search test is an independent calculation model, and its name Name, display name Text, table label Caption, and control parameter ControlData are set. Therefore, factor import, structure data generation, factor search test, factor search analysis, factor search output, and full factor analysis can be independent calculation models, and they can be connected in series according to the logical order. Some or all of the output parameters in the preceding calculation model are used as input parameters of the subsequent calculation model. For example, the "factor search test" calculation model is the preceding calculation model of "factor search analysis"; and "factor search analysis" is the subsequent calculation model of "factor search test", which are connected by arrow connecting lines. Start Start and Stop End End are process nodes. Start Start is used to start the calculation task; Stop End End is used to stop and end the calculation task. Among them, it also includes "confirmation" and "search" independent modules for specific processing process data control operations.

[0034] In order to better package and modularize different independent calculation models, so that they can be quickly called in the process of specific engineering task processing to meet the needs of personalized and different engineering calculation tasks, in another embodiment of the present invention, the configuration module is also used for the output parameters, input parameter types and precision settings of the calculation model. The parameter setting of the calculation model is realized through the permission configuration module, which effectively avoids the problem of calculation errors or inaccurate calculation results caused by improper parameter settings. At the same time, the permission configuration module personalizes the parameters of the calculation model according to the needs of different users or application scenarios, thereby improving the applicability and practicality of the calculation model.

[0035] In order to better update and modify independent computing models, different computing model modules can be continuously expanded in terms of functions, and the permissions for model updates and modifications need to be optimized and managed, such as Figure 5 As shown. In another embodiment of the present invention, the modular mathematical calculation model combination system also includes a permission configuration module, which is used for the establishment, modification and update of the calculation model, as well as the permission control of multiple combinations of the calculation models. The permission configuration module controls the operation permissions of the calculation model by configuring the permissions of different users or user groups. For example, only specific users or user groups can modify or update the calculation model, thereby ensuring the security and stability of the calculation model. In addition, the permission configuration module also implements permission control for different combinations of calculation models. For example, different calculation models can only be combined under specific conditions, thereby avoiding data corruption or calculation errors that may be caused by unreasonable combinations. The flexibility and scalability of the calculation model are improved, while the security and controllability of the calculation model can be guaranteed.

[0036] In order to ensure the correct start of the process, the stop module can ensure that the process stops processing tasks at the right time. Avoid starting or stopping the process too early or too late, which causes the process to fail to operate normally. In another embodiment, the modular mathematical calculation model combination system also includes a start module and a stop module; the start module is used to start the calculation model process of the series or parallel combination; the stop module is used to stop the calculation model process of the series or parallel combination. By setting the start and stop modules, the process can be easily modified and maintained. For example, if the starting condition or stop condition of the process needs to be changed, it is only necessary to modify the settings of the start and stop nodes. To improve the visualization of the process, the start and stop modules are usually at the very beginning and the very end of the flowchart, so that the start and end of the entire process are clearer. At the same time, by setting the start and stop modules, the execution process of the entire process is made clearer and more visible.

[0037] The present invention also discloses a method for the modular mathematical computing model combination system as described above, the method comprising: Step S1, select a modular calculation model from the candidate library, and set the type, format and precision of the input parameters; Step S2, multiple calculation models are combined in series or in parallel to form a workflow, wherein input parameters and output parameters in the calculation models are associated and connected; Step S3, displaying the logical connection relationship between the multiple calculation models and the output parameters of each calculation model through a display module.

[0038] The technical solution provided by the invention can visually combine multiple computing models in series or in parallel to form a workflow through steps S1 to S3, and the independent computing models interact with data through interfaces to finally complete the entire computing task, thereby realizing efficient processing of complex computing tasks. By combining multiple computing models into a workflow, the step-by-step processing of computing tasks can be realized, thereby improving computing efficiency. At the same time, by setting parameters such as the type and format of input parameters and precision, the precision and accuracy of the calculation can be further improved. By selecting modular computing models from the alternative library, flexible combinations can be made according to actual needs to meet the needs of different users or application scenarios. At the same time, the connection logic relationship and output parameters of multiple computing models are displayed through the display module, which is convenient for users to debug and optimize. Through the display of the display module, users can clearly understand the input-output relationship of each computing model and the execution process of the entire workflow, thereby improving the visualization of the computing process.

[0039] In order to further improve the accuracy and reliability of the calculation results, avoid the problem of abnormal or erroneous calculation results due to poor or inconsistent data quality, thereby improving the stability and reliability of the calculation model. In another embodiment, the output parameters generated by multiple calculation models can be input into other calculation models as input parameters after preprocessing. Specifically, preprocessing can include operations such as data cleaning, deduplication, normalization, feature extraction, etc., so that the calculation results are more accurate and reliable. By preprocessing the output parameters generated by multiple calculation models, errors and deviations in the calculation results can be effectively avoided, and the accuracy and reliability of the calculation results can be improved. At the same time, preprocessing can also personalize the calculation results according to the needs of different users or application scenarios, thereby improving the applicability and practicality of the calculation results.

[0040] The preprocessing includes the following steps: Step S11, data cleaning, performs data cleaning on the output parameters generated by the calculation model to remove abnormal values ​​or erroneous data to ensure the accuracy and reliability of the data.

[0041] Step S12, data aggregation, aggregates the output parameters generated by multiple calculation models to form a comprehensive calculation result, thereby improving the comprehensiveness and reliability of the calculation result.

[0042] Step S13, data conversion, converts the output parameters generated by the calculation model to meet specific needs or format requirements, thereby improving the applicability and usability of the calculation results.

[0043] Furthermore, the present invention also provides an electronic device, comprising a memory and a processor: the memory is used to store a computer program; the processor is used to implement the above method when executing the computer program.

[0044] Furthermore, the present invention also provides a computer-readable storage medium on which a computer program is stored, and when the program is executed by a processor, the above method provided by the present invention is implemented.

[0045] It should be noted that, for the above-mentioned method embodiments, for the sake of simplicity, they are all described as a series of action combinations, but those skilled in the art should know that the present invention is not limited by the described action sequence, because according to the present invention, certain steps can be performed in other sequences or simultaneously. Secondly, those skilled in the art should also know that the embodiments described in the specification are all preferred embodiments, and the actions and modules involved are not necessarily required by the present invention.

[0046] In the above embodiments, the description of each embodiment has its own emphasis. For parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0047] In the several embodiments provided by the present invention, it should be understood that the disclosed device can be implemented in other ways. For example, the device embodiments described above are only schematic, such as the division of the units, which is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, and the indirect coupling or communication connection of devices or units can be electrical or other forms.

[0048] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0049] In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0050] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including a number of instructions for a computer device (which can be a personal computer, a mobile terminal, a server or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), mobile hard disk, magnetic disk or optical disk and other media that can store program codes.

[0051] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. For those skilled in the art, the present invention may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A modular mathematical computing model combination system for engineering computing tasks, characterized by: The modular mathematical computing model combination system includes: A plurality of modular mathematical computing models, wherein the mathematical computing models at least include a basic model, a combination model and a scenario model, and the mathematical computing models include an interface for multi-parameter input and multi-parameter output; Wherein, a plurality of the mathematical calculation models can be visually combined in series or in parallel, and a combined calculation model can be constructed in the form of dragging to be used for the engineering calculation task; The basic model is a basic calculation unit, the combined model is a model including processes formed by combining the basic models, and the scenario model is oriented to engineering applications, and is a model including industry processes formed by re-identifying the combined model and adding data preprocessing links; Among them, in the series combination of multiple mathematical calculation models, the output parameters of the preceding mathematical calculation model can be used as input parameters of the subsequent mathematical calculation model.

2. The modular mathematical computing model combination system according to claim 1, characterized in that: The output parameter A of the mathematical calculation model can be used as the input parameter B of other mathematical calculation models after being preprocessed by function mapping f; B=f(A) Among them, A and B include numerical data, vector data, and image data.

3. The modular mathematical computing model combination system according to claim 1, characterized in that: The modular mathematical calculation model combination system also includes a configuration module, which is used for associative connection during the series or parallel combination of multiple mathematical calculation models.

4. The modular mathematical computing model combination system according to claim 3 is characterized in that: The configuration module is also used to set the output parameters, input parameter types and precision of the mathematical calculation model.

5. The modular mathematical computing model combination system according to claim 1, characterized in that: The basic model includes a statistical model, a planning model, and a differential model; the combination model includes a factor analysis model and a decision combination model; the scenario model includes a product performance factor analysis model. The modular mathematical computing model combination system also includes a permission configuration module, which is used for establishing, modifying and updating the mathematical computing model, as well as the permission control of a combination of multiple mathematical computing models.

6. The modular mathematical computing model combination system according to any one of claims 1 to 5, characterized in that: The modular mathematical calculation model combination system also includes a start module and a stop module; the start module is used to start the mathematical calculation model process in series or parallel combination; the stop module is used to stop the mathematical calculation model process in series or parallel combination.

7. A method for a modular mathematical computing model combination system as claimed in any one of claims 1 to 6, characterized in that: The method comprises, Step S1, selecting a modular mathematical calculation model from a candidate library, and setting the type, format, and precision of input parameters; Step S2, multiple mathematical calculation models are combined in series or in parallel to form a workflow, wherein input parameters and output parameters in the mathematical calculation models are associated and connected; Step S3, displaying the connection logic relationship of multiple mathematical calculation models and the output parameters of each mathematical calculation model through a display module.

8. The method according to claim 7, characterized in that The output parameters generated by multiple mathematical calculation models can be input into other mathematical calculation models as input parameters after preprocessing.

9. An electronic device, characterized in that: The method comprises a memory and a processor: the memory is used to store a computer program; the processor is used to implement the method according to any one of claims 7 to 8 when executing the computer program.

10. A machine-readable storage medium having instructions stored thereon, the instructions being used to enable a machine to execute the method according to any one of claims 7 to 8 of the present application.

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