Multi-scene coverage engineering data calculation method and equipment

Abstract

The invention discloses a multi-scene coverage engineering data calculation method and equipment, and relates to the technical field related to data processing, and the method comprises the steps: responding to an engineering data calculation request input by a user side; matching based on a formula database of a memory of the intelligent calculator to obtain a first calculation formula; obtaining a second calculation formula; constructing a collaborative computing tree until the Nth input data attribute of the Nth computing formula is the same as the computing input data attribute; and obtaining a calculation target data characteristic value and feeding back to a user side display interface. The technical problems that in existing engineering data calculation, calculation formulas are mutually isolated, it is difficult to cooperatively match and schedule multiple formulas for calculation according to data attributes, and then the engineering data calculation accuracy and calculation efficiency are insufficient are solved, efficient engineering data processing is achieved, and the engineering data calculation efficiency is improved. The technical effect of improving data calculation efficiency and calculation accuracy is achieved.

Description

Technical Field

[0001] The present application relates to the technical field related to data processing, and specifically to a method and device for calculating engineering data covering multiple scenarios. Background Art

[0002] In today's rapidly developing field of engineering technology, accurate calculation and efficient processing of data have become key factors in improving project efficiency and quality. With the continuous advancement of big data, cloud computing and artificial intelligence technologies, intelligent calculators, as a tool that integrates advanced computing algorithms and data processing capabilities, are gradually showing their unique advantages in the field of engineering data calculation. In particular, when faced with complex and changing engineering scenarios, traditional calculators have been unable to meet the needs of efficient and accurate data calculation. In existing engineering data calculations, when the attributes of the input data do not match the input requirements of the required calculation formula, manual tedious data conversion or re-searching for a suitable calculation formula is often required. Faced with complex engineering scenarios and diverse data calculation needs, choosing a suitable calculation formula is often a challenge, and it is impossible to achieve coordinated scheduling of multiple formulas, which makes engineering data calculation processing inefficient, thereby affecting the accuracy and consistency of data calculation.

[0003] Therefore, in the current technologies related to engineering data calculation, there are technical problems such as isolated calculation formulas, which make it difficult to coordinate and match multiple formulas according to data attributes for calculation, thus leading to insufficient accuracy and efficiency of engineering data calculation. Summary of the invention

[0004] The present application provides an engineering data calculation method and equipment covering multiple scenarios, thereby solving the technical problem that the calculation formulas in existing engineering data calculations are isolated from each other, making it difficult to coordinately match and schedule multiple formulas for calculations according to data attributes, which in turn leads to insufficient accuracy and efficiency in engineering data calculations. The application realizes efficient engineering data processing and achieves the technical effect of improving data calculation efficiency and accuracy.

[0005] The present application provides an engineering data calculation method covering multiple scenarios, and the method is applied to an intelligent calculator, which includes a server, including: responding to an engineering data calculation request input by a user, wherein the engineering data calculation request includes a calculation input data attribute and a calculation target data attribute; according to the calculation target data attribute, matching is performed based on a formula database in a memory of the intelligent calculator to obtain a first calculation formula; when the first input data attribute of the first calculation formula is different from the calculation input data attribute, matching is performed based on a formula database in a memory of the intelligent calculator according to the first input data attribute to obtain a second calculation formula; until the Nth input data attribute of the Nth calculation formula is the same as the calculation input data attribute, a collaborative calculation tree is constructed according to the Nth calculation formula until the second calculation formula and the first calculation formula; according to the collaborative calculation tree, the calculation input data characteristic value of the calculation input data attribute is processed to obtain the calculation target data characteristic value and feedback it to the user-side display interface.

[0006] In a possible implementation, the engineering data calculation method covering multiple scenarios also performs the following processing: when the first input data attribute of the first calculation formula is the same as the calculation input data attribute, the calculation input data characteristic value is processed according to the first calculation formula to obtain the calculation target data characteristic value; the calculation target data characteristic value is fed back to the user-end display interface.

[0007] In a possible implementation, the engineering data calculation method covering multiple scenarios also performs the following processing: obtaining the first input sub-attribute of the formula, the second input sub-attribute of the formula, and so on to the Qth input sub-attribute of the formula of the first input data attribute; obtaining the first calculation input sub-attribute, the second calculation input sub-attribute, and so on to the Mth calculation input sub-attribute of the calculation input data attribute; calculating the attribute overlap rate of the first input sub-attribute of the formula, the second input sub-attribute of the formula, and the first calculation input sub-attribute, the second calculation input sub-attribute, and so on to the Mth calculation input sub-attribute; when the attribute overlap rate is 1, the first input data attribute of the first calculation formula is deemed to be the same as the calculation input data attribute; when the attribute overlap rate is not 1, the first input data attribute of the first calculation formula is deemed to be different from the calculation input data attribute.

[0008] In a possible implementation, the engineering data calculation method covering multiple scenarios also performs the following processing: taking the first calculation formula as the root node, setting the second calculation formula as the child node of the first calculation formula, and generating a second-level leaf node, wherein the output of the child node will be used as the input of the parent node; until the N-1th calculation formula is traversed, the Nth calculation formula is grouped to obtain the grouping result of the Nth calculation formula, and the grouping result of the Nth calculation formula is set as the child node corresponding to the N-1th calculation formula, to generate N-level leaf nodes; based on the root node, the second-level leaf node and up to the N-level leaf node, the collaborative calculation tree is constructed.

[0009] In a possible implementation, the engineering data calculation method covering multiple scenarios also performs the following processing: when all the formulas in the formula database are traversed and a collaborative calculation tree that meets the engineering data calculation request cannot be generated, a mapping exception signal is generated; based on the mapping exception signal, an error mark is generated and displayed on the user-end display interface.

[0010] In a possible implementation, the engineering data calculation method covering multiple scenarios also performs the following processing: through the user terminal, configuring the mapping result data attributes, mapping cause data attributes and mapping calculation identifier; when the mapping calculation identifier is a mapping calculation linear formula, updating the formula database according to the mapping result data attributes, the mapping cause data attributes and the mapping calculation linear formula; when the mapping calculation identifier is a nonlinear mapping label, training the mapping model according to the mapping result data attributes and the mapping cause data attributes; updating the formula database according to the mapping model, the mapping result data attributes, the mapping cause data attributes and the mapping calculation linear formula.

[0011] In a possible implementation, the engineering data calculation method covering multiple scenarios also performs the following processing: collecting a mapping cause data attribute record data set and a mapping result data attribute record data set, and setting them as a mapping model construction data set; dividing the mapping model construction data set into L equal parts to obtain L groups of mapping model construction data; performing L times of extraction with replacement on the L groups of mapping model construction data to obtain a first mapping model construction data set, and training a first mapping sub-model; performing L times of extraction with replacement on the L groups of mapping model construction data to obtain a second mapping model construction data set, and training a second mapping sub-model; performing L times of extraction with replacement on the L groups of mapping model construction data to obtain a third mapping model construction data set, and training a third mapping sub-model; wherein the model topological structures of the first mapping sub-model, the second mapping sub-model and the third mapping sub-model are different; and obtaining the mapping model by fully connecting the outputs of the first mapping sub-model, the second mapping sub-model and the third mapping sub-model with the output mean.

[0012] The present application also provides an electronic device, comprising: a memory for storing executable instructions; and a processor for implementing an engineering data calculation method covering multiple scenarios when executing the executable instructions stored in the memory.

[0013] The engineering data calculation method and device proposed in this application, which covers multiple scenarios, responds to the engineering data calculation request input by the user end; matches the formula database based on the memory of the intelligent calculator to obtain the first calculation formula; obtains the second calculation formula; until the Nth input data attribute of the Nth calculation formula is the same as the calculation input data attribute, a collaborative calculation tree is constructed; the calculation target data characteristic value is obtained and fed back to the user end display interface. The technical problem that the calculation formulas in the existing engineering data calculation are isolated from each other, it is difficult to coordinate and match and schedule multiple formulas for calculation according to data attributes, which leads to insufficient accuracy and efficiency of engineering data calculation is solved, efficient engineering data processing is realized, and the technical effect of improving data calculation efficiency and accuracy is achieved. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] In order to more clearly illustrate the technical solution of the embodiment of the present disclosure, the accompanying drawings of the embodiment of the present disclosure will be briefly introduced below. A flow chart is used in the present application to illustrate the operations performed by the system according to the embodiment of the present application. It should be understood that the preceding or following operations are not necessarily performed accurately in order. On the contrary, various steps can be processed in reverse order or simultaneously as needed. At the same time, other operations can also be added to these processes, or one or more operations can be removed from these processes.

[0015] Figure 1 A schematic diagram of a flow chart of a method for calculating engineering data covering multiple scenarios provided in an embodiment of the present application;

[0016] Figure 2 A schematic diagram of the structure of an electronic device provided in an embodiment of the present application.

[0017] Description of the reference numerals: input device 401 , processor 402 , memory 403 , output device 404 . DETAILED DESCRIPTION

[0018] The above description is only an overview of the technical solution of the present application. In order to more clearly understand the technical means of the present application, it can be implemented in accordance with the contents of the specification. In order to make the above and other purposes, features and advantages of the present application more obvious and easy to understand, the specific implementation methods of the present application are listed below.

[0019] In order to make the purpose, technical solutions and advantages of the present application clearer, the present application will be further described in detail below in conjunction with the accompanying drawings. The described embodiments should not be regarded as limiting the present application. All other embodiments obtained by ordinary technicians in the field without making creative work are within the scope of protection of this application.

[0020] In the following description, reference is made to "some embodiments", which describe a subset of all possible embodiments, but it is understood that "some embodiments" may be the same subset or different subsets of all possible embodiments, and may be combined with each other without conflict, and the terms "first\second" involved are merely to distinguish similar objects and do not represent a specific ordering of objects. The terms "including" and "having" and any variations are intended to cover non-exclusive inclusions, for example, a process, method, system, product, or server that includes a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or modules that are not clearly listed or inherent to these processes, methods, products, or devices. Unless otherwise defined, all technical and scientific terms used herein have the same meaning as those generally understood by technicians in the technical field of this application. The terms used herein are for the purpose of describing the embodiments of the present application only.

[0021] The present application embodiment provides a method for calculating engineering data covering multiple scenarios, such as Figure 1 As shown, the method is applied to an intelligent calculator, and the intelligent calculator includes a server, including:

[0022] Step S100, responding to an engineering data calculation request input by a user, wherein the engineering data calculation request includes calculating input data attributes and calculating target data attributes.

[0023] Preferably, the engineering data calculation method covering multiple scenarios is applied to an intelligent calculator. The intelligent calculator includes a server, which is responsible for processing data calculation requests, executing calculation tasks and returning calculation results. Specifically, the server is responsible for receiving engineering data calculation requests from the user side (such as client applications of smart devices such as smartphones, tablets, computers, etc.), and matching and searching in the internally stored formula database based on the information in the request, finding the calculation formula suitable for the engineering data of the current calculation scenario, executing the calculation task, obtaining the calculation results and encapsulating the calculation results into a response message, and sending it back to the user side through the network for the user to view and use.

[0024] Preferably, the server of the intelligent calculator responds to the engineering data calculation request input by the user end. The engineering data calculation request includes two key parts, namely, calculation input data attributes and calculation target data attributes. Specifically, calculation input data attributes refer to a series of basic data input by the user through the user end (such as the application program interface of a computer, mobile phone or other smart device) when performing engineering data calculations, which describes the specific details of the engineering problem or scenario. For example, in the field of mechanical engineering, calculation input data attributes may include the size, material, and load of a part. In the field of civil engineering, they may include the physical properties of soil, the size and structure of a building, etc.; calculation target data attributes refer to the result data that the user hopes to obtain through calculation, which is the main goal of the user in performing engineering data calculations. Calculation target data attributes are usually related to the user's actual needs or the specific requirements of the engineering problem. For example, the user may want to know the stress distribution of a part, the load-bearing capacity of a building, or the yield of a chemical reaction. When entering a calculation request, the user will explicitly specify the target data attributes they want to calculate.

[0025] Step S200, according to the calculation target data attribute, matching is performed based on the formula database in the memory of the intelligent calculator to obtain a first calculation formula.

[0026] Preferably, matching is performed based on a formula database in a memory of an intelligent calculator according to the calculation target data attributes, wherein a formula database is stored in the memory of the intelligent calculator, and the formula database internally stores engineering data calculation formulas corresponding to various scenarios. Users can add and retrieve target formulas for engineering data calculation processing through a shared database, and these calculation formulas are classified and stored according to different calculation scenarios and target data attributes. Specifically, after receiving a calculation request, the server searches and matches in the formula database according to the calculation target data attributes specified by the user, and quickly and accurately finds the calculation formula related to the calculation target data attributes in the user request as the first calculation formula, which is used to process the calculation input data attributes provided by the user and obtain a calculation result, wherein the input data attributes of the first calculation formula do not necessarily completely match the calculation input data attributes provided by the user.

[0027] Furthermore, step S200 also includes updating the formula database, including step S210, configuring the mapping result data attributes, mapping cause data attributes and mapping calculation identifiers through the user terminal; step S220, when the mapping calculation identifier is a mapping calculation linear formula, updating the formula database according to the mapping result data attributes, the mapping cause data attributes and the mapping calculation linear formula; step S230, when the mapping calculation identifier is a nonlinear mapping label, training the mapping model according to the mapping result data attributes and the mapping cause data attributes; step S240, updating the formula database according to the mapping model, the mapping result data attributes, the mapping cause data attributes and the mapping calculation linear formula.

[0028] Preferably, the user configures the mapping result data attributes, mapping cause data attributes and mapping calculation identifiers through the user-side interface. The mapping result data attributes refer to the attributes of the result data desired to be obtained after calculation or mapping, such as data type, data range, precision, etc. The mapping cause data attributes refer to the attributes of the input data used for calculation or mapping, which also include data type, data range, etc. The mapping calculation identifier is a label used to identify the calculation type or method, such as a linear formula, a nonlinear model, etc.; when the mapping calculation identifier is a mapping calculation linear formula, according to the mapping result data attributes, mapping cause data attributes and mapping calculation linear formula configured by the user, the new linear formula is updated or added to the formula database, and the implementation Dynamic addition or update of linear formulas is realized; if the mapping calculation is identified as a nonlinear mapping label, a nonlinear mapping model is trained based on the mapping result data attributes and mapping cause data attributes configured by the user and based on the machine learning model (such as decision tree, neural network, support vector machine, etc.); then the formula database is updated according to the mapping model, mapping result data attributes, mapping cause data attributes and mapping calculation linear formula, that is, the relevant information of the nonlinear mapping model (such as model parameters, model structure, etc.) is added to the formula database in a way that can be stored and retrieved, so as to realize the comprehensive update of nonlinear mapping models and linear formulas, so that the formula database can support more complex computing needs.

[0029] Further, step S230 also includes step S231, collecting a mapping cause data attribute record data set and a mapping result data attribute record data set, and setting them as a mapping model construction data set; step S232, dividing the mapping model construction data set into L equal parts to obtain L groups of mapping model construction data; step S233, performing L times of extraction with replacement on the L groups of mapping model construction data to obtain a first mapping model construction data set, and training a first mapping sub-model; step S234, performing L times of extraction with replacement on the L groups of mapping model construction data to obtain a second mapping model construction data set, and training a second mapping sub-model; step S235, performing L times of extraction with replacement on the L groups of mapping model construction data to obtain a third mapping model construction data set, and training a third mapping sub-model; step S236, wherein the model topological structures of the first mapping sub-model, the second mapping sub-model and the third mapping sub-model are different; step S237, fully connecting the outputs of the first mapping sub-model, the second mapping sub-model and the third mapping sub-model with the output mean, to obtain the mapping model.

[0030] Preferably, a mapping cause data attribute record data set and a mapping result data attribute record data set are collected, which respectively represent the input (cause) and output (result) data sets for constructing a mapping model, and then the collected mapping model construction data set is equally divided into L parts to obtain L groups of mapping model construction data; L groups of mapping model construction data are subjected to L times of extraction with replacement, and each extraction obtains a data set, namely, a mapping model construction data set, wherein when there is replacement extraction, the same data sample may be selected multiple times in one extraction, or may not be selected at all, and L is a positive integer greater than 1. Specifically, a first mapping model construction data set, a second mapping model construction data set, and a third mapping model construction data set are extracted, and then based on a neural network, using The three mapping models are constructed with data sets and trained separately to obtain a first mapping sub-model, a second mapping sub-model and a third mapping sub-model, and the model topological structures of the first mapping sub-model, the second mapping sub-model and the third mapping sub-model are different, wherein the topological structure refers to the connection mode and hierarchy between nodes (such as neurons) in the model, and different topological structures may cause the model to produce different outputs under the same input, thereby increasing the diversity and generalization ability of the model; finally, their outputs are integrated through the output mean full connection method to obtain the final mapping model, that is, the output values ​​of the three sub-models are averaged as the output of the final model, so as to improve the accuracy and generalization ability of the final mapping model, which is particularly effective in dealing with complex data mapping problems.

[0031] Step S300: When the first input data attribute of the first calculation formula is different from the calculation input data attribute, matching is performed based on the formula database in the memory of the intelligent calculator according to the first input data attribute to obtain a second calculation formula.

[0032] Preferably, if the first input data attribute of the first calculation formula is different from the calculation input data attribute, matching is performed again in the formula database based on the first input data attribute. Specifically, if the server identifies a mismatch between the first input data attribute of the first calculation formula and the calculation input data attribute provided by the user, such as differences in data type, data range, data unit, etc., the server searches and matches again in the formula database based on the first input data attribute, that is, considering the relevant features of the first input data attribute to ensure that a formula matching the current calculation scenario and target data attribute is found, and a second calculation formula is obtained for processing the calculation input data attribute provided by the user to obtain a final calculation result, wherein the input data attribute of the second calculation formula may still not completely match the calculation input data attribute provided by the user.

[0033] Furthermore, step S300 also includes step S301, when the first input data attribute of the first calculation formula is the same as the calculation input data attribute, processing the calculation input data characteristic value according to the first calculation formula to obtain the calculation target data characteristic value; step S302, feeding back the calculation target data characteristic value to the user-end display interface.

[0034] Preferably, if the first input data attribute of the first calculation formula is exactly the same as the calculation input data attribute, the calculation input data characteristic value is directly processed according to the first calculation formula, that is, the server directly uses the first calculation formula to process the calculation input data characteristic value provided by the user, such as numerical calculation, logical operation, data conversion and other operations to obtain the calculation target data characteristic value. The calculation target data characteristic value represents the information or data that the user expects to obtain through calculation, and the calculation target data characteristic value is encapsulated by the server of the intelligent calculator and sent to the display interface of the user.

[0035] Further, step S300 also includes step S310, obtaining the first input sub-attribute of the formula, the second input sub-attribute of the formula, and up to the Qth input sub-attribute of the formula of the first input data attribute; step S320, obtaining the first calculation input sub-attribute, the second calculation input sub-attribute, and up to the Mth calculation input sub-attribute of the calculation input data attribute; step S330, calculating the attribute overlap rate of the first input sub-attribute of the formula, the second input sub-attribute of the formula, and the first calculation input sub-attribute, the second calculation input sub-attribute, and up to the Mth calculation input sub-attribute; step S340, when the attribute overlap rate is 1, the first input data attribute of the first calculation formula is deemed to be the same as the calculation input data attribute; step S350, when the attribute overlap rate is not 1, the first input data attribute of the first calculation formula is deemed to be different from the calculation input data attribute.

[0036] Preferably, for the first input data attribute of the first calculation formula, all its sub-attributes are obtained, that is, from the first input sub-attribute of the formula, the second input sub-attribute of the formula to the Qth input sub-attribute of the formula. Similarly, for the calculation input data attribute, all its sub-attributes are obtained, that is, from the first calculation input sub-attribute, the second calculation input sub-attribute to the Mth calculation input sub-attribute, wherein Q and M are both positive integers greater than or equal to 2, and then the overlap degree of the two groups of sub-attributes is compared. Specifically, it is achieved by calculating the attribute overlap rate, that is, calculating the ratio of the number of identical attributes in the two groups of sub-attributes to the total number of sub-attributes in the two groups, wherein the attribute overlap rate is a value between 0 and 1, indicating the degree of similarity or overlap between the two groups of attributes. According to the calculated attribute overlap rate, it is determined whether the first input data attribute of the first calculation formula is the same as the calculation input data attribute. If the attribute overlap rate is 1, that is, the two groups of sub-attributes are exactly the same, it is considered that the first input data attribute of the first calculation formula is the same as the calculation input data attribute; if the attribute overlap rate is not 1, that is, there is a difference between the two groups of sub-attributes, it is considered that the first input data attribute of the first calculation formula is different from the calculation input data attribute. By accurately calculating the attribute overlap rate, it is possible to accurately determine whether a given calculation formula is applicable to specific input data, thereby ensuring the accuracy and effectiveness of the calculation.

[0037] Step S400, until the Nth input data attribute of the Nth calculation formula is the same as the calculation input data attribute, a collaborative calculation tree is constructed according to the Nth calculation formula until the second calculation formula and the first calculation formula.

[0038] Preferably, after multiple iterations of searching and matching, until the Nth input data attribute of the Nth calculation formula is the same as the calculation input data attribute, a collaborative calculation tree is constructed according to these calculation formulas (from the Nth calculation formula to the second calculation formula and the first calculation formula). Specifically, starting from the first calculation formula, the matching of the input data attribute of each calculation formula with the calculation input data attribute is determined in turn. When the Nth input data attribute of the Nth calculation formula is the same as the calculation input data attribute, the iterative matching is stopped to obtain a calculation formula sequence, including the first calculation formula to the Nth calculation formula, and then this calculation formula sequence is regarded as a tree structure, in which each calculation formula is It is a node. According to the dependency of the calculation formula and the transitivity of the input data attributes, connections are established between nodes. In the collaborative calculation tree, starting from the root node (which may be the first calculation formula, depending on the matching process), the calculation order of each node is determined. According to the calculation order, the flow path of the data in the tree is determined to ensure that each node can obtain the input data it needs when calculating. Then, the calculation task of each calculation formula is executed collaboratively to ensure the accuracy and completeness of the data. When all calculation formulas are executed, the final calculation results are output to the user. The construction process of the collaborative calculation tree reflects the flexibility and efficiency of the intelligent calculator in handling complex calculation tasks. By iteratively matching and building a collaborative calculation tree, the intelligent calculator can find the calculation formula sequence that best suits the current calculation scenario, and execute the calculation task in the correct calculation order and path, so as to obtain accurate and reliable calculation results.

[0039] Furthermore, step S400 also includes step S410, taking the first calculation formula as the root node, setting the second calculation formula as the child node of the first calculation formula, and generating a second-level leaf node, wherein the output of the child node will be used as the input of the parent node; step S420, until the N-1th calculation formula is traversed, the Nth calculation formula is grouped to obtain the grouping result of the Nth calculation formula, and the grouping results of the Nth calculation formula are respectively set as the child nodes corresponding to the N-1th calculation formula to generate N-level leaf nodes; step S430, constructing the collaborative computing tree according to the root node, the second-level leaf node until the N-level leaf node.

[0040] Preferably, the first calculation formula is selected as the root node of the collaborative calculation tree, representing the starting point of the entire calculation process, and the second calculation formula is set as the child node of the first calculation formula to form a secondary structure. The output of the second calculation formula will be used as part of the input of the first calculation formula. This process is continued and traversed to the N-1th calculation formula. For each new calculation formula, it is grouped (for example, based on the logical requirements of the calculation task, the optimization of the data flow, the allocation of computing resources, etc.) and set as the child node of the previous calculation formula. Each calculation formula becomes the child node of its parent node, and its own output is used as the input of the parent node calculation formula, thereby forming a continuously expanding tree structure. When traversing to the Nth calculation formula, it is grouped and the grouped Nth calculation formula is set as the child node corresponding to the N-1th calculation formula to generate N-level leaf nodes. Then the generated root node, secondary leaf node, ... N-level leaf nodes are connected to form a complete collaborative calculation tree, which clearly represents the hierarchical relationship and input-output dependency between the various calculation formulas, allowing complex computing tasks to be decomposed into multiple smaller, more manageable sub-tasks, and efficiently processed through a hierarchical structure.

[0041] Furthermore, step S400 also includes step S440, when all the formulas in the formula database are traversed and a collaborative computing tree that meets the engineering data calculation request cannot be generated, a mapping exception signal is generated; step S450, based on the mapping exception signal, an error mark is generated and displayed on the user-end display interface.

[0042] Preferably, if a suitable formula combination cannot be found after traversing the entire formula database when building a collaborative computing tree that satisfies the engineering data calculation request, a mapping exception signal will be generated. Specifically, a comprehensive search of the formula database is performed to retrieve and match formulas that can be used to build a collaborative computing tree from the formula database. If a formula combination that can fully meet the engineering data calculation request cannot be found after traversing the entire formula database, a valid collaborative computing tree cannot be built, and a mapping exception signal is generated. This mapping exception signal is an internal flag used to indicate that all possible formula combinations have been tried, but a solution that meets the request cannot be found. An error indicator is then generated based on the mapping exception signal and displayed on the display interface of the user end, which is used to clearly indicate to the user the reason why the calculation request cannot be met. The user can intuitively understand the reason for the failure of the calculation request and take corresponding measures accordingly, such as re-entering data or modifying the calculation request.

[0043] Step S500: Process the calculation input data characteristic value of the calculation input data attribute according to the collaborative calculation tree, obtain the calculation target data characteristic value and feed it back to the user terminal display interface.

[0044] Preferably, the calculation input data characteristic values ​​of the calculation input data attributes are processed according to the constructed collaborative calculation tree, and finally the calculation target data characteristic values ​​are obtained, and this value is fed back to the user-side display interface. Specifically, the specific calculation input data characteristic values ​​are extracted from the calculation input data attributes received from the user side, such as data in various forms such as numbers, texts, and images, which represent the original data that the user wants to calculate. Then, these calculation input data characteristic values ​​are input into each calculation formula node for processing according to the order and path defined in the collaborative calculation tree. Each calculation formula node calculates the input data characteristic value, and this continues until the end node of the collaborative calculation tree, that is, the node where the final calculation target data characteristic value is located, and outputs the calculation target data characteristic value. The calculation target data characteristic value is the result that the user expects to obtain by calculating through the intelligent calculator. The server of the intelligent calculator will organize and package these calculation target data characteristic values ​​and send them to the user-side display interface through the network.

[0045] Figure 2 1 is a schematic diagram of the structure of an electronic device provided by an embodiment of the present invention, showing a block diagram of an exemplary electronic device suitable for implementing an implementation of the present invention. Figure 2 The electronic device shown is only an example and should not bring any limitation to the functions and scope of use of the embodiments of the present invention. The electronic device is in the form of a general computing device, and its components may include but are not limited to an input device 401, a processor 402, a memory 403, and an output device 404. Among them, the processor 402 may be one or more; the memory 403 may include a computer-readable medium and at least one program product, and the program product has a set (at least one) of program modules, which are configured to perform the functions of each embodiment of the present application.

[0046] The memory 403 shown in the embodiment of the present invention may adopt any combination of one or more computer-readable media; the computer-readable storage medium may be, but is not limited to, an infrared, semiconductor system, device or component, or any combination of the above, for storing software programs, computer executable programs and modules, such as the program instructions / modules corresponding to the engineering data calculation method for multi-scene coverage in the embodiment of the present invention. The processor 402 executes various functional applications and data processing of the computer device by running the software programs, instructions and modules stored in the memory 403, thereby realizing the above-mentioned engineering data calculation method for multi-scene coverage.

[0047] The engineering data calculation device covering multiple scenarios provided by the embodiment of the present invention can execute the engineering data calculation method covering multiple scenarios provided by any embodiment of the present invention, and has the corresponding functional modules and beneficial effects of the execution method.

[0048] Although the present application makes various references to certain modules in the system according to the embodiments of the present application, any number of different modules may be used and run on the user terminal and / or server, and the various units and modules included are only divided according to functional logic, but are not limited to the above division, as long as the corresponding functions can be achieved; in addition, the specific names of the functional units are only for the convenience of distinguishing each other, and are not used to limit the scope of protection of the present invention.

[0049] The above specific implementations do not constitute a limitation on the protection scope of this application. It should be understood by those skilled in the art that various modifications, combinations and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions and improvements made within the spirit and principles of this application should be included in the protection scope of this application.

Claims

1. A method for calculating engineering data covering multiple scenarios, characterized in that: Applied to an intelligent calculator, the intelligent calculator includes a server, including: Responding to an engineering data calculation request input by a user, wherein the engineering data calculation request includes calculation input data attributes and calculation target data attributes; According to the calculation target data attribute, matching is performed based on a formula database in the memory of the intelligent calculator to obtain a first calculation formula; When the first input data attribute of the first calculation formula is different from the calculation input data attribute, matching is performed based on the formula database in the memory of the intelligent calculator according to the first input data attribute to obtain a second calculation formula; Until the Nth input data attribute of the Nth calculation formula is the same as the calculation input data attribute, a collaborative calculation tree is constructed according to the Nth calculation formula up to the second calculation formula and the first calculation formula; The calculation input data characteristic value of the calculation input data attribute is processed according to the collaborative calculation tree to obtain the calculation target data characteristic value which is fed back to the user terminal display interface.

2. The engineering data calculation method for multi-scenario coverage according to claim 1, characterized in that: Also includes: When the first input data attribute of the first calculation formula is the same as the attribute of the calculation input data, processing the characteristic value of the calculation input data according to the first calculation formula to obtain the characteristic value of the calculation target data; The calculated target data characteristic value is fed back to the user terminal display interface.

3. The engineering data calculation method for multi-scenario coverage according to claim 1, characterized in that: When the first input data attribute of the first calculation formula is different from the calculation input data attribute, it includes: Obtaining a formula first input sub-attribute, a formula second input sub-attribute, and so on to a formula Qth input sub-attribute of the first input data attribute; Obtaining a first calculation input sub-attribute, a second calculation input sub-attribute, and finally an Mth calculation input sub-attribute of the calculation input data attribute; Calculate the attribute overlap rate of the first input sub-attribute of the formula, the second input sub-attribute of the formula up to the Qth input sub-attribute of the formula, and the first calculation input sub-attribute, the second calculation input sub-attribute up to the Mth calculation input sub-attribute; When the attribute overlap rate is 1, it is considered that the first input data attribute of the first calculation formula is the same as the calculation input data attribute; When the attribute overlap rate is not 1, it is considered that the first input data attribute of the first calculation formula is different from the calculation input data attribute.

4. The engineering data calculation method for multi-scenario coverage according to claim 1, characterized in that: Until the Nth input data attribute of the Nth calculation formula is the same as the calculation input data attribute, constructing a collaborative calculation tree according to the Nth calculation formula until the second calculation formula and the first calculation formula, including: Taking the first calculation formula as the root node, setting the second calculation formula as the child node of the first calculation formula, and generating a secondary leaf node, wherein the output of the child node will be used as the input of the parent node; Until the N-1th calculation formula is traversed, the Nth calculation formula is grouped to obtain the Nth calculation formula grouping result, and the Nth calculation formula grouping result is set as the child node corresponding to the N-1th calculation formula to generate N-level leaf nodes; The collaborative computing tree is constructed according to the root node, the second-level leaf nodes, and up to the N-level leaf nodes.

5. The engineering data calculation method for multi-scenario coverage according to claim 1, characterized in that: Also includes: When all the formulas in the formula database are traversed and a collaborative calculation tree that satisfies the engineering data calculation request cannot be generated, a mapping abnormality signal is generated; An error indicator is generated according to the mapping abnormality signal and displayed on the user terminal display interface.

6. The engineering data calculation method for multi-scenario coverage according to claim 1, characterized in that: The formula database updating step comprises: Through the user end, configure the mapping result data attributes, mapping cause data attributes and mapping calculation identifier; When the mapping calculation identifier is a mapping calculation linear formula, the formula database is updated according to the mapping result data attribute, the mapping cause data attribute and the mapping calculation linear formula; When the mapping calculation identifier is a nonlinear mapping label, training a mapping model according to the mapping result data attribute and the mapping cause data attribute; The formula database is updated according to the mapping model, the mapping result data attribute, the mapping cause data attribute and the mapping calculation linear formula.

7. The engineering data calculation method for multi-scenario coverage according to claim 6, characterized in that: When the mapping calculation identifier is a nonlinear mapping label, training a mapping model according to the mapping result data attribute and the mapping cause data attribute includes: Collect a data set recording the attribute of the mapping cause data and a data set recording the attribute of the mapping result data, and set them as a data set for mapping model construction; Divide the mapping model construction data set into L equal parts to obtain L groups of mapping model construction data; Perform L extractions with replacement on the L groups of mapping model construction data to obtain a first mapping model construction data set, and train a first mapping sub-model; Perform L extractions with replacement on the L groups of mapping model construction data to obtain a second mapping model construction data set, and train a second mapping sub-model; Perform L extractions with replacement on the L groups of mapping model construction data to obtain a third mapping model construction data set, and train a third mapping sub-model; Wherein, the model topological structures of the first mapping sub-model, the second mapping sub-model and the third mapping sub-model are different; The outputs of the first mapping sub-model, the second mapping sub-model and the third mapping sub-model are fully connected with the output mean to obtain the mapping model.

8. An electronic device, characterized in that: The electronic device comprises: A memory for storing executable instructions; A processor is used to implement the engineering data calculation method covering multiple scenarios as described in any one of claims 1 to 7 when executing the executable instructions stored in the memory.

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