Engineering data calculation method and device for multi-scenario coverage

Abstract

The present invention discloses a method and device for engineering data calculation with multi-scenario coverage, relating to the technical field of data processing. The method includes: responding to an engineering data calculation request input by a user terminal; performing matching based on a formula database in the memory of an intelligent calculator to obtain a first calculation formula; obtaining a second calculation formula; 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; obtaining a calculation target data eigenvalue and feeding it back to the display interface of the user terminal. It solves the technical problem that existing engineering data calculations have isolated calculation formulas, making it difficult to perform operations by coordinating and matching multiple formulas according to data attributes, thereby resulting in insufficient accuracy and calculation efficiency of engineering data calculations, realizes efficient engineering data processing, and achieves the technical effect of improving data calculation efficiency and calculation accuracy.

Description

Technical Field

[0001] This application relates to the technical field of data processing, and specifically relates to an engineering data calculation method and device covering multiple scenarios. Background Art

[0002] In the rapidly developing field of engineering technology today, the accurate calculation and efficient processing of data have become key factors in improving project efficiency and quality. With the continuous progress of big data, cloud computing, and artificial intelligence technologies, as an integrated tool with advanced calculation algorithms and data processing capabilities, intelligent calculators are gradually showing their unique advantages in the field of engineering data calculation. Especially when facing complex and changeable engineering scenarios, traditional calculators are difficult to meet the requirements 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, it is often necessary to manually perform cumbersome data conversion or search for a suitable calculation formula again. Facing complex engineering scenarios and diverse data calculation requirements, selecting a suitable calculation formula is often a challenge, and the coordinated scheduling operation of multiple formulas cannot be achieved, resulting in low efficiency of engineering data calculation and processing, and thus affecting the accuracy and coherence of data calculation.

[0003] Therefore, in the current related technologies of engineering data calculation, there are technical problems that calculation formulas are isolated from each other, it is difficult to coordinate and match multiple formulas for operation according to data attributes, and thus the accuracy and calculation efficiency of engineering data calculation are insufficient. Summary of the Invention

[0004] By providing an engineering data calculation method and device covering multiple scenarios, this application solves the technical problems existing in the existing engineering data calculation that calculation formulas are isolated from each other, it is difficult to coordinate and match multiple formulas for operation according to data attributes, and thus the accuracy and calculation efficiency of engineering data calculation are insufficient, realizes efficient engineering data processing, and achieves the technical effects of improving data calculation efficiency and calculation accuracy.

[0005] The present application provides an engineering data calculation method for multi-scenario coverage. The method is applied to an intelligent calculator, and the intelligent calculator includes a server, and includes: responding to an engineering data calculation request input by a user terminal, where the engineering data calculation request includes calculation input data attributes and calculation target data attributes; based on the calculation target data attributes, performing matching on the 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 attributes, performing matching on the formula database in the memory of the intelligent calculator based on 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 attributes, constructing a collaborative calculation tree according to the Nth calculation formula, the second calculation formula, and the first calculation formula; processing the calculation input data feature values of the calculation input data attributes according to the collaborative calculation tree to obtain calculation target data feature values and feeding them back to the display interface of the user terminal.

[0006] In a possible implementation manner, the engineering data calculation method for multi-scenario coverage further performs the following processing: when the first input data attribute of the first calculation formula is the same as the calculation input data attributes, processing the calculation input data feature values according to the first calculation formula to obtain the calculation target data feature values; feeding back the calculation target data feature values to the display interface of the user terminal.

[0007] In a possible implementation manner, the engineering data calculation method for multi-scenario coverage further performs the following processing: obtaining 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 for the first input data attribute; obtaining the first calculation input sub-attribute, the second calculation input sub-attribute, up to the Mth calculation input sub-attribute of the calculation input data attributes; calculating the attribute coincidence rate between 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 coincidence 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 attributes; when the attribute coincidence 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 attributes.

[0008] In a possible implementation manner, the engineering data calculation method for multi-scenario coverage further performs the following processing: using the first calculation formula as the root node, setting the second calculation formula as a child node of the first calculation formula to generate second-level leaf nodes, where the output of the child node serves as the input of the parent node; until the (N-1)th calculation formula is traversed, grouping the Nth calculation formula to obtain the grouping result of the Nth calculation formula, and respectively setting the grouping result of the Nth calculation formula as the child node of the corresponding (N-1)th calculation formula to generate N-level leaf nodes; constructing the collaborative calculation tree according to the root node, the second-level leaf nodes up to the N-level leaf nodes.

[0009] In a possible implementation manner, the engineering data calculation method for multi-scenario coverage further performs the following processing: when all the formulas in the formula database have been traversed and a collaborative calculation tree that meets the engineering data calculation request cannot be generated, generating a mapping exception signal; generating an error flag according to the mapping exception signal and displaying it on the display interface of the user terminal.

[0010] In a possible implementation manner, the engineering data calculation method for multi-scenario coverage further performs the following processing: configuring the mapped result data attribute, the mapped cause data attribute, and the mapping calculation identifier through the user terminal; when the mapping calculation identifier is a mapping calculation linear formula, updating the formula database according to the mapped result data attribute, the mapped cause data attribute, and the mapping calculation linear formula; when the mapping calculation identifier is a non-linear mapping label, training a mapping model according to the mapped result data attribute and the mapped cause data attribute; updating the formula database according to the mapping model, the mapped result data attribute, the mapped cause data attribute, and the mapping calculation linear formula.

[0011] In a possible implementation manner, the engineering data calculation method for multi-scenario coverage further performs the following processing: collecting the mapped cause data attribute record data set and the mapped result data attribute record data set, and setting them as the mapping model construction data set; equally dividing the mapping model construction data set into L parts to obtain L groups of mapping model construction data; performing L times of sampling 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 sampling 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 sampling 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; where the model topological structures of the first mapping sub-model, the second mapping sub-model, and the third mapping sub-model are different; 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.

[0012] The present application also provides an electronic device, including: a memory for storing executable instructions; a processor for implementing an engineering data calculation method with multi-scenario coverage when executing the executable instructions stored in the memory.

[0013] It is intended to respond to an engineering data calculation request input by a user terminal through the engineering data calculation method and device with multi-scenario coverage proposed in the present application; perform matching based on the formula database in the memory of the intelligent calculator to obtain a first calculation formula; 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, construct a collaborative calculation tree; obtain the calculation target data characteristic value and feedback it to the user terminal display interface. This solves the technical problem that existing engineering data calculations have isolated calculation formulas and it is difficult to coordinately match and schedule multiple formulas for operation according to data attributes, resulting in insufficient accuracy and calculation efficiency of engineering data calculations. It realizes efficient engineering data processing and achieves the technical effect of improving data calculation efficiency and calculation accuracy. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] In order to more clearly illustrate the technical solutions of the embodiments of the present disclosure, the drawings of the embodiments of the present disclosure will be briefly introduced below. Flowcharts are used in the present application to illustrate the operations performed by the systems according to the embodiments of the present application. It should be understood that the operations described above or below do not necessarily need to be executed precisely in sequence. On the contrary, according to needs, they can be executed in reverse order or simultaneously. At the same time, other operations can also be added to these processes, or one or several operations can be removed from these processes.

[0015] Figure 1 It is a schematic flowchart of the engineering data calculation method with multi-scenario coverage provided by the embodiments of the present application;

[0016] Figure 2 It is a schematic structural diagram of an electronic device provided by the embodiments of the present application.

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

[0018] The above description is only an overview of the technical solutions of the present application. In order to be able to understand the technical means of the present application more clearly, it can be implemented according to the content of the description. And in order to make the above and other purposes, features and advantages of the present application more obvious and understandable, the following specifically illustrates the specific embodiments of the present application.

[0019] To make the objectives, technical solutions and advantages of this application clearer, the following will further describe this application in detail with reference to the accompanying drawings. The described embodiments should not be regarded as limitations to this application. All other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall 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. However, it can be understood that "some embodiments" can be the same subset or different subsets of all possible embodiments and can be combined with each other without conflict. The terms "first / second" involved are only used to distinguish similar objects and do not represent a specific order for the objects. The terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusion. For example, a process, method, system, product or server that includes a series of steps or units does not necessarily have to be limited to those steps or units clearly listed, but may include other steps or modules that are not clearly listed or are inherent to these processes, methods, products or devices. Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by those skilled in the technical field to which this application belongs. The terms used herein are only for the purpose of describing the embodiments of this application.

[0021] Embodiments of this application provide an engineering data calculation method for multi-scenario coverage, such as Figure 1 shown, the method is applied to an intelligent calculator, and the intelligent calculator includes a server, including:

[0022] Step S100, in response to an engineering data calculation request input by the user terminal, where the engineering data calculation request includes calculation input data attributes and calculation target data attributes.

[0023] Preferably, the engineering data calculation method for multi-scenario coverage is applied to an intelligent calculator. The intelligent calculator includes a server that 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 terminal (such as client applications of intelligent devices such as smartphones, tablets, and computers), and according to the information in the requests, performing matching and searching in the formula database stored internally to find a calculation formula applicable to the engineering data in the current calculation scenario, executing the calculation task, obtaining the calculation result, encapsulating the calculation result into a response message, and sending it back to the user terminal 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 terminal. This engineering data calculation request includes two key parts: the calculation input data attribute and the calculation target data attribute. Specifically, the calculation input data attribute refers to a series of basic data input by the user through the user terminal (such as the application program interface of intelligent devices like computers and mobile phones) when performing engineering data calculations, which describes the specific details of the engineering problem or scenario. For example, in the field of mechanical engineering, the calculation input data attributes may include the dimensions, materials, and loads of parts; in the field of civil engineering, they may include the physical properties of the soil, the dimensions and structure of the building, etc. The calculation target data attribute refers to the result data that the user hopes to obtain through the calculation and is the main goal of the user's engineering data calculation. The calculation target data attribute is 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 certain part, the load-bearing capacity of a certain building, or the yield of a certain chemical reaction, etc. When inputting the calculation request, the user will clearly specify the calculation target data attribute they want to calculate.

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

[0026] Preferably, based on the calculation target data attribute, perform matching in the formula database of the memory of the intelligent calculator. Among them, the memory of the intelligent calculator stores a formula database, and this formula database internally stores the engineering data calculation formulas corresponding to various scenarios. Users can add and retrieve target formulas through the shared database for engineering data calculation processing. These calculation formulas are classified and stored according to different calculation scenarios and target data attributes. Specifically, after receiving the calculation request, the server will search and match in the formula database according to the calculation target data attribute specified by the user, quickly and accurately find the calculation formula related to the calculation target data attribute in the user's request as the first calculation formula, which is used to process the calculation input data attributes provided by the user and obtain the calculation result. Among them, the input data attributes of the first calculation formula do not necessarily exactly match the calculation input data attributes provided by the user.

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

[0028] Preferably, the user configures the mapped result data attributes, the mapped cause data attributes, and the mapping calculation identifier through the user terminal interface. The mapped result data attributes refer to the attributes of the result data that is expected to be obtained after calculation or mapping, such as data type, data range, precision, etc. The mapped 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 non-linear model, etc. When the mapping calculation identifier is a mapping calculation linear formula, a new linear formula is updated or added to the formula database according to the mapped result data attributes, the mapped cause data attributes, and the mapping calculation linear formula configured by the user, realizing the dynamic addition or update of the linear formula. If the mapping calculation identifier is a non-linear mapping label, a non-linear mapping model is trained based on the machine learning model (such as decision tree, neural network, support vector machine, etc.) according to the mapped result data attributes and the mapped cause data attributes configured by the user. Then, the formula database is updated according to the mapping model, the mapped result data attributes, the mapped cause data attributes, and the mapping calculation linear formula, that is, the relevant information (such as model parameters, model structure, etc.) of this non-linear mapping model is added to the formula database in a way that can be stored and retrieved, realizing the comprehensive update of the non-linear mapping model and the linear formula, so that the formula database can support more complex calculation requirements.

[0029] Further, step S230 further includes step S231, collecting a mapping cause data attribute record data set and a mapping effect data attribute record data set, and setting them as a mapping model construction data set; step S232, equally dividing the mapping model construction data set into L parts to obtain L groups of mapping model construction data; step S233, performing L times of sampling 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 sampling 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 sampling 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 topologies 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 an output mean to obtain the mapping model.

[0030] Preferably, the mapping cause data attribute record data set and the mapping effect data attribute record data set are collected, which respectively represent the data sets of the input (cause) and output (effect) for constructing the mapping model. Then, the collected mapping model construction data set is equally divided into L parts to obtain L groups of mapping model construction data; L times of sampling with replacement are performed on the L groups of mapping model construction data, and each sampling results in a data set, that is, a mapping model construction data set. When sampling with replacement, the same data sample may be selected multiple times in one sampling or may not be selected at all. 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 obtained. Then, based on a neural network, these three mapping model construction data sets are used for training respectively to obtain a first mapping sub-model, a second mapping sub-model, and a third mapping sub-model. And the model topologies of the first mapping sub-model, the second mapping sub-model, and the third mapping sub-model are different. Among them, the topology refers to the connection method and hierarchical structure between nodes (such as neurons) in the model. Different topologies 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 by the method of fully connecting with an output mean 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 to improve the accuracy and generalization ability of the final mapping model, which is particularly effective when 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, match based on the first input data attribute in the formula database of the memory of the intelligent calculator 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, match again in the formula database according to 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 different data types, data ranges, data units, etc., the server searches and matches again in the formula database according to the first input data attribute, that is, considers the relevant characteristics of the first input data attribute to ensure finding a formula that matches the current calculation scenario and the target data attribute, and obtains a second calculation formula for processing the calculation input data attribute provided by the user to obtain the final calculation result. Among them, the input data attribute of the second calculation formula may still not fully match the calculation input data attribute provided by the user.

[0033] Further, step S300 further includes step S301, when the first input data attribute of the first calculation formula is the same as the calculation input data attribute, process the calculation input data characteristic value according to the first calculation formula to obtain the calculation target data characteristic value; step S302, feedback the calculation target data characteristic value to the display interface of the user terminal.

[0034] Preferably, if the first input data attribute of the first calculation formula is exactly the same as the calculation input data attribute, directly process the calculation input data characteristic value 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 various operations such as numerical calculation, logical operation, data conversion, etc., 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 the 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 terminal.

[0035] Further, step S300 further includes step S310 of obtaining the first input sub-property, the second input sub-property of the formula, up to the Q-th input sub-property of the formula for the first input data property; step S320 of obtaining the first calculation input sub-property, the second calculation input sub-property of the calculation input data property, up to the M-th calculation input sub-property; step S330 of calculating the property coincidence rate between the first input sub-property of the formula, the second input sub-property of the formula, up to the Q-th input sub-property of the formula, and the first calculation input sub-property, the second calculation input sub-property, up to the M-th calculation input sub-property; step S340 of, when the property coincidence rate is 1, considering that the first input data property of the first calculation formula is the same as the calculation input data property; step S350 of, when the property coincidence rate is not 1, considering that the first input data property of the first calculation formula is different from the calculation input data property.

[0036] Preferably, for the first input data property of the first calculation formula, all its sub-properties are obtained, that is, from the first input sub-property of the formula, the second input sub-property of the formula, up to the Q-th input sub-property of the formula. Similarly, for the calculation input data property, all its sub-properties are obtained, that is, from the first calculation input sub-property, the second calculation input sub-property, up to the M-th calculation input sub-property, where Q and M are both positive integers greater than or equal to 2. Then, the coincidence degree of these two groups of sub-properties is compared. Specifically, it is achieved by calculating the property coincidence rate, that is, calculating the ratio of the number of identical properties in the two groups of sub-properties to the total number of the two groups of sub-properties. Among them, the property coincidence rate is a value between 0 and 1, indicating the degree of similarity or coincidence between the two groups of properties. According to the calculated property coincidence rate, it is judged whether the first input data property of the first calculation formula is the same as the calculation input data property. If the property coincidence rate is 1, that is, the two groups of sub-properties are exactly the same, it is considered that the first input data property of the first calculation formula is the same as the calculation input data property; if the property coincidence rate is not 1, that is, there are differences between the two groups of sub-properties, it is considered that the first input data property of the first calculation formula is different from the calculation input data property. By accurately calculating the property coincidence rate, it is accurately judged whether a given calculation formula is applicable to specific input data, thus ensuring the accuracy and effectiveness of the calculation.

[0037] Step S400, until the N-th input data property of the N-th calculation formula is the same as the calculation input data property, construct a collaborative calculation tree according to the N-th calculation formula, the second calculation formula, and the first calculation formula.

[0038] Preferably, after multiple iterative searches and matches, 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 situation between the input data attribute of each calculation formula and 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, and a calculation formula sequence is obtained, including the first calculation formula to the Nth calculation formula. Then, this calculation formula sequence is regarded as a tree structure, where each calculation formula is a node. According to the dependency relationship of the calculation formulas and the transitivity of the input data attributes, connections are established between the 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 data flow path in the tree is determined to ensure that each node can obtain the input data it needs when calculating. Then, the calculation tasks of each calculation formula are executed collaboratively to ensure the accuracy and integrity of the data. When all the calculation formulas are executed, the final calculation result is output to the user. The construction process of the collaborative calculation tree reflects the flexibility and efficiency of the intelligent calculator in processing complex calculation tasks. Through iterative matching and constructing the collaborative calculation tree, the intelligent calculator can find the most suitable calculation formula sequence for the current calculation scenario and execute the calculation tasks according to the correct calculation order and path, thereby obtaining accurate and reliable calculation results.

[0039] Further, step S400 further 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 to generate a secondary leaf node, where the output of the child node will be used as the input of the parent node; step S420, until the (N - 1)th calculation formula is traversed, grouping the Nth calculation formula to obtain the grouping result of the Nth calculation formula, and respectively setting the grouping result of the Nth calculation formula as the child node of the corresponding (N - 1)th calculation formula to generate an N-level leaf node; step S430, constructing the collaborative calculation tree according to the root node, the secondary leaf node until the N-level leaf node.

[0040] Preferably, select the first calculation formula as the root node of the collaborative calculation tree, representing the starting point of the entire calculation process. Set the second calculation formula as the child node of the first calculation formula to form a two-level structure. The output of the second calculation formula will be used as part of the input of the first calculation formula. Continue this process until the (N - 1)-th calculation formula is traversed. For each new calculation formula, group it (for example, group it based on the logical requirements of the calculation task, the optimization of the data flow, the allocation of computing resources, etc.) and set it as the child node of the previous calculation formula. Each calculation formula becomes the child node of its parent node, and at the same time, its own output is used as the input of the parent node calculation formula, thus forming an expanding tree structure. When the N-th calculation formula is traversed, group it and set the grouped N-th calculation formula as the child node of the corresponding (N - 1)-th calculation formula to generate N-level leaf nodes. Then connect the generated root node, two-level leaf nodes, …… N-level leaf nodes to form a complete collaborative calculation tree, which clearly shows the hierarchical relationship and input-output dependency relationship between each calculation formula, allows complex calculation tasks to be decomposed into multiple smaller and more manageable subtasks, and is efficiently processed through a hierarchical structure.

[0041] Further, step S400 further includes step S440, when all the formulas in the formula database have been traversed and a collaborative calculation tree that meets the engineering data calculation request cannot be generated, generate a mapping exception signal; step S450, generate an error flag according to the mapping exception signal and display it on the display interface of the user terminal.

[0042] Preferably, if when constructing a collaborative calculation tree that meets the engineering data calculation request, after traversing the entire formula database, no suitable formula combination can still be found, a mapping exception signal will be generated. Specifically, conduct a comprehensive search of the formula database, retrieve and match the formulas in the formula database that can be used to construct the collaborative calculation tree. If after traversing the entire formula database, no formula combination that can fully meet the engineering data calculation request can still be found, an effective collaborative calculation tree cannot be constructed, and a mapping exception signal will be generated. This mapping exception signal is an internal flag used to indicate that all possible formula combinations have been tried, but no solution that meets the request can still be found. Then generate an error flag according to the mapping exception signal and display it on the display interface of the user terminal to clearly indicate to the user the reason why the calculation request cannot be satisfied. The user can then 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 feature values of the calculation input data attributes according to the collaborative calculation tree, and obtain the calculation target data feature values and feedback them to the display interface of the user terminal.

[0044] Preferably, the calculated input data feature values of the calculated input data attributes are processed according to the already constructed collaborative computing tree, and finally the calculated target data feature values are obtained and fed back to the user terminal display interface. Specifically, from the calculated input data attributes received from the user terminal, specific calculated input data are extracted. These calculated input data feature values, such as data in various forms like numerical values, texts, images, etc., represent the original data that the user hopes to calculate. Then, these calculated input data feature values are input into each calculation formula node for processing in the order and path defined in the collaborative computing tree. Each calculation formula node calculates the input data feature values until the end node of the collaborative computing tree, that is, the node where the final calculated target data feature values are located, and outputs the calculated target data feature values. The calculated target data feature values are the results that the user expects to obtain through the intelligent calculator. The server of the intelligent calculator will organize and encapsulate these calculated target data feature values and send them to the user terminal display interface through the network.

[0045] Figure 2 FIG. 5 is a schematic structural diagram of an electronic device provided by an embodiment of the present invention, showing a block diagram of an exemplary electronic device suitable for implementing the embodiments of the present invention. Figure 2 The electronic device shown is merely an example and should not impose any limitation on the functions and usage scope of the embodiments of the present invention. The electronic device is presented in the form of a general-purpose 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 this program product has a set (at least one) of program modules, and these program modules are configured to execute the functions of the embodiments of the present application.

[0046] The memory 403 shown in the embodiments 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, infrared rays, semiconductor systems, devices or components, or any combination of the above, for storing software programs, computer-executable programs, and modules, such as the program instructions / modules corresponding to the multi-scenario coverage engineering data calculation method in the embodiments 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, that is, implements the above multi-scenario coverage engineering data calculation method.

[0047] The engineering data calculation device with multi-scenario coverage provided by the embodiments of the present invention can execute the engineering data calculation method with multi-scenario coverage provided by any embodiment of the present invention, and has the corresponding functional modules and beneficial effects for executing the method.

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

[0049] The above specific embodiments do not constitute a limitation on the protection scope of the present application. Those skilled in the art should understand 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 principle of the present application shall be included within the protection scope of the present 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; Each calculation formula is a node. Connections are established between nodes based on the dependency of the calculation formula and the transitivity of the input data attributes. In the collaborative calculation tree, the calculation order of each node is determined starting from the root node. Based on 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 during calculation, and collaboratively execute the calculation tasks of each calculation formula to ensure the accuracy and integrity of the data. The root node depends on the matching process; 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 to the Qth input sub-attribute of the formula, and the first calculated input sub-attribute, the second calculated input sub-attribute to the Mth calculated input sub-attribute, that is, calculate the ratio of the number of identical attributes in the two groups of sub-attributes to the total number of the two groups of sub-attributes. The attribute overlap rate is a value between 0 and 1, indicating the degree of similarity or overlap between the two groups of attributes; 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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