Automatic generation method, system and equipment of road engineering project and medium

Abstract

The invention provides an automatic generation method, system and device for a road engineering project and a medium, and the method comprises the steps: obtaining a real-time engineering data set and a plurality of historical engineering data sets of a target project, determining a plurality of similar engineering data sets according to the real-time engineering data set and all historical engineering data sets, determining a plurality of data peak proximity degrees of the target project according to all the similar project data sets, determining project sensitive data sequences corresponding to all the similar project data sets according to all the data peak proximity degrees, and determining project difference characteristic quantity of each project sensitive data in the project sensitive data sequences, and determining an engineering data stage table of the target engineering according to all the engineering difference characteristic quantities, and automatically generating an engineering project of the target engineering according to the engineering data stage table, so that automatic generation of the engineering project can be realized.

Description

Technical Field

[0001] This application relates to the technical field of engineering projects. More specifically, this application relates to a method, system, device, and medium for automatically generating road engineering projects. Background Art

[0002] An engineering project generally refers to a series of planned, organized, and budgeted work carried out to achieve a certain goal or complete a task. Engineering projects can cover multiple fields, including roads, infrastructure, information technology, and manufacturing, etc.

[0003] The automatic generation of an engineering project is to first collect all necessary information about the engineering project, including a task list, resource requirements, dependencies, constraints, etc., and then use computer software, algorithms, and technologies to automatically generate a reasonable engineering project by inputting relevant information of the project, setting constraints, and dependencies between project tasks, reducing errors in manual operations, and making the project more flexible and adaptable. However, in the prior art, a large number of professionals are often required to evaluate the engineering project and it takes a lot of time to generate the engineering project, resulting in a waste of human resources. Therefore, how to achieve the automatic generation of engineering projects has become a difficult problem faced by the industry. Summary of the Invention

[0004] This application provides a method, system, device, and medium for automatically generating road engineering projects, which can intelligently achieve the automatic generation of engineering projects.

[0005] In a first aspect, this application provides a method for automatically generating a road engineering project, including the following steps: Obtain the real-time engineering data set of the target project and multiple historical engineering data sets; Determine multiple similar engineering data sets according to the real-time engineering data set and all historical engineering data sets; Determine multiple data peak proximity degrees of the target project according to all similar engineering data sets, and then determine the engineering sensitive data sequence corresponding to all similar engineering data sets from all data peak proximity degrees; Determine the engineering difference feature quantity of each engineering sensitive data in the engineering sensitive data sequence, and determine the engineering data stage table of the target project according to all engineering difference feature quantities; Automatically generate the engineering project of the target project according to the engineering data stage table.

[0006] In some embodiments, determining multiple similar engineering data sets according to the real-time engineering data set and all historical engineering data sets specifically includes: Select a historical engineering dataset, determine the engineering difference amount of each historical engineering data in this historical engineering dataset according to the real-time engineering dataset, determine the engineering data similarity coefficient of this historical engineering dataset according to all the engineering difference amounts, and repeat the above steps to determine the engineering data similarity coefficients of the remaining historical engineering datasets; Determine the engineering similarity threshold for all engineering data similarity coefficients; Select an engineering data similarity coefficient. When this engineering data similarity coefficient is greater than the engineering similarity threshold, use this engineering data similarity coefficient as the offset when engineering is similar. Repeat the above steps to judge the remaining engineering data similarity coefficients and obtain multiple offsets when engineering is similar; Regard each historical engineering dataset corresponding to each offset when engineering is similar as a similar engineering dataset.

[0007] In some embodiments, determining the multiple data peak proximities of the target engineering according to all the similar engineering datasets specifically includes: Select a similar engineering dataset and determine the engineering compaction factor of each similar engineering data in this similar engineering dataset; Form the engineering compaction sequence of this similar engineering dataset with all the engineering compaction factors; Repeat the above steps to determine the engineering compaction sequences of the remaining similar engineering datasets; Convert all the engineering compaction sequences into an engineering compaction matrix; Determine the multiple data peak proximities of the target engineering according to the engineering compaction matrix.

[0008] In some embodiments, determining the engineering sensitive data sequences corresponding to all the similar engineering datasets from all the data peak proximities specifically includes: Determine multiple engineering sensitive data according to all the data peak proximities and all the similar engineering datasets; Determine the engineering sensitive data sequences corresponding to all the similar engineering datasets according to all the engineering sensitive data.

[0009] In some embodiments, determining the engineering difference characteristic amount of each engineering sensitive data in the engineering sensitive data sequence specifically includes: Determine the engineering construction data corresponding to each engineering sensitive data in the engineering sensitive data sequence; Determine the engineering difference characteristic amount corresponding to each engineering sensitive data in the engineering sensitive data sequence according to all the engineering construction data.

[0010] In some embodiments, determining the engineering data stage table of the target engineering according to all the engineering difference characteristic amounts specifically includes: Obtain all the engineering construction data; Convert all engineering construction data into a project data stage table for the target project based on all engineering difference characteristic quantities.

[0011] In some embodiments, the real-time engineering data in the real-time engineering data set is a collection of road foundation data in a real-time engineering node of the target project.

[0012] In a second aspect, the present application provides an automatic generation system for a road engineering project, including: An acquisition module for acquiring a real-time engineering data set of the target project and a plurality of historical engineering data sets; A processing module for determining a plurality of similar engineering data sets according to the real-time engineering data set and all the historical engineering data sets; The processing module is further configured to determine a plurality of data peak proximity degrees of the target project according to all the similar engineering data sets, and then determine an engineering sensitive data sequence corresponding to all the similar engineering data sets from all the data peak proximity degrees; The processing module is further configured to determine the engineering difference characteristic quantity of each engineering sensitive data in the engineering sensitive data sequence, and determine the project data stage table of the target project according to all the engineering difference characteristic quantities; An execution module for automatically generating a project of the target project according to the project data stage table.

[0013] In a third aspect, the present application provides a computer device, which includes a memory and a processor. The memory stores code, and the processor is configured to acquire the code and execute the above-mentioned automatic generation method for a road engineering project.

[0014] In a fourth aspect, the present application provides a computer-readable storage medium, which stores a computer program. When the computer program is executed by a processor, the above-mentioned automatic generation method for a road engineering project is implemented.

[0015] The technical solutions provided by the disclosed embodiments of the present application have the following beneficial effects: In a method, system, device, and medium for automatically generating a road engineering project provided by this application, multiple similar engineering data sets are determined through the real-time engineering data set of the target project and multiple historical engineering data sets. Multiple historical projects with a relatively small similarity to the target project are removed, facilitating the selection of historical projects close to the target project. The engineering data similarity coefficient of each engineering data in each similar engineering data set is calculated. The engineering data similarity coefficient reflects the similarity degree between each historical engineering node and the real-time engineering node. All the maximum engineering data similarity coefficients are formed into a data peak proximity sequence. Then, according to the data peak proximity sequence, a set of historical road basic data sequences with the highest similarity to the real-time engineering data set of the target project is extracted from all the similar engineering data sets. Thus, the engineering construction data set of the target project is predicted based on this set of historical road basic data sequences. The compensation amount of each engineering construction data in the engineering construction data set is determined through the real-time engineering data set. Each compensation amount is used as an engineering difference feature quantity. Each engineering construction data in the engineering construction data set is compensated according to all the engineering difference feature quantities, thereby obtaining the engineering data stage table of the target project. Finally, the engineering project of the target project is automatically generated by the engineering data stage table, realizing the automatic generation of the engineering project. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 is an exemplary flowchart of a method for automatically generating a road engineering project according to some embodiments of this application; Figure 2 is an exemplary flowchart of determining a similar engineering data set according to some embodiments of this application; Figure 3 is an exemplary flowchart of determining the data peak proximity according to some embodiments of this application; Figure 4 is a schematic diagram of exemplary hardware and / or software of a system for automatically generating a road engineering project according to some embodiments of this application; Figure 5 is a schematic diagram of the structure of a computer device for implementing the method for automatically generating a road engineering project according to some embodiments of this application. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0017] The core of this application is to obtain the real-time engineering data set and multiple historical engineering data sets of the target project, determine multiple similar engineering data sets based on the real-time engineering data set and all historical engineering data sets, determine the multiple data peak proximity degrees of the target project based on all similar engineering data sets, and then determine the engineering sensitive data sequences corresponding to all similar engineering data sets from all data peak proximity degrees, determine the engineering difference feature quantities of each engineering sensitive data in the engineering sensitive data sequence, determine the engineering data phase table of the target project based on all engineering difference feature quantities, and automatically generate the engineering project of the target project according to the engineering data phase table, so as to realize the automatic generation of the engineering project.

[0018] To better understand the above technical solution, the above technical solution will be described in detail below in conjunction with the specification drawings and specific implementation manners. Refer to Figure 1 , which is an exemplary flowchart of the method for automatically generating a road engineering project shown in some embodiments of this application. The method 100 for automatically generating a road engineering project mainly includes the following steps: In step 101, obtain the real-time engineering data set and multiple historical engineering data sets of the target project.

[0019] Specifically, the real-time engineering data set of the target project is obtained through the engineering project database of the target project. The real-time engineering data set is a set composed of all real-time engineering data; the engineering type of the target project is obtained through the engineering construction unit, and multiple historical projects with the same engineering type as the engineering type are matched from the historical engineering library through the engineering type, and the historical engineering data sets of each historical project are obtained through the engineering project database, so as to obtain multiple historical engineering data sets. The historical engineering data set is a set composed of all historical engineering data.

[0020] It should be noted that the real-time engineering data in the real-time engineering data set in this application is a set of road basic data in a real-time engineering node of the target project. Among them, when the target project is a road, the real-time engineering node can be the section of the road under construction, and the road basic data is the basic information such as the length, width, height, terrain height and low, slope size, and landform type of the section. It should be noted that after one real-time engineering node is completed, the next real-time engineering node starts, that is, after the construction of this section is completed, the construction of the next section starts; the historical engineering data in the historical engineering data set is a set of historical road basic data in a historical engineering node of the historical project. Among them, when the historical project is a completed road, the historical engineering node can be the completed section of the completed road, and the historical road basic data is the basic information such as the length, width, height, terrain height and low, slope size, and landform type of the completed section. It should be noted that one real-time engineering node corresponds to one historical engineering node.

[0021] In step 102, multiple similar engineering data sets are determined based on the real-time engineering data set and all historical engineering data sets.

[0022] In some embodiments, referring to Figure 2 As shown, this figure is a schematic flowchart of determining similar engineering data sets in some embodiments of the present application. In this embodiment, the determination of similar engineering data sets can be implemented by the following steps: First, in step 1021, select a historical engineering data set. Determine the engineering difference amount of each historical engineering data in this historical engineering data set according to the real-time engineering data set, and determine the engineering data similarity coefficient of this historical engineering data set according to all the engineering difference amounts. Repeat the above steps to determine the engineering data similarity coefficients of the remaining historical engineering data sets; Secondly, in step 1022, determine the engineering similarity threshold of all engineering data similarity coefficients; Then, in step 1023, select an engineering data similarity coefficient. When this engineering data similarity coefficient is greater than the engineering similarity threshold, use this engineering data similarity coefficient as the offset value when engineering is similar. Repeat the above steps to judge the remaining engineering data similarity coefficients to obtain multiple offset values when engineering is similar; Finally, in step 1024, regard the historical engineering data sets corresponding to each offset value when engineering is similar as similar engineering data sets.

[0023] Among them, in specific implementation, determine the engineering difference amount of each historical engineering data in this historical engineering data set according to the real-time engineering data set, that is: select a historical engineering data in this historical engineering data set, subtract the value of the length in this historical engineering data from the value of the length of the corresponding engineering data in the real-time engineering data set, subtract the value of the width in this historical engineering data from the value of the width of the corresponding engineering data in the real-time engineering data set, subtract the value of the height in this historical engineering data from the value of the height of the corresponding engineering data in the real-time engineering data set, and use the average value of all the subtracted values as the engineering difference amount of this historical engineering data. Repeat the above steps to determine the engineering difference amounts of the remaining historical engineering data in this historical engineering data set. It should be noted that the engineering difference amount in the present application represents the parameter value of the difference degree between the road foundation data in the target project and the road foundation data in the historical project, so as to facilitate the identification of historical projects. Here is an example, and the same is true for other data. Therefore, the data here are all compared and differentiated with historical data.

[0024] Among them, in some embodiments, the engineering data similarity coefficient of this historical engineering data set can be determined according to the following formula according to all engineering difference amounts: Among them, represents the engineering data similarity coefficient of the historical engineering data set, represents the th engineering difference amount, represents the average value of all engineering difference amounts, represents the maximum engineering difference amount, represents the minimum engineering difference amount, represents the total number of all engineering difference amounts.

[0025] It should be noted that the engineering data similarity coefficient in this application reflects the degree of conformity between the target project and the historical project. The smaller the engineering data similarity coefficient, the higher the degree of conformity between the target project and the historical project.

[0026] Among them, it should be noted that the engineering similarity threshold in this application is a parameter value reflecting the central tendency of all engineering data similarity coefficients, and is used to analyze all engineering data similarity coefficients. In some embodiments, the average value of all engineering data similarity coefficients can be used as the engineering similarity threshold; when this engineering data similarity coefficient is greater than the engineering similarity threshold, this engineering data similarity coefficient is used as the engineering similarity deviation value; if this engineering data similarity coefficient is less than or equal to the engineering similarity threshold, then this engineering data similarity coefficient is deleted, and the engineering similarity deviation value represents a parameter value of the deviation degree between the target project and the historical project.

[0027] It should be noted that in this application, an engineering similarity deviation value corresponds to a historical engineering data set. The similar engineering data set is composed of all similar engineering data. The similar engineering data set represents the road foundation data set of the historical project close to the target project, so as to predict the road foundation data of the target project; all engineering similarity deviation values are arranged in ascending order, the arranged sequence is used as the engineering similarity deviation value sequence, and all similar engineering data sets are arranged in the order of the corresponding engineering similarity deviation values in the engineering similarity deviation value sequence, and the arranged sequence is used as the similar engineering data set sequence.

[0028] In step 103, multiple data peak proximities of the target project are determined according to all similar engineering data sets, and then an engineering sensitive data sequence corresponding to all similar engineering data sets is determined from all data peak proximities.

[0029] In some embodiments, as shown in Figure 3 This figure is a schematic flowchart of determining the data peak proximity in some embodiments of this application. In this embodiment, the data peak proximity can be determined by the following steps: First, in step 1031, select a similar project dataset and determine the project compaction factor for each similar project data in the similar project dataset. Secondly, in step 1032, form the project compaction sequence of the similar project dataset with all the project compaction factors. Furthermore, in step 1033, repeat the above steps to determine the project compaction sequences of the remaining similar project datasets. Thus, in step 1034, convert all the project compaction sequences into a project compaction matrix. Finally, in step 1035, determine the multiple data peak proximities of the target project according to the project compaction matrix.

[0030] Among them, in some embodiments, determining the project compaction factor for each similar project data in the similar project dataset can be implemented by the following steps: Determine the project inspection coefficient ; Obtain the value of the th road foundation data of the th similar project data in the similar project dataset ; Obtain the value of the th road foundation data of the real-time project data corresponding to the th similar project data in the real-time project dataset ; Obtain the th project difference amount of the similar project dataset ; Obtain the project data similarity coefficient of the similar project dataset ; According to the project inspection coefficient , the value of the th road foundation data of the th similar project data in the similar project dataset , the value of the th road foundation data of the real-time project data corresponding to the th similar project data in the real-time project dataset , the th project difference amount of the similar project dataset and the project data similarity coefficient of the similar project dataset determine the project compaction factor of the similar project data, where the project compaction factor can be determined according to the following formula: Among them, represents the engineering compaction factor of the th similar engineering data, represents the sum of the values of all road foundation data in the th similar engineering data in the set of similar engineering data, represents the sum of the values of all road foundation data in the real-time engineering data corresponding to the th similar engineering data in the real-time engineering data set, represents the logarithmic function with base 2.

[0031] It should be noted that the engineering inspection coefficient in this application represents a parameter for correcting the road foundation data in the real-time engineering data. In some embodiments, the engineering inspection coefficient can be set by all historical engineering data through the cross-validation method of the prior art. The value range of the engineering inspection coefficient is 0-1. In other embodiments, other methods can also be used for setting, which is not limited here.

[0032] It should be noted that in this application can take values of 1, 2, 3. When is 1, represents the length value in the th similar engineering data in the set of similar engineering data, represents the length value in the real-time engineering data corresponding to the th similar engineering data in the real-time engineering data set. When is 2, represents the width value in the th similar engineering data in the set of similar engineering data, represents the width value in the real-time engineering data corresponding to the th similar engineering data in the real-time engineering data set. When is 3, represents the height value in the th similar engineering data in the set of similar engineering data, represents the height value in the real-time engineering data corresponding to the th similar engineering data in the real-time engineering data set; the engineering compaction factor reflects the parameter of the coincidence degree between the road foundation data of the real-time engineering and the road foundation data of the historical engineering.

[0033] It should be noted that this basic data can take other data, but its meaning is to reflect one point: indicating the coincidence degree of the data.

[0034] Specifically, in implementation, all project tamping factors form the project tamping sequence of this similar project dataset, that is: all project tamping factors are arranged in the order of corresponding project nodes, and the arranged sequence is used as the project tamping sequence of this similar project dataset; it should be noted that in this application, one project tamping factor corresponds to one project node; all project tamping sequences are converted into a project tamping matrix, that is: all project tamping sequences are arranged in the order of corresponding similar project datasets in the similar project dataset sequence, and the first project tamping sequence in the arranged sequence is selected. The first project tamping factor in this project tamping sequence is used as the first project tamping factor in the first row of the project tamping matrix, and the second project tamping factor in this project tamping sequence is used as the second project tamping factor in the first row of the project tamping matrix, and so on, until the last project tamping factor in this project tamping sequence is used as the last project tamping factor in the first row of the project tamping matrix. Repeat the above steps to determine the remaining project tamping factors in the project tamping matrix. The project tamping matrix is a matrix composed of all project tamping factors; multiple data peak proximities of the target project are determined according to the project tamping matrix, that is: the maximum project tamping factor in each column of the project tamping matrix is used as the data peak proximity of the target project.

[0035] It should be noted that the data peak proximity in this application is a parameter value reflecting the maximum similarity degree between a project node and the corresponding historical project node, so as to facilitate selecting the historical project data with the highest similarity to the project data of the target project.

[0036] In some embodiments, the following steps can be adopted to determine the project sensitive data sequences corresponding to all similar project datasets through all data peak proximities: Determine multiple project sensitive data according to all data peak proximities and all similar project datasets; Determine the project sensitive data sequences corresponding to all similar project datasets according to all project sensitive data.

[0037] In specific implementation, multiple engineering sensitive data are determined according to all data peak proximities and all similar project data sets, that is: all data peak proximities are arranged in the order of corresponding engineering nodes, and the obtained sequence is used as the data peak proximity sequence. One data peak proximity in the data peak proximity sequence is selected, and the similar project data corresponding to this data peak proximity is used as the engineering sensitive data of this data peak proximity. Repeat the above steps to determine the engineering sensitive data of the remaining data peak proximities; According to all the engineering sensitive data, an engineering sensitive data sequence corresponding to all similar project data sets is determined, that is: all the engineering sensitive data are arranged in the order of the corresponding data peak proximities in the data peak proximity sequence, and the arranged sequence is used as the engineering sensitive data sequence corresponding to all similar project data sets.

[0038] It should be noted that the engineering sensitive data in the engineering sensitive data sequence in this application are data that reflect the greatest similarity to the real-time engineering data in the real-time engineering data set, and are used to predict all engineering data of the target project.

[0039] In step 104, the engineering difference feature quantity of each engineering sensitive data in the engineering sensitive data sequence is determined, and an engineering data stage table of the target project is determined according to all the engineering difference feature quantities.

[0040] In some embodiments, determining the engineering difference feature quantity of each engineering sensitive data in the engineering sensitive data sequence can be implemented by the following steps; Determine the engineering construction data corresponding to each engineering sensitive data in the engineering sensitive data sequence; According to all the engineering construction data, determine the engineering difference feature quantity corresponding to each engineering sensitive data in the engineering sensitive data sequence.

[0041] Among them, in specific implementation, to determine the engineering construction data corresponding to each engineering sensitive data in the engineering sensitive data sequence, that is: obtain the engineering construction data corresponding to each engineering sensitive data in the engineering sensitive data sequence through the historical engineering construction database. The engineering construction data is a combination of the start time and end time of the historical engineering node corresponding to this engineering construction data. It should be noted that in this application, one engineering construction data corresponds to one historical engineering node.

[0042] Among them, in some embodiments, determining the engineering difference feature quantity corresponding to each engineering sensitive data in the engineering sensitive data sequence according to all the engineering construction data can be implemented by the following steps: Obtain the sum of the values of all road foundation data in the th engineering sensitive data in the engineering sensitive data sequence ; Determine the Engineering interval quantity of engineering sensitive data corresponding to engineering construction data ; Obtain the engineering inspection coefficient ; Obtain the engineering compaction factor corresponding to the th engineering sensitive data According to the sum of the values of all road foundation data in the th engineering sensitive data in the engineering sensitive data sequence , the engineering interval quantity of engineering sensitive data corresponding to engineering construction data , the engineering progress deviation coefficient and the engineering compaction factor corresponding to the th engineering sensitive data, determine the engineering difference characteristic quantity of this engineering sensitive data, and then obtain the engineering difference characteristic quantity corresponding to each engineering sensitive data in the engineering sensitive data sequence, where the engineering difference characteristic quantity can be determined according to the following formula: Among them, represents the engineering difference characteristic quantity of the th engineering sensitive data, represents the engineering difference equilibrium value, represents the sum of the values of all road foundation data in the real-time engineering data corresponding to the th engineering sensitive data in the real-time engineering data set.

[0043] In specific implementation, select an engineering sensitive data in the engineering sensitive data sequence, subtract the value of the length in the real-time engineering data corresponding to this engineering sensitive data in the real-time engineering data set from the value of the length in this engineering sensitive data, subtract the value of the width in the real-time engineering data corresponding to this engineering sensitive data in the real-time engineering data set from the value of the width in this engineering sensitive data, subtract the value of the height in the real-time engineering data corresponding to this engineering sensitive data in the real-time engineering data set from the value of the height in this engineering sensitive data, and take the sum of all the subtracted values as the engineering adjustment difference quantity of this engineering sensitive data. Repeat the above steps to determine the engineering adjustment difference quantity of the remaining engineering sensitive data in this engineering sensitive data sequence, and take the average value of all the engineering adjustment difference quantities as the engineering difference equilibrium value. The engineering difference equilibrium value represents the parameter value that measures the central tendency of the distance difference between the target engineering and the historical engineering; take the value of the interval time between the start time and the end time in the engineering construction data as the interval quantity of this engineering construction data.

[0044] It should be noted additionally that the use of equal values for length, width, height, etc. here is for the best understanding. Changing to other basic data makes no essential difference. In principle, this is mainly to show the differences.

[0045] It should be noted that in this application, the engineering difference characteristic quantity is a parameter value that reflects the degree of compensation for engineering construction data, so as to facilitate the prediction of the progress of the target project.

[0046] In some embodiments, the engineering data stage table of the target project can be determined according to all the engineering difference characteristic quantities by the following steps: Obtain all the engineering construction data; Convert all the engineering construction data into the engineering data stage table of the target project according to all the engineering difference characteristic quantities.

[0047] Specifically, when implementing, convert all the engineering construction data into the engineering data stage table according to all the engineering difference characteristic quantities, that is: select an engineering difference characteristic quantity, add the end time of the engineering construction data corresponding to this engineering difference characteristic quantity, and use the combination of the added end time and the start time of the engineering construction data corresponding to this engineering difference characteristic quantity as the engineering progress solidification data. Repeat the above steps to determine the remaining engineering progress solidification data. Make a table of all the engineering progress solidification data through the third-party library openpyxl of the existing technology python software, and use the obtained table as the engineering data stage table of the target project.

[0048] It should be noted that the engineering progress solidification data in this application is the progress data after adjusting the engineering construction data, which is used to predict the progress of the target project; the engineering data stage table is a table for predicting the construction progress of each engineering node of the target project.

[0049] In step 105, generate the engineering project of the target project automatically according to the engineering data stage table.

[0050] Specifically, when implementing, use the engineering data stage table as the engineering project construction table of the target project, and generate the engineering project of the target project through the engineering project management tool such as procore software with the engineering project construction table and the construction configuration file of the target project. In other embodiments, other methods can be used to implement, which are not limited here.

[0051] It should be noted that the construction configuration file of the target project in this application includes but is not limited to the construction site design file, the construction foundation engineering table, the overall engineering structure configuration file, the construction in-site layout file, etc. The construction configuration file of the target project can be obtained through the construction configuration system of the target project, which will not be elaborated here.

[0052] It should be noted that in this application, multiple historical projects with the same project type as the target project are matched, and the historical project datasets of each historical project are obtained. By comparing the similarity between the historical project data and the real-time project data, the historical project data of each historical project node with the maximum similarity is selected, and then an engineering sensitive data sequence is obtained. The engineering sensitive data sequence is used to predict all the engineering construction data of the target project, and corresponding adjustments are made to the predicted engineering construction data. Then, an engineering data stage table is generated from all the adjusted engineering construction data, and the engineering data stage table is used as the engineering project construction table of the target project.

[0053] In addition, on the other hand of this application, in some embodiments, this application provides an automatic generation system for road engineering projects. Refer to Figure 4 , which is a schematic diagram of the exemplary hardware and / or software of the automatic generation system for road engineering projects according to some embodiments of this application. The automatic generation system 400 for road engineering projects includes: an acquisition module 401, a processing module 402, and an execution module 403, which are described as follows: Acquisition module 401. In this application, the historical project dataset acquisition module 401 is mainly used to acquire the real-time project dataset of the target project and multiple historical project datasets; Processing module 402. In this application, the processing module 402 is used to determine multiple similar project datasets based on the real-time project dataset and all the historical project datasets; In this application, the processing module 402 is further used to determine the multiple data peak proximity degrees of the target project based on all the similar project datasets, and then determine the engineering sensitive data sequence corresponding to all the similar project datasets from all the data peak proximity degrees; In this application, the processing module 402 is also used to determine the engineering difference feature quantity of each engineering sensitive data in the engineering sensitive data sequence, and determine the engineering data stage table of the target project based on all the engineering difference feature quantities; Execution module 403. In this application, the execution module 403 is mainly used to automatically generate the engineering project of the target project according to the engineering data stage table.

[0054] In addition, this application also provides a computer device, which includes a memory and a processor. The memory stores code, and the processor is configured to obtain the code and execute the above-mentioned automatic generation method for road engineering projects.

[0055] In some embodiments, refer to Figure 5 , which is a schematic diagram of the structure of a computer device applying the automatic generation method for road engineering projects according to some embodiments of this application. The automatic generation method for road engineering projects in the above embodiments can be passed throughFigure 5 implemented by the computer device shown. The computer device 500 includes at least one processor 501, a communication bus 502, a memory 503, and at least one communication interface 504.

[0056] The processor 501 can be a general-purpose central processing unit (CPU), an application-specific integrated circuit (ASIC), or one or more for controlling the execution of the automatic generation method of the road engineering project in this application.

[0057] The communication bus 502 may include a path for transmitting information between the above components.

[0058] The memory 503 can be a read-only memory (ROM) or other types of static storage devices that can store static information and instructions, a random access memory (RAM), or other types of dynamic storage devices that can store information and instructions. It can also be an electrically erasable programmable read-only memory (EEPROM), a compact disc read-only memory (CD-ROM), or other optical disc storage, optical disc storage (including compact discs, laser discs, optical discs, digital versatile discs, Blu-ray discs, etc.), magnetic disks, or other magnetic storage devices, or any other medium that can be used to carry or store the desired program code in the form of instructions or data structures and can be accessed by a computer, but is not limited thereto. The memory 503 can exist independently and be connected to the processor 501 through the communication bus 502. The memory 503 can also be integrated with the processor 501.

[0059] Among them, the memory 503 is used to store the program code for executing the solution of this application and is controlled by the processor 501 for execution. The processor 501 is used to execute the program code stored in the memory 503. The program code may include one or more software modules. The determination of the similar engineering data set in the above embodiments can be implemented by one or more software modules in the program code of the processor 501 and the memory 503.

[0060] A communication interface 504, using any transceiver-like device, is used to communicate with other devices or communication networks, such as Ethernet, radio access network (RAN), wireless local area networks (WLAN), etc.

[0061] In a specific implementation, as an embodiment, a computer device may include multiple processors, and each of these processors may be a single-core (single-CPU) processor or a multi-core (multi-CPU) processor. Here, the processor may refer to one or more devices, circuits, and / or processing cores for processing data (such as computer program instructions).

[0062] The above computer device may be a general-purpose computer device or a special-purpose computer device. In a specific implementation, the computer device may be a desktop computer, a laptop computer, a network server, a personal digital assistant (PDA), a mobile phone, a tablet computer, a wireless terminal device, a communication device, or an embedded device. The embodiments of the present application do not limit the type of the computer device.

[0063] In addition, the present application also provides a computer-readable storage medium, which stores a computer program, and when the computer program is executed by a processor, it implements the above-mentioned automatic generation method for road engineering projects.

[0064] In summary, in the automatic generation method, system, device, and storable medium for road engineering projects disclosed in the embodiments of the present application, first, a real-time engineering data set and multiple historical engineering data sets of a target project are obtained, multiple similar engineering data sets are determined according to the real-time engineering data set and all the historical engineering data sets, multiple data peak proximity degrees of the target project are determined according to all the similar engineering data sets, and then an engineering sensitive data sequence corresponding to all the similar engineering data sets is determined from all the data peak proximity degrees. The engineering difference feature amount of each engineering sensitive data in the engineering sensitive data sequence is determined, an engineering data stage table of the target project is determined according to all the engineering difference feature amounts, and the engineering project of the target project is automatically generated according to the engineering data stage table, so as to realize the automatic generation of the engineering project.

[0065] Although the preferred embodiments of the present application have been described, those skilled in the art can make additional changes and modifications once they learn the basic creative concepts. Therefore, the appended claims are intended to be construed to include the preferred embodiments as well as all changes and modifications falling within the scope of the present application.

[0066] Obviously, those skilled in the art can make various changes and modifications to this application without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of this application fall within the scope of the claims of this application and their equivalent technologies, this application is also intended to include these modifications and variations.

Claims

1. A method for automatically generating a road engineering project, characterized in that: The steps include: Acquire the real-time engineering dataset and multiple historical engineering datasets of the target project; Determine multiple similar engineering data sets based on the real-time engineering data set and all historical engineering data sets; Determine the proximity of multiple data peaks of the target project based on all similar project data sets, and then determine the engineering sensitive data sequences corresponding to all similar project data sets based on all data peak proximity; Determine the engineering difference feature quantity of each engineering sensitive data in the engineering sensitive data sequence, and determine the engineering data stage table of the target engineering according to all the engineering difference feature quantities; The engineering items of the target engineering are automatically generated according to the engineering data stage table.

2. The method according to claim 1, characterized in that Determine multiple similar engineering datasets based on the real-time engineering dataset and all historical engineering datasets, including: Select a historical engineering data set, determine the engineering difference amount of each historical engineering data in the historical engineering data set according to the real-time engineering data set, determine the engineering data similarity coefficient of the historical engineering data set according to all the engineering difference amounts, repeat the above steps to determine the engineering data similarity coefficients of the remaining historical engineering data sets; Determine the engineering similarity threshold of the similarity coefficient of all engineering data; Selecting a similarity coefficient of engineering data, when the similarity coefficient of engineering data is greater than the engineering similarity threshold, taking the similarity coefficient of engineering data as the engineering similarity time deviation value, repeating the above steps, judging the remaining engineering data similarity coefficients, and obtaining multiple engineering similarity time deviation values; The historical engineering data sets corresponding to similar time deviation values ​​of each project are all used as similar engineering data sets.

3. The method according to claim 1, characterized in that Determining the proximity of multiple data peaks of the target project based on all similar project data sets specifically includes: Select a similar engineering data set, and determine the engineering compaction factor of each similar engineering data in the similar engineering data set; All engineering compaction factors are combined into an engineering compaction sequence of the similar engineering data set; Repeat the above steps to determine the engineering compaction sequence of the remaining similar engineering data sets; Convert all engineering compaction sequences into engineering compaction matrices; The proximity of multiple data peaks of the target project is determined according to the project consolidation matrix.

4. The method according to claim 1, characterized in that The engineering sensitive data sequences corresponding to all similar engineering data sets are determined by the proximity of all data peaks, including: Determine multiple engineering sensitive data based on all data peak proximity and all similar engineering data sets; Determine the engineering sensitive data sequences corresponding to all similar engineering data sets based on all engineering sensitive data.

5. The method according to claim 1, characterized in that Determining the engineering difference feature quantity of each engineering sensitive data in the engineering sensitive data sequence specifically includes: Determine the engineering construction data corresponding to each engineering sensitive data in the engineering sensitive data sequence; The engineering difference feature quantity corresponding to each engineering sensitive data in the engineering sensitive data sequence is determined according to all engineering construction data.

6. The method according to claim 1, characterized in that The engineering data stage table of the target engineering project is determined based on all engineering difference characteristics, including: Obtain all engineering construction data; All engineering construction data are converted into an engineering data phase table of the target project according to all engineering difference characteristic quantities.

7. The method according to claim 1, characterized in that The real-time engineering data in the real-time engineering data set is a collection of basic road data in a real-time engineering node in the target project.

8. An automatic generation system for road engineering projects, characterized in that: include: An acquisition module, used to acquire a real-time engineering data set and multiple historical engineering data sets of a target project; A processing module, used for determining a plurality of similar engineering data sets according to the real-time engineering data set and all historical engineering data sets; The processing module is further used to determine the proximity of multiple data peaks of the target project based on all similar project data sets, and then determine the engineering sensitive data sequences corresponding to all similar project data sets based on all data peak proximity; The processing module is further used to determine the engineering difference feature quantity of each engineering sensitive data in the engineering sensitive data sequence, and determine the engineering data stage table of the target engineering according to all the engineering difference feature quantities; An execution module is used to automatically generate engineering items of a target engineering project according to the engineering data stage table.

9. A computer device, characterized in that: The computer device comprises a memory and a processor, wherein the memory stores codes, and the processor is configured to obtain the codes and execute the method for automatically generating a road engineering project according to any one of claims 1 to 7.

10. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the method for automatically generating a road engineering project as claimed in any one of claims 1 to 7 is implemented.

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