Contact network construction data management method, platform and equipment and readable storage medium
By obtaining basic contact network data from the database, calculating configuration data and using a pre-trained construction model to predict installation data, the problem of difficulty in ensuring quality and safety in traditional contact network construction has been solved, intelligent management has been achieved, construction quality has been improved and labor costs have been reduced.
Patent Information
- Application Number
- CN202510384324.8
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-03-28
- Publication Date
- 2025-09-26
AI Technical Summary
Traditional contact network construction is mainly manual, which makes it difficult to ensure construction quality, installation accuracy and safety, and the labor cost is high, which cannot meet the needs of intelligent development of the industry.
By obtaining basic contact network data from the database, calculating configuration data, using pre-trained construction models to predict installation data, and then carrying out construction, intelligent management is achieved.
It improves the construction quality and installation accuracy of the contact network, reduces labor costs and enterprise safety pressure, and meets the needs of intelligent development of the industry.
Smart Images
Figure CN120707328A_ABST
Abstract
Description
Technical Field
[0001] The present disclosure relates to the field of contact network engineering technology, and in particular to a contact network construction data management method, platform, device and readable storage medium. Background Art
[0002] In recent years, with the continuous development of electrified railway construction, great progress has been made in contact network design and construction.
[0003] Currently, catenary construction involves key processes such as on-site data measurement, equipment and material storage, support assembly, pre-assembly of the catenary arm and dropper strings, transportation of the support, arm, and dropper strings to site, installation of the pre-assembled arm, erection of the catenary conductors, and calibration and installation of the dropper strings. Traditional, manual construction methods are detrimental to overall catenary construction quality, installation accuracy, and process safety. Furthermore, these methods are costly, increase safety pressures on enterprises, and fail to meet the demands of intelligent industry development. Summary of the Invention
[0004] In order to solve the above technical problems or at least partially solve the above technical problems, the present disclosure provides a contact network construction data management method, platform, device and readable storage medium.
[0005] In a first aspect, an embodiment of the present disclosure provides a method for managing catenary construction data, the method comprising:
[0006] Obtain basic data of the target contact network to be constructed from the database;
[0007] Calculating configuration data of the target contact network based on basic data of the target contact network, wherein the configuration data of the target contact network includes arm configuration data and dropper configuration data;
[0008] Based on the configuration data of the target contact network, the installation data of the target contact network is predicted;
[0009] The target contact network is constructed using the installation data of the target contact network.
[0010] In some embodiments, before acquiring basic data of the target contact network to be constructed from the database, the method further includes:
[0011] Collect basic data of each contact network and save the basic data of each contact network in a database.
[0012] In some embodiments, predicting the target contact network installation data based on the target contact network configuration data includes:
[0013] Preprocessing the configuration data of the target contact network to obtain the preprocessed configuration data of the target contact network;
[0014] Based on the pre-processed configuration data of the target contact network, installation data of the target contact network is predicted.
[0015] In some embodiments, preprocessing the configuration data of the target contact network to obtain the preprocessed configuration data of the target contact network includes:
[0016] Detecting whether there is abnormal data in the configuration data of the target contact network;
[0017] If abnormal data exists, the abnormal data is corrected to obtain pre-processed configuration data of the target contact network.
[0018] In some embodiments, predicting the target contact network installation data based on the target contact network configuration data includes:
[0019] Extracting features from the configuration data of the target contact network to obtain configuration feature data of the target contact network;
[0020] The configuration feature data of the target contact network is input into a pre-trained construction model, and the installation data of the target contact network is predicted by the pre-trained construction model.
[0021] In some embodiments, after predicting the installation data of the target contact network based on the configuration data of the target contact network, the method further includes:
[0022] Calculate the prediction accuracy of the pre-trained construction model based on the predicted target catenary installation data and actual construction data;
[0023] Based on the prediction accuracy of the pre-trained construction model, a model evaluation report is generated.
[0024] In some embodiments, after predicting the installation data of the target contact network using the pre-trained construction model, the method further includes:
[0025] Determine whether the prediction accuracy of the pre-trained construction model meets the preset accuracy requirements;
[0026] If not, the model parameters of the pre-trained construction model are adjusted to obtain the target construction model;
[0027] The target construction model is used to predict the installation data of the target contact network, and a result file is generated based on the installation data of the target contact network.
[0028] In a second aspect, an embodiment of the present disclosure provides a catenary construction data management platform, the catenary construction data management platform comprising:
[0029] An acquisition module is used to obtain basic data of the target contact network to be constructed from a database;
[0030] A calculation module, configured to calculate configuration data of the target contact network based on basic data of the target contact network, wherein the configuration data of the target contact network includes arm configuration data and dropper configuration data;
[0031] A prediction module, used for predicting the installation data of the target contact network based on the configuration data of the target contact network;
[0032] A construction module is used to construct the target contact network using the installation data of the target contact network.
[0033] In a third aspect, an embodiment of the present disclosure provides an electronic device, including:
[0034] Memory;
[0035] processor; and
[0036] computer programs;
[0037] The computer program is stored in the memory and is configured to be executed by the processor to implement the method as described in the first aspect.
[0038] In a fourth aspect, an embodiment of the present disclosure provides a computer-readable storage medium having a computer program stored thereon, wherein the computer program is executed by a processor to implement the method as described in the first aspect.
[0039] In a fifth aspect, an embodiment of the present disclosure further provides a computer program product, which includes a computer program or instructions, and when the computer program or instructions are executed by a processor, implements the method described in the first aspect.
[0040] The catenary network construction data management method, platform, device, and readable storage medium provided by the disclosed embodiments obtain basic data of the target catenary network to be constructed from a database, calculate the configuration data of the target catenary network based on the basic data of the target catenary network, and predict the installation data of the target catenary network based on the configuration data of the target catenary network. The target catenary network is constructed using the installation data of the target catenary network. Compared with the existing technology, the disclosed embodiments can ensure the overall construction quality, installation accuracy, and process safety of the catenary network, reduce labor costs and enterprise safety pressures, and meet the needs of the industry's intelligent development. BRIEF DESCRIPTION OF THE DRAWINGS
[0041] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present disclosure and, together with the description, serve to explain the principles of the present disclosure.
[0042] In order to more clearly illustrate the embodiments of the present disclosure or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, for ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.
[0043] Figure 1 A flow chart of a method for managing contact network construction data provided by an embodiment of the present disclosure;
[0044] Figure 2 A schematic diagram of the architecture of a contact network construction data management system provided in an embodiment of the present disclosure;
[0045] Figure 3 A flow chart of a method for managing contact network construction data provided by another embodiment of the present disclosure;
[0046] Figure 4 A flow chart of a method for managing contact network construction data provided by another embodiment of the present disclosure;
[0047] Figure 5 A schematic diagram of the structure of a contact network construction data management platform provided in an embodiment of the present disclosure;
[0048] Figure 6 A schematic diagram of the structure of an electronic device provided in an embodiment of the present disclosure. DETAILED DESCRIPTION
[0049] In order to more clearly understand the above-mentioned objectives, features and advantages of the present disclosure, the scheme of the present disclosure will be further described below. It should be noted that the embodiments of the present disclosure and the features therein can be combined with each other in the absence of conflict.
[0050] In the following description, many specific details are set forth to facilitate a full understanding of the present disclosure, but the present disclosure may also be implemented in other ways different from those described herein; it is obvious that the embodiments in the specification are only part of the embodiments of the present disclosure, rather than all of the embodiments.
[0051] In recent years, with the continuous development of electrified railway construction, great progress has been made in contact network design and construction.
[0052] Currently, catenary construction involves key processes such as on-site data measurement, equipment and material storage, support assembly, pre-assembly of the catenary arm and dropper strings, transportation of the support, arm, and dropper strings to site, installation of the pre-assembled arm, erection of the catenary conductors, and calibration and installation of the dropper strings. Traditional, manual construction methods are detrimental to overall catenary construction quality, installation accuracy, and process safety. Furthermore, these methods are costly, increase safety pressures on enterprises, and fail to meet the demands of intelligent industry development.
[0053] To address this issue, an embodiment of the present disclosure provides a method for managing contact network construction data, which will be introduced below in conjunction with specific embodiments.
[0054] Figure 1 A flow chart of the contact network construction data management method provided in the embodiment of the present disclosure. The execution subject of the method is an electronic device, which can be a portable mobile device such as a smartphone, tablet computer, laptop computer, or a fixed device such as a personal computer or server, wherein the server can be a single server or a server cluster, and the server cluster can be a distributed cluster or a centralized cluster. The method can be applied to the scenario of managing the construction data of the contact network, which can ensure the overall contact network construction quality, installation accuracy and process safety, reduce labor costs and enterprise safety pressure, and meet the needs of the intelligent development of the industry. It is understandable that the contact network construction data management method provided in the embodiment of the present disclosure can also be applied in other scenarios.
[0055] Below Figure 1 The method for managing contact network construction data shown in FIG. 1 is introduced, and the specific steps of the method are as follows:
[0056] S101. Obtain basic data of a target contact network to be constructed from a database.
[0057] In this step, if Figure 2 As shown, the electronic device will obtain basic data of the target contact network to be built from the database. Optionally, the basic data of the target contact network may include but is not limited to on-site measurement data, engineering drawing data, contact network plane layout data, etc.
[0058] In some embodiments, before acquiring basic data of the target contact network to be constructed from the database, the method further includes: collecting basic data of each contact network and saving the basic data of each contact network into the database.
[0059] In some embodiments, data related to the contact network, such as contact network plan layout data, contact network installation data, and component data, can be stored in a database to facilitate subsequent analysis and management.
[0060] S102: Calculate configuration data of the target contact network based on basic data of the target contact network, where the configuration data of the target contact network includes arm configuration data and dropper configuration data.
[0061] In this step, after obtaining the basic data of the target contact network, the electronic device will calculate the configuration data of the target contact network based on the basic data of the target contact network. The configuration data of the target contact network includes arm configuration data and dropper configuration data. Figure 2 As shown, the arm pre-configuration and the suspension string pre-configuration can be achieved according to the arm configuration data and the suspension string configuration data.
[0062] In some embodiments, the arm configuration data includes the number of arms, the length, angle and position of each arm, etc.; the string configuration data includes the number of strings, the length of each string, the distance between adjacent strings, etc.
[0063] S103: Predicting the installation data of the target contact network based on the configuration data of the target contact network.
[0064] In this step, after calculating the configuration data of the target contact network, the electronic device can predict the installation data of the target contact network based on the configuration data of the target contact network. Optionally, the installation data of the target contact network includes arm installation data and dropper installation data. Figure 2 As shown, the cantilever installation data and the suspension string installation data can be used to guide the cantilever installation and the suspension string installation.
[0065] In some embodiments, S103 may include but is not limited to S1031 and S1032:
[0066] S1031. Extracting features from the configuration data of the target contact network to obtain configuration feature data of the target contact network;
[0067] In this embodiment, a feature extraction algorithm may be used to extract features from the configuration data of the target contact network to obtain configuration feature data of the target contact network. The configuration feature data of the target contact network may characterize the construction regularity of the target contact network.
[0068] S1032: Input the configuration feature data of the target contact network into a pre-trained construction model, and predict the installation data of the target contact network through the pre-trained construction model.
[0069] S104: construct the target contact network using the installation data of the target contact network.
[0070] In this step, after obtaining the installation data of the target contact network, the target contact network can be constructed using the installation data of the target contact network. Specifically, the installation data of the target contact network is sent to the construction personnel, who can construct the target contact network based on the installation data of the target contact network.
[0071] The disclosed embodiments obtain basic data of the target catenary to be constructed from a database, calculate the target catenary configuration data based on the basic data, and predict the target catenary installation data based on the target catenary configuration data. The target catenary installation data is then used to construct the target catenary. Compared to existing technologies, the disclosed embodiments can ensure overall catenary construction quality, installation accuracy, and process safety, reduce labor costs and enterprise safety pressures, and meet the needs of intelligent development in the industry.
[0072] The contact network construction data management method provided by the present invention can realize data interface processing of intelligent material storage, intelligent pre-matching, intelligent transportation of pre-accessories, and on-site intelligent construction equipment, form a continuous and effective real-time management list for contact network construction at the design end, provide accurate material and working hour lists, and form standardization of contact network construction.
[0073] Figure 3 A flow chart of a method for managing contact network construction data according to another embodiment of the present disclosure is shown in FIG. Figure 3 As shown, the method includes the following steps:
[0074] S201. Obtain basic data of the target contact network to be constructed from a database.
[0075] Specifically, the implementation process and principle of S201 and S101 are the same and will not be repeated here.
[0076] S202: Calculate configuration data of the target contact network based on basic data of the target contact network, where the configuration data of the target contact network includes arm configuration data and dropper configuration data.
[0077] Specifically, the implementation process and principle of S202 are the same as those of S102 and will not be repeated here.
[0078] S203: Preprocess the configuration data of the target contact network to obtain the preprocessed configuration data of the target contact network.
[0079] In this step, the electronic device may pre-process the configuration data of the target contact network to obtain the pre-processed configuration data of the target contact network. The pre-processing may include abnormal data correction.
[0080] In some embodiments, S203 may include but is not limited to S2031 and S2032:
[0081] S2031, detecting whether there is abnormal data in the configuration data of the target contact network;
[0082] S2032: If abnormal data exists, correct the abnormal data to obtain pre-processed configuration data of the target contact network.
[0083] S204: Predicting installation data of the target contact network based on the preprocessed configuration data of the target contact network.
[0084] In this step, the electronic device can predict the installation data of the target contact network based on the pre-processed configuration data of the target contact network. Specifically, the installation data of the target contact network can be predicted based on the pre-processed configuration data of the target contact network using a pre-trained construction model.
[0085] S205: Calculate the prediction accuracy of the pre-trained construction model based on the predicted installation data of the target contact network and the actual construction data.
[0086] In this step, the prediction accuracy is the ratio of the number of correct predictions to the total number. Specifically, key technologies such as data management platform control algorithms, data-driven equipment core algorithms, and equipment structure models and performance can be used to mine and analyze installation data, generate installation data analysis results, and compare these results with actual construction data to analyze factors affecting catenary construction efficiency, predict catenary construction quality, and improve prediction accuracy, which can then be used to guide catenary design and construction processes.
[0087] S206: Generate a model evaluation report based on the prediction accuracy of the pre-trained construction model.
[0088] S207: Utilize the installation data of the target contact network to construct the target contact network.
[0089] Specifically, the implementation process and principle of S207 and S104 are the same and will not be repeated here.
[0090] The disclosed embodiment obtains basic data of a target contact network to be constructed from a database and calculates the target contact network configuration data based on the basic data. The target contact network configuration data includes arm configuration data and dropper configuration data. Furthermore, the target contact network configuration data is preprocessed to obtain preprocessed configuration data of the target contact network. Based on the preprocessed configuration data, the target contact network installation data is predicted. The prediction accuracy of a pretrained construction model is calculated based on the predicted target contact network installation data and actual construction data. A model evaluation report is generated based on the prediction accuracy of the pretrained construction model. The target contact network installation data is then used to construct the target contact network. This method allows the installation data to be compared with actual construction data, analyzes factors affecting contact network construction efficiency, ensures contact network construction quality, and improves the prediction accuracy of the pretrained construction model, further guiding contact network design and construction processes.
[0091] Figure 4 A flow chart of a method for managing contact network construction data according to another embodiment of the present disclosure is shown in FIG. Figure 4 As shown, the method includes the following steps:
[0092] S301. Obtain basic data of the target contact network to be constructed from a database.
[0093] Specifically, the implementation process and principle of S301 and S101 are the same and will not be described in detail here.
[0094] S302: Calculate configuration data of the target contact network based on basic data of the target contact network, where the configuration data of the target contact network includes arm configuration data and dropper configuration data.
[0095] Specifically, the implementation process and principle of S302 and S102 are the same and will not be repeated here.
[0096] S303: Extract features from the configuration data of the target contact network to obtain configuration feature data of the target contact network.
[0097] In this step, a feature extraction algorithm may be used to extract features from the configuration data of the target contact network to obtain configuration feature data of the target contact network. The configuration feature data of the target contact network may characterize the construction regularity of the target contact network.
[0098] S304: Input the configuration feature data of the target contact network into a pre-trained construction model, and predict the installation data of the target contact network through the pre-trained construction model.
[0099] Furthermore, the electronic device may input the configuration feature data of the target contact network into a pre-trained construction model, and predict the installation data of the target contact network through the pre-trained construction model.
[0100] S305: Determine whether the prediction accuracy of the pre-trained construction model meets the preset accuracy requirement.
[0101] In this step, the electronic device determines whether the prediction accuracy of the pre-trained construction model meets the preset accuracy requirement. For example, if an accuracy threshold is set, if the prediction accuracy is greater than or equal to the accuracy threshold, it is determined that the preset accuracy requirement is met.
[0102] S306: If not, adjust the model parameters of the pre-trained construction model to obtain the target construction model.
[0103] In this step, if the prediction accuracy of the pre-trained construction model does not meet the preset accuracy requirement, the electronic device will adjust the model parameters of the pre-trained construction model to obtain the target construction model.
[0104] In some embodiments, adjusting the model parameters of the pre-trained construction model in S306 to obtain the target construction model includes but is not limited to S3061 and S3062:
[0105] S3061. Compare the predicted installation data of the target contact network with the actual construction data to obtain an error compensation value;
[0106] S3062. Adjust the model parameters of the pre-trained construction model based on the error compensation value until the prediction accuracy of the construction model after the model parameters are adjusted meets the preset accuracy requirements, thereby obtaining the target construction model.
[0107] In this embodiment, the electronic device will compare the predicted installation data of the target contact network with the actual construction data to obtain an error compensation value. Further, the model parameters of the pre-trained construction model will be adjusted according to the error compensation value. When the prediction accuracy of the construction model after adjusting the model parameters meets the preset accuracy requirements, the target construction model is obtained.
[0108] S307 : Predicting the installation data of the target contact network through the target construction model, and generating a result file based on the installation data of the target contact network.
[0109] In this step, the electronic device predicts the target contact network installation data using the target construction model and generates a result file based on the target contact network installation data. In some embodiments, the result file includes a list of materials and work hours, achieving standardized and intelligent construction of the contact network.
[0110] The disclosed embodiment obtains basic data of the target contact network to be constructed from a database, and calculates the configuration data of the target contact network based on the basic data of the target contact network. The configuration data of the target contact network includes arm configuration data and dropper configuration data. Furthermore, feature extraction is performed on the configuration data of the target contact network to obtain configuration feature data of the target contact network. The configuration feature data of the target contact network is input into a pre-trained construction model, and the installation data of the target contact network is predicted by the pre-trained construction model. Next, it is determined whether the prediction accuracy of the pre-trained construction model meets the preset accuracy requirements. If not, the model parameters of the pre-trained construction model are adjusted to obtain the target construction model. Then, the installation data of the target contact network is predicted by the target construction model, and a result file is generated based on the installation data of the target contact network. Through this method, the overall contact network construction quality, installation accuracy and process safety can be guaranteed, labor costs and enterprise safety pressure can be reduced, and the needs of intelligent development of the industry can be met. The model parameters of the pre-trained construction model are adjusted based on the error compensation value, which can improve the prediction accuracy of the pre-trained construction model and further be used to guide the contact network design and construction process.
[0111] Figure 5 The structure diagram of the catenary network construction data management platform provided by the embodiment of the present disclosure. The catenary network construction data management platform can be the electronic device as described in the above embodiment, or the catenary network construction data management platform can be a component or assembly in the electronic device. The catenary network construction data management platform provided by the embodiment of the present disclosure can execute the processing flow provided by the embodiment of the catenary network construction data management method, such as Figure 5 As shown, the contact network construction data management platform 40 includes: an acquisition module 41, a calculation module 42, a prediction module 43, and a construction module 44; wherein, the acquisition module 41 is used to obtain basic data of the target contact network to be constructed from the database; the calculation module 42 is used to calculate the configuration data of the target contact network based on the basic data of the target contact network, and the configuration data of the target contact network includes arm configuration data and dropper configuration data; the prediction module 43 is used to predict the installation data of the target contact network based on the configuration data of the target contact network; the construction module 44 is used to construct the target contact network using the installation data of the target contact network.
[0112] Optionally, before obtaining the basic data of the target contact network to be constructed from the database, the contact network construction data management platform 40 further includes: a collection module 45; the collection module 45 is used to collect the basic data of each contact network and save the basic data of each contact network into the database.
[0113] Optionally, when the prediction module 43 predicts the installation data of the target contact network based on the configuration data of the target contact network, it is specifically used to: preprocess the configuration data of the target contact network to obtain the preprocessed configuration data of the target contact network; and predict the installation data of the target contact network based on the preprocessed configuration data of the target contact network.
[0114] Optionally, the prediction module 43 preprocesses the configuration data of the target contact network to obtain the preprocessed configuration data of the target contact network, which is specifically used to: detect whether there is abnormal data in the configuration data of the target contact network; if there is abnormal data, correct the abnormal data to obtain the preprocessed configuration data of the target contact network.
[0115] Optionally, when the prediction module 43 predicts the installation data of the target contact network based on the configuration data of the target contact network, it is specifically used to: extract features from the configuration data of the target contact network to obtain the configuration feature data of the target contact network; input the configuration feature data of the target contact network into a pre-trained construction model, and predict the installation data of the target contact network through the pre-trained construction model.
[0116] Optionally, after predicting the installation data of the target contact network based on the configuration data of the target contact network, the contact network construction data management platform 40 also includes: a generation module 46; the generation module 46 is used to calculate the prediction accuracy of the pre-trained construction model based on the predicted installation data of the target contact network and the actual construction data; and generate a model evaluation report based on the prediction accuracy of the pre-trained construction model.
[0117] Optionally, after the installation data of the target contact network is predicted by the pre-trained construction model, the contact network construction data management platform 40 also includes: a judgment module 47 and an acquisition module 48; the judgment module 47 is used to judge whether the prediction accuracy of the pre-trained construction model meets the preset accuracy requirements; if not, the model parameters of the pre-trained construction model are adjusted to obtain the target construction model; the installation data of the target contact network is predicted by the target construction model, and a result file is generated based on the installation data of the target contact network.
[0118] Figure 5 The contact network construction data management platform of the illustrated embodiment can be used to execute the technical solution of the above-mentioned method embodiment. Its implementation principle and technical effects are similar and will not be repeated here.
[0119] Figure 6 This is a schematic diagram of the structure of an electronic device in the embodiment of the present disclosure. Figure 6, which shows a structural diagram of an electronic device 600 suitable for implementing the embodiments of the present disclosure. Figure 6 The electronic device shown is only an example and should not limit the functions and scope of use of the embodiments of the present disclosure.
[0120] like Figure 6 As shown, electronic device 600 may include a processing device (e.g., a central processing unit, a graphics processing unit, etc.) 601, which can perform various appropriate actions and processes to implement the contact network construction data management method according to the program stored in read-only memory (ROM) 602 or the program loaded from storage device 608 into random access memory (RAM) 603 to implement the contact network construction data management method according to the embodiment of the present disclosure. RAM 603 also stores various programs and data required for the operation of electronic device 600. Processing device 601, ROM 602, and RAM 603 are interconnected via bus 604. An input / output (I / O) interface 605 is also connected to bus 604.
[0121] Typically, the following devices may be connected to the I / O interface 605: an input device 606 including, for example, a touch screen, a touchpad, a keyboard, a mouse, a camera, a microphone, an accelerometer, a gyroscope, etc.; an output device 607 including, for example, a liquid crystal display (LCD), a speaker, a vibrator, etc.; a storage device 608 including, for example, a magnetic tape, a hard disk, etc.; and a communication device 609. The communication device 609 may allow the electronic device 600 to communicate with other devices wirelessly or by wire to exchange data. Although Figure 6 The electronic device 600 is shown with various devices, but it should be understood that it is not required to implement or possess all of the devices shown. More or fewer devices may be implemented or possessed instead.
[0122] In particular, according to embodiments of the present disclosure, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, embodiments of the present disclosure include a computer program product comprising a computer program carried on a non-transitory computer-readable medium, the computer program containing program code for executing the method illustrated in the flowcharts, thereby implementing the above-described method for managing contact network construction data. In such embodiments, the computer program can be downloaded and installed from a network via a communication device 609, or installed from a storage device 608, or installed from a ROM 602. When executed by the processing device 601, the computer program performs the above-described functions defined in the method of the embodiments of the present disclosure.
[0123] It should be noted that the computer-readable medium mentioned above in the present disclosure may be a computer-readable signal medium or a computer-readable storage medium, or any combination of the two. A computer-readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device, or component, or any combination of the above. More specific examples of computer-readable storage media may include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In the present disclosure, a computer-readable storage medium may be any tangible medium that contains or stores a program that can be used by or in conjunction with an instruction execution system, device, or component. In the present disclosure, a computer-readable signal medium may include a data signal propagated in baseband or as part of a carrier wave, which carries computer-readable program code. Such a propagated data signal may take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. A computer-readable signal medium may also be any computer-readable medium other than a computer-readable storage medium that can transmit, propagate, or transport a program for use by or in conjunction with an instruction execution system, apparatus, or device. The program code contained on the computer-readable medium may be transmitted using any suitable medium, including but not limited to wires, optical cables, RF (radio frequency), etc., or any suitable combination thereof.
[0124] In some embodiments, the client and server can communicate using any currently known or future developed network protocol, such as HTTP (HyperText Transfer Protocol), and can be interconnected with any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include a local area network ("LAN"), a wide area network ("WAN"), an internet (e.g., the Internet), and a peer-to-peer network (e.g., an ad hoc peer-to-peer network), as well as any currently known or future developed network.
[0125] The computer-readable medium may be included in the electronic device, or may exist independently without being incorporated into the electronic device.
[0126] The computer-readable medium carries one or more programs. When the one or more programs are executed by the electronic device, the electronic device:
[0127] Obtain basic data of the target contact network to be constructed from the database;
[0128] Calculating configuration data of the target contact network based on basic data of the target contact network, wherein the configuration data of the target contact network includes arm configuration data and dropper configuration data;
[0129] Based on the configuration data of the target contact network, the installation data of the target contact network is predicted;
[0130] The target contact network is constructed using the installation data of the target contact network.
[0131] Optionally, when the above one or more programs are executed by the electronic device, the electronic device may also execute other steps described in the above embodiments.
[0132] Computer program code for performing the operations of the present disclosure may be written in one or more programming languages, or a combination thereof, including, but not limited to, object-oriented programming languages such as Java, Smalltalk, C++, and conventional procedural programming languages such as "C" or similar programming languages. The program code may be executed entirely on the user's computer, partially on the user's computer, as a stand-alone software package, partially on the user's computer and partially on a remote computer, or entirely on the remote computer or server. In cases involving a remote computer, the remote computer may be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., through the Internet using an Internet service provider).
[0133] The flowcharts and block diagrams in the accompanying drawings illustrate the possible implementation architecture, functions and operations of the systems, methods and computer program products according to various embodiments of the present disclosure. In this regard, each box in the flowchart or block diagram can represent a module, program segment, or a part of code, and the module, program segment, or a part of code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in a different order than that marked in the accompanying drawings. For example, two boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram and / or flowchart, and the combination of the boxes in the block diagram and / or flowchart, can be implemented with a dedicated hardware-based system that performs the specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.
[0134] The units involved in the embodiments described in this disclosure may be implemented in software or hardware, wherein the name of a unit does not necessarily limit the unit itself.
[0135] The functions described above herein may be performed, at least in part, by one or more hardware logic components. For example, and without limitation, exemplary types of hardware logic components that may be used include: field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on chip (SOCs), complex programmable logic devices (CPLDs), and the like.
[0136] In the context of the present disclosure, a machine-readable medium can be a tangible medium that can contain or store a program for use by or in conjunction with an instruction execution system, device or equipment. A machine-readable medium can be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium can include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or equipment, or any suitable combination of the foregoing. A more specific example of a machine-readable storage medium can include an electrical connection based on one or more lines, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.
[0137] The above description is merely a preferred embodiment of the present disclosure and an illustration of the technical principles employed. Those skilled in the art should understand that the scope of disclosure involved in the present disclosure is not limited to the technical solutions formed by the specific combination of the above-mentioned technical features, but also includes other technical solutions formed by any combination of the above-mentioned technical features or their equivalents without departing from the above-mentioned disclosed concepts. For example, a technical solution formed by replacing the above-mentioned features with (but not limited to) technical features with similar functions disclosed in this disclosure.
[0138] In addition, although each operation is described in a specific order, this should not be understood as requiring these operations to be performed in the specific order shown or in a sequential order. Under certain circumstances, multitasking and parallel processing may be advantageous. Similarly, although some specific implementation details have been included in the above discussion, these should not be interpreted as limiting the scope of the present disclosure. Some features described in the context of a separate embodiment can also be implemented in a single embodiment in combination. On the contrary, the various features described in the context of a single embodiment can also be implemented in multiple embodiments individually or in any suitable sub-combination mode.
[0139] Although the subject matter has been described in language specific to structural features and / or methodological logical acts, it should be understood that the subject matter defined in the appended claims is not necessarily limited to the specific features or acts described above. Rather, the specific features and acts described above are merely example forms of implementing the claims.
Claims
1. A method for managing contact network construction data, characterized in that: The method comprises: Obtain basic data of the target contact network to be constructed from the database; Calculating configuration data of the target contact network based on basic data of the target contact network, wherein the configuration data of the target contact network includes arm configuration data and dropper configuration data; Based on the configuration data of the target contact network, the installation data of the target contact network is predicted; The target contact network is constructed using the installation data of the target contact network.
2. The method according to claim 1, characterized in that Before acquiring basic data of the target contact network to be constructed from the database, the method further includes: Collect basic data of each contact network and save the basic data of each contact network in a database.
3. The method according to claim 1, characterized in that The method of predicting the installation data of the target contact network based on the configuration data of the target contact network includes: Preprocessing the configuration data of the target contact network to obtain the preprocessed configuration data of the target contact network; Based on the pre-processed configuration data of the target contact network, installation data of the target contact network is predicted.
4. The method according to claim 3, characterized in that The preprocessing of the configuration data of the target contact network to obtain the preprocessed configuration data of the target contact network includes: Detecting whether there is abnormal data in the configuration data of the target contact network; If abnormal data exists, the abnormal data is corrected to obtain pre-processed configuration data of the target contact network.
5. The method according to claim 1, wherein The method of predicting the installation data of the target contact network based on the configuration data of the target contact network includes: Extracting features from the configuration data of the target contact network to obtain configuration feature data of the target contact network; The configuration feature data of the target contact network is input into a pre-trained construction model, and the installation data of the target contact network is predicted by the pre-trained construction model.
6. The method according to claim 1, characterized in that After predicting the installation data of the target contact network based on the configuration data of the target contact network, the method further includes: Calculate the prediction accuracy of the pre-trained construction model based on the predicted target catenary installation data and actual construction data; Based on the prediction accuracy of the pre-trained construction model, a model evaluation report is generated.
7. The method according to claim 5, characterized in that After predicting the installation data of the target contact network by the pre-trained construction model, the method further includes: Determine whether the prediction accuracy of the pre-trained construction model meets the preset accuracy requirements; If not, the model parameters of the pre-trained construction model are adjusted to obtain the target construction model; The target construction model is used to predict the installation data of the target contact network, and a result file is generated based on the installation data of the target contact network.
8. A catenary construction data management platform, characterized in that: The contact network construction data management platform includes: An acquisition module is used to obtain basic data of the target contact network to be constructed from a database; A calculation module, configured to calculate configuration data of the target contact network based on basic data of the target contact network, wherein the configuration data of the target contact network includes arm configuration data and dropper configuration data; A prediction module, used for predicting the installation data of the target contact network based on the configuration data of the target contact network; A construction module is used to construct the target contact network using the installation data of the target contact network.
9. An electronic device, characterized in that: include: Memory; processor; as well as computer programs; The computer program is stored in the memory and configured to be executed by the processor to implement the method according to any one of claims 1 to 7.
10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the method according to any one of claims 1 to 7 is implemented.