CN117786500A - Method, device, equipment and storage medium for predicting earth surface subsidence in shield construction - Google Patents
Method, device, equipment and storage medium for predicting earth surface subsidence in shield construction Download PDFInfo
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Abstract
The invention discloses a method, a device, equipment and a storage medium for predicting earth surface subsidence in shield construction. The method comprises the following steps: acquiring real-time construction data; inputting the real-time construction data into a settlement prediction model to obtain a settlement value of a ground surface settlement monitoring point corresponding to the real-time construction data, wherein the settlement prediction model is obtained by iteratively training an initial model through a target sample set, and the target sample set comprises: the method comprises the steps that a target sample and a ground surface subsidence monitoring point subsidence value corresponding to the target sample are included, wherein the target sample comprises: according to the technical scheme, the settlement value of the earth surface settlement monitoring point corresponding to the real-time construction data can be obtained, so that the situation that the settlement exceeds a control range and the safety of surrounding buildings is influenced is prevented.
Description
Technical Field
The embodiment of the invention relates to the field of shield tunnel construction risk control, in particular to a method, a device, equipment and a storage medium for predicting earth surface subsidence in shield construction.
Background
In the construction process of the shield method, the soil layer around the tunnel can deform, and the deformation is particularly remarkable in a soft aquifer or an unstable soil layer. Because the shield method construction site is mainly located in the urban prosperous region, the sedimentation control of the surrounding soil mass is very important. Once the settlement is out of control, the safety of surrounding buildings may be affected.
In view of the above, it is now highly desirable to design a method for predicting the subsidence of the earth surface in shield construction.
Disclosure of Invention
The embodiment of the invention provides a method, a device, equipment and a storage medium for predicting earth surface subsidence of shield construction, which can acquire earth surface subsidence monitoring point subsidence values corresponding to real-time construction data, thereby preventing the situation that the safety of surrounding buildings is influenced due to subsidence exceeding a control range.
According to one aspect of the invention, there is provided a method for predicting earth surface subsidence in shield construction, comprising:
acquiring real-time construction data;
inputting the real-time construction data into a settlement prediction model to obtain a settlement value of a ground surface settlement monitoring point corresponding to the real-time construction data, wherein the settlement prediction model is obtained by iteratively training an initial model through a target sample set, and the target sample set comprises: the method comprises the steps that a target sample and a ground surface subsidence monitoring point subsidence value corresponding to the target sample are included, wherein the target sample comprises: a basic information sample and a disturbance parameter sample.
According to another aspect of the present invention, there is provided a shield construction earth surface subsidence prediction apparatus including:
the real-time construction data acquisition module is used for acquiring real-time construction data;
the subsidence value determining module of the earth surface subsidence monitoring point is used for inputting the real-time construction data into a subsidence prediction model to obtain the subsidence value of the earth surface subsidence monitoring point corresponding to the real-time construction data, wherein the subsidence prediction model is obtained by iteratively training an initial model through a target sample set, and the target sample set comprises: the method comprises the steps that a target sample and a ground surface subsidence monitoring point subsidence value corresponding to the target sample are included, wherein the target sample comprises: a basic information sample and a disturbance parameter sample.
According to another aspect of the present invention, there is provided an electronic apparatus including:
at least one processor; and
a memory communicatively coupled to the at least one processor; wherein,
the memory stores a computer program executable by the at least one processor to enable the at least one processor to perform the shield construction surface subsidence prediction method according to any one of the embodiments of the present invention.
According to another aspect of the present invention, there is provided a computer readable storage medium storing computer instructions for causing a processor to implement the method for predicting earth surface subsidence in shield construction according to any one of the embodiments of the present invention when executed.
The embodiment of the invention acquires real-time construction data; inputting the real-time construction data into a settlement prediction model to obtain a settlement value of a ground surface settlement monitoring point corresponding to the real-time construction data, wherein the settlement prediction model is obtained by iteratively training an initial model through a target sample set, and the target sample set comprises: the method comprises the steps that a target sample and a ground surface subsidence monitoring point subsidence value corresponding to the target sample are included, wherein the target sample comprises: the foundation information samples and the disturbance parameter samples can obtain the subsidence value of the earth surface subsidence monitoring point corresponding to the real-time construction data, and further the situation that the safety of surrounding buildings is affected due to the fact that subsidence exceeds a control range is prevented.
It should be understood that the description in this section is not intended to identify key or critical features of the embodiments of the invention or to delineate the scope of the invention. Other features of the present invention will become apparent from the description that follows.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings that are needed in the embodiments will be briefly described below, it being understood that the following drawings only illustrate some embodiments of the present invention and therefore should not be considered as limiting the scope, and other related drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a flow chart of a method for predicting subsidence of earth's surface in shield construction in an embodiment of the invention;
FIG. 2 is a flow chart of another method for predicting subsidence of the earth's surface in shield construction according to an embodiment of the present invention;
FIG. 3 is a schematic structural diagram of a device for predicting subsidence of earth's surface in shield construction according to an embodiment of the present invention;
fig. 4 is a schematic structural diagram of an electronic device in an embodiment of the present invention.
Detailed Description
In order that those skilled in the art will better understand the present invention, a technical solution in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in which it is apparent that the described embodiments are only some embodiments of the present invention, not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the present invention without making any inventive effort, shall fall within the scope of the present invention.
It should be noted that the terms "first," "second," and the like in the description and the claims of the present invention and the above figures are used for distinguishing between similar objects and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used may be interchanged where appropriate such that the embodiments of the invention described herein may be implemented in sequences other than those illustrated or otherwise described herein. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.
It will be appreciated that prior to using the technical solutions disclosed in the embodiments of the present disclosure, the user should be informed and authorized of the type, usage range, usage scenario, etc. of the personal information related to the present disclosure in an appropriate manner according to the relevant legal regulations.
Example 1
Fig. 1 is a flowchart of a method for predicting earth surface subsidence in shield construction, which is provided by the embodiment of the present invention, and the method may be implemented by a device for predicting earth surface subsidence in shield construction, which may be implemented by software and/or hardware, as shown in fig. 1, and specifically includes the following steps:
s110, acquiring real-time construction data.
Wherein, the real-time construction data includes: engineering foundation data and construction parameters of the current construction project. The current construction project engineering basic data comprises: and the soil parameters corresponding to the current construction project engineering.
Specifically, the manner of acquiring the real-time construction data may be: and acquiring the current construction project engineering foundation data and the real-time construction parameters input by the user.
It should be noted that the real-time construction data may further include: and (5) shield tunneling data in real time.
S120, inputting the real-time construction data into a settlement prediction model to obtain a settlement value of the earth surface settlement monitoring point corresponding to the real-time construction data.
The settlement prediction model is obtained by iteratively training an initial model through a target sample set, wherein the target sample set comprises: the method comprises the steps that a target sample and a ground surface subsidence monitoring point subsidence value corresponding to the target sample are included, wherein the target sample comprises: a basic information sample and a disturbance parameter sample.
Wherein the basic information sample comprises: soil parameters corresponding to the historical construction parameters and tunnel process parameters corresponding to the historical construction parameters. The disturbance parameter sample comprises: incision disturbance parameters, attitude disturbance parameters and shield tail disturbance parameters corresponding to historical construction parameters.
Specifically, the manner of inputting the real-time construction data into a settlement prediction model to obtain the settlement value of the earth surface settlement monitoring point corresponding to the real-time construction data may be as follows: and establishing an initial model in advance, iteratively training the initial model based on a target sample set to obtain a settlement prediction model, and inputting the real-time construction data into the settlement prediction model to obtain a settlement value of a ground surface settlement monitoring point corresponding to the real-time construction data. The method for inputting the real-time construction data into the settlement prediction model to obtain the settlement value of the earth surface settlement monitoring point corresponding to the real-time construction data can be as follows: extracting element attributes of the real-time construction data to obtain basic class attributes, disturbance class attributes, basic information corresponding to the basic class attributes and disturbance parameters corresponding to the disturbance class attributes corresponding to the real-time construction data; and inputting the foundation type attribute, the disturbance type attribute, the foundation information corresponding to the foundation type attribute and the disturbance parameter corresponding to the disturbance type attribute corresponding to the real-time construction data into a settlement prediction model to obtain the settlement value of the earth surface settlement monitoring point corresponding to the real-time construction data.
In the embodiment of the invention, real-time construction data after element attributes are extracted is input into a settlement prediction model to obtain the settlement value of the earth surface settlement monitoring point.
Optionally, before the initial model is iteratively trained by the target sample set, the method further comprises:
acquiring historical construction data;
extracting element attributes of the historical construction data to obtain attribute sets and characteristic parameters corresponding to each attribute in the attribute sets;
and generating a target sample set according to the attribute set and the characteristic parameters corresponding to each attribute in the attribute set.
Wherein the historical construction data comprises: the system comprises a basic class attribute, basic information corresponding to the basic class attribute, a disturbance parameter corresponding to the disturbance class attribute, a subsidence class attribute and a subsidence monitoring point subsidence value corresponding to the subsidence class attribute.
Specifically, the method for extracting the element attribute of the historical construction data to obtain the attribute set and the feature parameter corresponding to each attribute in the attribute set may be: and re-combining the historical construction data to extract meta-attributes, and obtaining basic class attributes, basic information corresponding to the basic class attributes, disturbance parameters corresponding to the disturbance class attributes, sedimentation class attributes and surface subsidence monitoring point subsidence values corresponding to the sedimentation class attributes.
Optionally, the attribute set includes: the system comprises a basic class attribute, a disturbance class attribute and a sedimentation class attribute, wherein characteristic parameters corresponding to the basic class attribute are basic information corresponding to the basic class attribute, characteristic parameters corresponding to the disturbance class attribute are disturbance parameters corresponding to the disturbance class attribute, and characteristic parameters corresponding to the sedimentation class attribute are ground surface sedimentation monitoring point sedimentation values corresponding to the sedimentation class attribute.
In order to facilitate the prediction of the subsidence value of the subsidence monitoring point, the main factors affecting the subsidence of the earth are divided into: a basic class attribute, a disturbance class attribute and a sedimentation class attribute. The characteristic parameters corresponding to the basic attributes are basic information required for shield tunnel construction, for example, the basic information may include: soil properties, geometric properties and process properties. The feature parameters corresponding to the disturbance type attribute are disturbance parameters corresponding to the disturbance type attribute, for example, the disturbance parameters may include: the method is mainly used for evaluating indexes of disturbance degree of the shield to soil in the tunneling process. The disturbance parameters can be obtained through analyzing and processing the shield real-time tunneling data. The disturbance parameters can be divided into: incision disturbance parameters, attitude disturbance parameters and shield tail disturbance parameters.
Optionally, before the initial model is iteratively trained by the target sample set, the method further comprises:
acquiring historical construction data;
generating a simulation data set according to the historical construction data and the current construction project engineering basic data;
extracting element attributes of data in the simulation data set to obtain an attribute set and characteristic parameters corresponding to each attribute in the attribute set;
and generating a target sample set according to the attribute set and the characteristic parameters corresponding to each attribute in the attribute set.
It should be noted that, a set of simulation data can be generated by combining the historical data and the current construction project engineering basic data, so that a large amount of data accumulation is not required in the early stage of model training, and the generation speed of the training sample set is improved.
Optionally, generating the target sample set according to the attribute set and the feature parameter corresponding to each attribute in the attribute set includes:
determining a target sample according to the basic class attribute, basic information corresponding to the basic class attribute, the disturbance class attribute and disturbance parameters corresponding to the disturbance class attribute;
determining the subsidence value of the earth surface subsidence monitoring point corresponding to the target sample according to the subsidence type attribute and the subsidence value of the earth surface subsidence monitoring point corresponding to the subsidence type attribute;
and generating a target sample set according to the target sample and the subsidence value of the earth surface subsidence monitoring point corresponding to the target sample.
Specifically, the method for determining the target sample according to the basic class attribute, the basic information corresponding to the basic class attribute, the disturbance class attribute and the disturbance parameter corresponding to the disturbance class attribute may be: generating a basic information sample according to the basic class attribute and basic information corresponding to the basic class attribute, and generating a disturbance parameter sample according to the disturbance class attribute and disturbance parameters corresponding to the disturbance class attribute; and determining a target sample according to the basic information sample and the disturbance parameter sample.
It should be noted that, each target sample is determined by a set of historical construction data, and the historical construction data needs to include three attribute categories of a basic attribute, a disturbance attribute and a sedimentation attribute. The real-time construction data needs to include: a basic class attribute and a disturbance class attribute.
Optionally, iteratively training the initial model by the target sample set includes:
establishing an initial model;
inputting the target samples in the target sample set into an initial model to obtain a predicted earth surface subsidence monitoring point subsidence value;
training parameters of the initial model according to an objective function formed by the subsidence value of the predicted surface subsidence monitoring point and the subsidence value of the surface subsidence monitoring point corresponding to the objective sample;
and returning to perform the operation of inputting the target samples in the target sample set into an initial model to obtain a settlement value of the predicted earth surface settlement monitoring point until a settlement prediction model is obtained.
Wherein the initial model may be a neural network model.
Specifically, the method for inputting the target samples in the target sample set into the initial model to obtain the predicted subsidence value of the earth surface subsidence monitoring point may be as follows: and inputting the basic information sample and the disturbance parameter sample in the target sample set into an initial model to obtain a predicted earth surface subsidence monitoring point subsidence value corresponding to the basic information sample and the disturbance parameter sample.
Optionally, the basic information corresponding to the basic class attribute includes: the soil property parameters and tunnel process parameters, and the disturbance parameters corresponding to the disturbance type attributes comprise: incision disturbance parameters, attitude disturbance parameters and shield tail disturbance parameters.
Optionally, the real-time construction data includes: engineering foundation data and construction parameters of the current construction project.
In a specific example, as shown in fig. 2, historical construction data is obtained, and meta-attributes are extracted by recombining the historical construction data to obtain an attribute set and feature parameters corresponding to each attribute in the attribute set; constructing a sedimentation data generator based on meta-attribute; combining the engineering basic data of the current construction project to generate simulation data; generating a target sample set according to output data and simulation data of the sedimentation data generator, and training an initial model based on the target sample set to obtain a sedimentation prediction model; and acquiring real-time shield tunneling data, and inputting the real-time shield tunneling data into a subsidence prediction model to obtain a subsidence value of a ground subsidence monitoring point corresponding to the real-time shield tunneling data.
After the real-time construction data is input into the subsidence prediction model to obtain the subsidence value of the earth surface subsidence monitoring point corresponding to the real-time construction data, the subsidence prediction model can be optimized according to the real-time construction data and the subsidence value of the earth surface subsidence monitoring point corresponding to the real-time construction data.
According to the technical scheme, real-time construction data are obtained; inputting the real-time construction data into a settlement prediction model to obtain a settlement value of a ground surface settlement monitoring point corresponding to the real-time construction data, wherein the settlement prediction model is obtained by iteratively training an initial model through a target sample set, and the target sample set comprises: the method comprises the steps that a target sample and a ground surface subsidence monitoring point subsidence value corresponding to the target sample are included, wherein the target sample comprises: the foundation information samples and the disturbance parameter samples can obtain the subsidence value of the earth surface subsidence monitoring point corresponding to the real-time construction data, and further the situation that the safety of surrounding buildings is affected due to the fact that subsidence exceeds a control range is prevented.
Example two
Fig. 3 is a schematic structural diagram of a device for predicting earth surface subsidence in shield construction according to an embodiment of the present invention. The embodiment can be applied to the situation of the earth surface subsidence prediction of the shield construction, the device can be realized in a software and/or hardware mode, the device can be integrated in any equipment for providing the earth surface subsidence prediction function of the shield construction, as shown in fig. 3, and the earth surface subsidence prediction device of the shield construction specifically comprises: a real-time construction data acquisition module 210 and a ground subsidence monitoring point subsidence value determination module 220.
The real-time construction data acquisition module is used for acquiring real-time construction data;
the subsidence value determining module of the earth surface subsidence monitoring point is used for inputting the real-time construction data into a subsidence prediction model to obtain the subsidence value of the earth surface subsidence monitoring point corresponding to the real-time construction data, wherein the subsidence prediction model is obtained by iteratively training an initial model through a target sample set, and the target sample set comprises: the method comprises the steps that a target sample and a ground surface subsidence monitoring point subsidence value corresponding to the target sample are included, wherein the target sample comprises: a basic information sample and a disturbance parameter sample.
Optionally, the method further comprises:
the historical construction data acquisition module is used for acquiring historical construction data;
the element attribute extraction module is used for extracting element attributes of the historical construction data to obtain attribute sets and characteristic parameters corresponding to each attribute in the attribute sets;
and the target sample set generating module is used for generating a target sample set according to the attribute set and the characteristic parameters corresponding to each attribute in the attribute set.
Optionally, the attribute set includes: the system comprises a basic class attribute, a disturbance class attribute and a sedimentation class attribute, wherein characteristic parameters corresponding to the basic class attribute are basic information corresponding to the basic class attribute, characteristic parameters corresponding to the disturbance class attribute are disturbance parameters corresponding to the disturbance class attribute, and characteristic parameters corresponding to the sedimentation class attribute are ground surface sedimentation monitoring point sedimentation values corresponding to the sedimentation class attribute.
Optionally, the target sample set generating module is specifically configured to:
determining a target sample according to the basic class attribute, basic information corresponding to the basic class attribute, the disturbance class attribute and disturbance parameters corresponding to the disturbance class attribute;
determining the subsidence value of the earth surface subsidence monitoring point corresponding to the target sample according to the subsidence type attribute and the subsidence value of the earth surface subsidence monitoring point corresponding to the subsidence type attribute;
and generating a target sample set according to the target sample and the subsidence value of the earth surface subsidence monitoring point corresponding to the target sample.
Optionally, the surface subsidence monitoring point subsidence value determining module is specifically configured to:
establishing an initial model;
inputting the target samples in the target sample set into an initial model to obtain a predicted earth surface subsidence monitoring point subsidence value;
training parameters of the initial model according to an objective function formed by the subsidence value of the predicted surface subsidence monitoring point and the subsidence value of the surface subsidence monitoring point corresponding to the objective sample;
and returning to perform the operation of inputting the target samples in the target sample set into an initial model to obtain a settlement value of the predicted earth surface settlement monitoring point until a settlement prediction model is obtained.
Optionally, the basic information corresponding to the basic class attribute includes: the soil property parameters and tunnel process parameters, and the disturbance parameters corresponding to the disturbance type attributes comprise: incision disturbance parameters, attitude disturbance parameters and shield tail disturbance parameters.
Optionally, the real-time construction data includes: engineering foundation data and construction parameters of the current construction project.
The product can execute the method provided by any embodiment of the invention, and has the corresponding functional modules and beneficial effects of the execution method.
According to the technical scheme, real-time construction data are obtained; inputting the real-time construction data into a settlement prediction model to obtain a settlement value of a ground surface settlement monitoring point corresponding to the real-time construction data, wherein the settlement prediction model is obtained by iteratively training an initial model through a target sample set, and the target sample set comprises: the method comprises the steps that a target sample and a ground surface subsidence monitoring point subsidence value corresponding to the target sample are included, wherein the target sample comprises: the foundation information samples and the disturbance parameter samples can obtain the subsidence value of the earth surface subsidence monitoring point corresponding to the real-time construction data, and further the situation that the safety of surrounding buildings is affected due to the fact that subsidence exceeds a control range is prevented.
Example III
Fig. 4 shows a schematic diagram of the structure of an electronic device 10 that may be used to implement an embodiment of the invention. Electronic devices are intended to represent various forms of digital computers, such as laptops, desktops, workstations, personal digital assistants, servers, blade servers, mainframes, and other appropriate computers. Electronic equipment may also represent various forms of mobile devices, such as personal digital processing, cellular telephones, smartphones, wearable devices (e.g., helmets, glasses, watches, etc.), and other similar computing devices. The components shown herein, their connections and relationships, and their functions, are meant to be exemplary only, and are not meant to limit implementations of the inventions described and/or claimed herein.
As shown in fig. 4, the electronic device 10 includes at least one processor 11, and a memory, such as a Read Only Memory (ROM) 12, a Random Access Memory (RAM) 13, etc., communicatively connected to the at least one processor 11, in which the memory stores a computer program executable by the at least one processor, and the processor 11 may perform various appropriate actions and processes according to the computer program stored in the Read Only Memory (ROM) 12 or the computer program loaded from the storage unit 18 into the Random Access Memory (RAM) 13. In the RAM 13, various programs and data required for the operation of the electronic device 10 may also be stored. The processor 11, the ROM 12 and the RAM 13 are connected to each other via a bus 14. An input/output (I/O) interface 15 is also connected to bus 14.
Various components in the electronic device 10 are connected to the I/O interface 15, including: an input unit 16 such as a keyboard, a mouse, etc.; an output unit 17 such as various types of displays, speakers, and the like; a storage unit 18 such as a magnetic disk, an optical disk, or the like; and a communication unit 19 such as a network card, modem, wireless communication transceiver, etc. The communication unit 19 allows the electronic device 10 to exchange information/data with other devices via a computer network, such as the internet, and/or various telecommunication networks.
The processor 11 may be a variety of general and/or special purpose processing components having processing and computing capabilities. Some examples of processor 11 include, but are not limited to, a Central Processing Unit (CPU), a Graphics Processing Unit (GPU), various specialized Artificial Intelligence (AI) computing chips, various processors running machine learning model algorithms, digital Signal Processors (DSPs), and any suitable processor, controller, microcontroller, etc. The processor 11 performs the various methods and processes described above, such as the shield construction earth surface subsidence prediction method.
In some embodiments, the shield construction surface subsidence prediction method may be implemented as a computer program tangibly embodied on a computer-readable storage medium, such as storage unit 18. In some embodiments, part or all of the computer program may be loaded and/or installed onto the electronic device 10 via the ROM 12 and/or the communication unit 19. When the computer program is loaded into RAM 13 and executed by processor 11, one or more steps of the shield construction surface subsidence prediction method described above may be performed. Alternatively, in other embodiments, processor 11 may be configured to perform the shield construction surface subsidence prediction method by any other suitable means (e.g., by means of firmware).
Various implementations of the systems and techniques described here above may be implemented in digital electronic circuitry, integrated circuit systems, field Programmable Gate Arrays (FPGAs), application Specific Integrated Circuits (ASICs), application Specific Standard Products (ASSPs), systems On Chip (SOCs), load programmable logic devices (CPLDs), computer hardware, firmware, software, and/or combinations thereof. These various embodiments may include: implemented in one or more computer programs, the one or more computer programs may be executed and/or interpreted on a programmable system including at least one programmable processor, which may be a special purpose or general-purpose programmable processor, that may receive data and instructions from, and transmit data and instructions to, a storage system, at least one input device, and at least one output device.
A computer program for carrying out methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general purpose computer, special purpose computer, or other programmable data processing apparatus, such that the computer programs, when executed by the processor, cause the functions/acts specified in the flowchart and/or block diagram block or blocks to be implemented. The computer program may execute entirely on the machine, partly on the machine, as a stand-alone software package, partly on the machine and partly on a remote machine or entirely on the remote machine or server.
In the context of the present invention, a computer-readable storage medium may be a tangible medium that can contain, or store a computer program for use by or in connection with an instruction execution system, apparatus, or device. The computer readable storage medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. Alternatively, the computer readable storage medium may be a machine readable signal medium. More specific examples of a machine-readable storage medium would include an electrical connection based on one or more wires, a portable computer diskette, 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 disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.
To provide for interaction with a user, the systems and techniques described here can be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to a user; and a keyboard and a pointing device (e.g., a mouse or a trackball) through which a user can provide input to the electronic device. Other kinds of devices may also be used to provide for interaction with a user; for example, feedback provided to the user may be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user may be received in any form, including acoustic input, speech input, or tactile input.
The systems and techniques described here can be implemented in a computing system that includes a background component (e.g., as a data server), or that includes a middleware component (e.g., an application server), or that includes a front-end component (e.g., a user computer having a graphical user interface or a web browser through which a user can interact with an implementation of the systems and techniques described here), or any combination of such background, middleware, or front-end components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: local Area Networks (LANs), wide Area Networks (WANs), blockchain networks, and the internet.
The computing system may include clients and servers. The client and server are typically remote from each other and typically interact through a communication network. The relationship of client and server arises by virtue of computer programs running on the respective computers and having a client-server relationship to each other. The server can be a cloud server, also called a cloud computing server or a cloud host, and is a host product in a cloud computing service system, so that the defects of high management difficulty and weak service expansibility in the traditional physical hosts and VPS service are overcome.
It should be appreciated that various forms of the flows shown above may be used to reorder, add, or delete steps. For example, the steps described in the present invention may be performed in parallel, sequentially, or in a different order, so long as the desired results of the technical solution of the present invention are achieved, and the present invention is not limited herein.
The above embodiments do not limit the scope of the present invention. It will be apparent to those skilled in the art that various modifications, combinations, sub-combinations and alternatives are possible, depending on design requirements and other factors. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present invention should be included in the scope of the present invention.
Claims (10)
1. The method for predicting the subsidence of the earth surface of the shield construction is characterized by comprising the following steps:
acquiring real-time construction data;
inputting the real-time construction data into a settlement prediction model to obtain a settlement value of a ground surface settlement monitoring point corresponding to the real-time construction data, wherein the settlement prediction model is obtained by iteratively training an initial model through a target sample set, and the target sample set comprises: the method comprises the steps that a target sample and a ground surface subsidence monitoring point subsidence value corresponding to the target sample are included, wherein the target sample comprises: a basic information sample and a disturbance parameter sample.
2. The method of claim 1, further comprising, prior to iteratively training the initial model by the set of target samples:
acquiring historical construction data;
extracting element attributes of the historical construction data to obtain attribute sets and characteristic parameters corresponding to each attribute in the attribute sets;
and generating a target sample set according to the attribute set and the characteristic parameters corresponding to each attribute in the attribute set.
3. The method of claim 2, wherein the set of attributes comprises: the system comprises a basic class attribute, a disturbance class attribute and a sedimentation class attribute, wherein characteristic parameters corresponding to the basic class attribute are basic information corresponding to the basic class attribute, characteristic parameters corresponding to the disturbance class attribute are disturbance parameters corresponding to the disturbance class attribute, and characteristic parameters corresponding to the sedimentation class attribute are ground surface sedimentation monitoring point sedimentation values corresponding to the sedimentation class attribute.
4. A method according to claim 3, wherein generating a target sample set from the set of attributes and the feature parameters corresponding to each attribute in the set of attributes comprises:
determining a target sample according to the basic class attribute, basic information corresponding to the basic class attribute, the disturbance class attribute and disturbance parameters corresponding to the disturbance class attribute;
determining the subsidence value of the earth surface subsidence monitoring point corresponding to the target sample according to the subsidence type attribute and the subsidence value of the earth surface subsidence monitoring point corresponding to the subsidence type attribute;
and generating a target sample set according to the target sample and the subsidence value of the earth surface subsidence monitoring point corresponding to the target sample.
5. The method of claim 4, wherein iteratively training the initial model through the set of target samples comprises:
establishing an initial model;
inputting the target samples in the target sample set into an initial model to obtain a predicted earth surface subsidence monitoring point subsidence value;
training parameters of the initial model according to an objective function formed by the subsidence value of the predicted surface subsidence monitoring point and the subsidence value of the surface subsidence monitoring point corresponding to the objective sample;
and returning to perform the operation of inputting the target samples in the target sample set into an initial model to obtain a settlement value of the predicted earth surface settlement monitoring point until a settlement prediction model is obtained.
6. The method of claim 5, wherein the base information corresponding to the base class attribute comprises: the soil property parameters and tunnel process parameters, and the disturbance parameters corresponding to the disturbance type attributes comprise: incision disturbance parameters, attitude disturbance parameters and shield tail disturbance parameters.
7. The method of claim 1, wherein the real-time construction data comprises: engineering foundation data and construction parameters of the current construction project.
8. The utility model provides a shield constructs construction earth's surface subsidence prediction device which characterized in that includes:
the real-time construction data acquisition module is used for acquiring real-time construction data;
the subsidence value determining module of the earth surface subsidence monitoring point is used for inputting the real-time construction data into a subsidence prediction model to obtain the subsidence value of the earth surface subsidence monitoring point corresponding to the real-time construction data, wherein the subsidence prediction model is obtained by iteratively training an initial model through a target sample set, and the target sample set comprises: the method comprises the steps that a target sample and a ground surface subsidence monitoring point subsidence value corresponding to the target sample are included, wherein the target sample comprises: a basic information sample and a disturbance parameter sample.
9. An electronic device, the electronic device comprising:
at least one processor; and
a memory communicatively coupled to the at least one processor; wherein,
the memory stores a computer program executable by the at least one processor to enable the at least one processor to perform the shield construction surface subsidence prediction method of any one of claims 1-7.
10. A computer readable storage medium, characterized in that the computer readable storage medium stores computer instructions for causing a processor to implement the shield construction surface subsidence prediction method of any one of claims 1-7 when executed.
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