CN113378346A - Method and device for model simulation - Google Patents
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Abstract
The invention discloses a method and a device for model simulation, and relates to the technical field of computers. One embodiment of the method comprises: constructing a simulation task, wherein the simulation task comprises the following steps: model identification and parameter identification; obtaining model data of a simulation model corresponding to the model identification according to the parameter identification and a preset basic database; executing the simulation task based on the model data and the simulation model. The implementation mode can realize the configurability of the simulation model and the basic data, greatly shorten the simulation time of the model simulation and improve the efficiency of the model simulation.
Description
Technical Field
The invention relates to the technical field of computers, in particular to a method and a device for model simulation.
Background
The model emulation is to verify the model quality, and the efficiency of the model emulation determines the progress of the model online. In the prior art, when performing model simulation, basic data required by a simulation model needs to be processed, model data required by the simulation model needs to be specified, developed model codes are manually submitted and executed, and a manual report is generated to analyze and verify the simulation model. However, the method has the problems of complex operation, long simulation period and the like, and the simulation efficiency is low.
Disclosure of Invention
In view of this, embodiments of the present invention provide a method and an apparatus for model simulation, which can implement configurability of a simulation model and basic data, greatly shorten simulation duration of model simulation, and improve efficiency of model simulation.
To achieve the above object, according to an aspect of an embodiment of the present invention, there is provided a method of model simulation, including:
constructing a simulation task, wherein the simulation task comprises the following steps: model identification and parameter identification;
obtaining model data of a simulation model corresponding to the model identification according to the parameter identification and a preset basic database;
executing the simulation task based on the model data and the simulation model.
Optionally, obtaining model data of the simulation model corresponding to the model identifier according to the parameter identifier and a preset basic database, including:
judging whether model data corresponding to the parameter identification exist in a preset model database or not; if so, acquiring the model data; otherwise, acquiring basic data corresponding to the parameter identification from the preset basic database, taking the acquired basic data as model data of the simulation model, and storing the model data into the model database.
Optionally, after the simulation task is built, the method further includes: writing the simulation task into a message queue;
obtaining model data of the simulation model corresponding to the model identification, including: acquiring model data of each simulation task in the message queue by adopting a big data platform;
executing the simulation task based on the model data and the simulation model, including: and executing each simulation task in the message queue by adopting a distributed system based on the model data and the simulation model.
Optionally, after the simulation task is executed based on the model data and the simulation model, the method further includes:
displaying the simulation result of the simulation task in a visualized manner; or screening a target simulation result from the simulation results according to result constraint conditions in the simulation tasks and visually displaying the target simulation result.
According to a second aspect of the embodiments of the present invention, there is provided an apparatus for model simulation, including:
the task construction module is used for constructing a simulation task, and the simulation task comprises the following steps: model identification and parameter identification;
the data acquisition module is used for acquiring model data of the simulation model corresponding to the model identification according to the parameter identification and a preset basic database;
a task execution module that executes the simulation task based on the model data and the simulation model.
Optionally, the obtaining, by the data obtaining module, model data of the simulation model corresponding to the model identifier according to the parameter identifier and a preset basic database includes:
judging whether model data corresponding to the parameter identification exist in a preset model database or not; if so, acquiring the model data; otherwise, acquiring basic data corresponding to the parameter identification from the preset basic database, taking the acquired basic data as model data of the simulation model, and storing the model data into the model database.
Optionally, the task receiving module is further configured to: writing the simulation task into a message queue;
the data acquisition module is further configured to: acquiring model data of each simulation task in the message queue by adopting a big data platform;
the task execution module is further configured to: and executing each simulation task in the message queue by adopting a distributed system based on the model data and the simulation model.
Optionally, the apparatus of the embodiment of the present invention further includes a visualization module, configured to: after the simulation task is executed based on the model data and the simulation model, a simulation result of the simulation task is visually displayed; or screening a target simulation result from the simulation results according to result constraint conditions in the simulation tasks and visually displaying the target simulation result.
According to a third aspect of embodiments of the present invention, there is provided an electronic device for model simulation, including:
one or more processors;
a storage device for storing one or more programs,
when the one or more programs are executed by the one or more processors, the one or more processors are caused to implement the method provided by the first aspect of the embodiments of the present invention.
According to a fourth aspect of embodiments of the present invention, there is provided a computer readable medium, on which a computer program is stored, which when executed by a processor, implements the method provided by the first aspect of embodiments of the present invention.
One embodiment of the above invention has the following advantages or benefits: model data are obtained according to the parameter identification, manual data specification is not needed during simulation each time, and the construction time of a simulation task can be greatly shortened; the simulation model is determined according to the model identification, model codes do not need to be manually submitted each time simulation is simulated, and sharing of the model and related data can be achieved. The invention can realize the configurability of the simulation model and the basic data, greatly shorten the simulation time of the model simulation and improve the efficiency of the model simulation.
Further effects of the above-mentioned non-conventional alternatives will be described below in connection with the embodiments.
Drawings
The drawings are included to provide a better understanding of the invention and are not to be construed as unduly limiting the invention. Wherein:
FIG. 1 is a schematic diagram of the main flow of a method of model simulation of an embodiment of the present invention;
FIG. 2 is a schematic diagram of data processing flow in an alternative embodiment of the invention;
FIG. 3 is a schematic diagram of a method of model simulation in an alternative embodiment of the invention;
FIG. 4 is a schematic diagram of the main blocks of an apparatus for model simulation of an embodiment of the present invention;
FIG. 5 is an exemplary system architecture diagram in which embodiments of the present invention may be employed;
fig. 6 is a schematic block diagram of a computer system suitable for use in implementing a terminal device or server of an embodiment of the invention.
Detailed Description
Exemplary embodiments of the present invention are described below with reference to the accompanying drawings, in which various details of embodiments of the invention are included to assist understanding, and which are to be considered as merely exemplary. Accordingly, those of ordinary skill in the art will recognize that various changes and modifications of the embodiments described herein can be made without departing from the scope and spirit of the invention. Also, descriptions of well-known functions and constructions are omitted in the following description for clarity and conciseness.
According to an aspect of an embodiment of the present invention, a method of model simulation is provided.
Fig. 1 is a schematic diagram of a main flow of a model simulation method according to an embodiment of the present invention, and as shown in fig. 1, the model simulation method includes: step S101, step S102, and step S103.
Step S101, constructing a simulation task, wherein the simulation task comprises the following steps: model identification and parameter identification.
The invention can pre-store each simulation model to form a simulation model library so as to realize the simulation of multiple models. In the practical application process, the simulation model in the simulation model library can be modified and deleted, and a new model can be added into the simulation model library to realize expandability. The model identification is used to uniquely represent a simulation model.
The invention extracts the basic data required by each simulation model in advance to form a basic database. The underlying data refers to the common data used as required by all or a portion of the simulation models. Taking the e-commerce field as an example, the basic data can be data such as commodity information, sales information and the like; taking the mobile communication field as an example, the basic data may be client information, mobile package information, user quantity information of each mobile package, and the like. In the practical application process, the basic data in the basic database can be modified and deleted, and new basic data can be added into the basic database, so that the expandability is realized. The parameter identification is an identification of the underlying data, reflecting the parameter processing logic of a simulation model (i.e., the logic that screens model data from the underlying database). The basic data corresponding to the same parameter identifier is data required to be used by a simulation model, that is, the parameter identifier is used for indicating which basic data in the basic database needs to be selected by a simulation task.
And S102, obtaining model data of the simulation model corresponding to the model identification according to the parameter identification and a preset basic database.
And determining the simulation model to be simulated according to the model identification, and sharing the model and related data without manually submitting model codes during simulation each time. The invention can realize the configurability of the simulation model and the basic data, greatly shorten the simulation time of the model simulation and improve the efficiency of the model simulation.
The model data refers to basic data which is screened from a basic database and corresponds to the parameter identification. Model data are obtained according to the parameter identification, manual data specification in simulation is not needed each time, configurability of a simulation model and basic data can be achieved, simulation time of model simulation is greatly shortened, and efficiency of model simulation is improved.
Optionally, obtaining model data of the simulation model corresponding to the model identifier according to the parameter identifier and a preset basic database, including: judging whether model data corresponding to the parameter identification exist in a preset model database or not; if so, acquiring the model data; otherwise, acquiring basic data corresponding to the parameter identification from the preset basic database, taking the acquired basic data as model data of the simulation model, and storing the model data into the model database.
Fig. 2 is a schematic diagram of a data processing flow in an alternative embodiment of the invention. In this example, basic data such as commodity information, sales information, stock information, and the like are stored in advance to form a basic database. And then acquiring corresponding basic data from the basic database according to the parameter processing logic of each simulation model, and obtaining and storing the model data of each simulation model.
The model data of each simulation model can be distinguished by task codes, so that different simulation tasks use different model data and the model data are mutually isolated. The embodiment can reduce the defect of repeated processing of data among simulation models, and can directly execute the simulation task according to the stored model data when the subsequent simulation models are simulated, so that only one part of model data needs to be stored in the same simulation model, the manual data specification during simulation at each time is not needed, the sharing of relevant data of the model is realized, and meanwhile, the improvement of the data construction efficiency is facilitated.
Step S103, executing the simulation task based on the model data and the simulation model. In this step, the simulation model is used to process the model data to obtain a simulation result. The simulation results may be used to evaluate the simulation model.
Optionally, after the simulation task is executed based on the model data and the simulation model, the method further includes: and displaying the simulation result of the simulation task in a visualized manner.
Taking a simulation model for inventory management as an example, the model includes two constraint conditions that are restricted with each other, namely turnover and stock rate. The high turnover can lead to high stock ratio and increased stock-keeping cost; the low turnover will result in low stock-in-stock ratio and affect the shopping experience of the user. When the simulation task is executed, the expression conditions of the two indexes under each scene can be calculated by exhaustively exhausting scenes as much as possible, and the simulation result is visually displayed. The business party can evaluate the simulation model according to the displayed simulation result or screen the simulation result meeting the business requirement.
The simulation result is displayed visually, so that the simulation personnel can screen the optimal simulation result, the monitoring of parameter indexes in the simulation process is more comprehensive, the abnormal condition of the simulation model in the simulation process can be found, and the optimization and the reconstruction of the simulation model are facilitated.
After executing the simulation task based on the model data and the simulation model, the method may also include: and screening a target simulation result from the simulation results according to the result constraint conditions in the simulation task, and visually displaying the target simulation result. The constraint condition represents a condition that a target simulation result needs to meet, and specific content of the constraint condition can be selectively set according to actual conditions. According to the constraint conditions specified by simulation personnel when constructing the simulation task, the optimal parameters meeting the constraint conditions are searched, the function has better effect when the multi-parameter model is simulated, and the simulation personnel can analyze the simulation result conveniently.
Optionally, after the simulation task is built, the method further includes: writing the simulation task into a message queue; obtaining model data of the simulation model corresponding to the model identification, including: acquiring model data of each simulation task in the message queue by adopting a big data platform; executing the simulation task based on the model data and the simulation model, including: and executing each simulation task in the message queue by adopting a distributed system based on the model data and the simulation model.
The big data platform is a computing cluster which is built by using distributed real-time or off-line computing frameworks such as Hadoop (a distributed system infrastructure), Spark (a computing engine), Storm (Twitter open source distributed real-time big data processing framework) and the like, and various computing tasks are run on the computing cluster.
Fig. 3 is a schematic diagram of a model simulation method in an alternative embodiment of the present invention, in which a front page is responsible for visualization. In this example, after the simulation task is constructed by the front page, the simulation task is written into JMQ (a message middleware system in kyoto research), and model data corresponding to each simulation task is acquired by a BDP (Beagledata Platform, an enterprise-level big data middleware Platform based on the Hadoop ecosystem). Task1, Task2, … … and Task in the BDP respectively represent a Task for acquiring model data, each Task acquires the model data from a basic database through data preprocessing or acquires the model data from the model database, and the acquired model data are pushed to Spark through data pushing. After the data preprocessing in the BDP is finished, a notification message can be sent to the front-end page through the JMQ message queue to notify that the basic data required by the front-end page model is processed. After the front-end page receives the notification message, it issues a computation task to Spark through JSF (Java server Faces), which is a standard framework for building Java Web applications, to notify Spark to execute the simulation task. Task1, Task2, … … and Task N in Spark represent a Task for executing the simulation Task in the message queue respectively, and the simulation result is stored to Phoenix (an SQL layer constructed on HBase). After the simulation result is obtained, a notification message can be sent to the front-end page through the JMQ message queue to notify the front-end page that the simulation task is completed. Phoenix can process the simulation result, for example, screening a target simulation result according to the constraint condition, and then sending a notification message to the front-end page to notify the front-end page that the data processing of the simulation result is finished. And after the simulation result is stored to Phoenix, the simulation result can be sent to a front-end page to visually display the simulation result.
In the embodiment, a large data platform and a scheduling system are utilized to realize the whole simulation process, a simulator can conveniently construct simulation tasks based on a front-end page, the operating environment of each simulation task is independent and does not interfere with each other, the normal operation of a simulation model is ensured, and the scheduling system realized based on a message queue can submit the tasks in real time and monitor the state and progress of the tasks all the time. The embodiment can realize the processes of constructing the simulation task, monitoring the simulation process and presenting the simulation result, and can visualize the simulation full link.
According to a second aspect of the embodiments of the present invention, there is provided an apparatus for implementing the above method.
FIG. 4 is a schematic diagram of the main modules of a model simulation apparatus according to an embodiment of the present invention, and as shown in FIG. 4, the model simulation apparatus 400 includes:
the task construction module 401 constructs a simulation task, where the simulation task includes: model identification and parameter identification;
a data obtaining module 402, configured to obtain model data of the simulation model corresponding to the model identifier according to the parameter identifier and a preset basic database;
a task execution module 403 for executing the simulation task based on the model data and the simulation model.
Optionally, the obtaining, by the data obtaining module, model data of the simulation model corresponding to the model identifier according to the parameter identifier and a preset basic database includes:
judging whether model data corresponding to the parameter identification exist in a preset model database or not; if so, acquiring the model data; otherwise, acquiring basic data corresponding to the parameter identification from the preset basic database, taking the acquired basic data as model data of the simulation model, and storing the model data into the model database.
Optionally, the task receiving module is further configured to: writing the simulation task into a message queue;
the data acquisition module is further configured to: acquiring model data of each simulation task in the message queue by adopting a big data platform;
the task execution module is further configured to: and executing each simulation task in the message queue by adopting a distributed system based on the model data and the simulation model.
Optionally, the apparatus of the embodiment of the present invention further includes a visualization module, configured to: after the simulation task is executed based on the model data and the simulation model, a simulation result of the simulation task is visually displayed; or screening a target simulation result from the simulation results according to result constraint conditions in the simulation tasks and visually displaying the target simulation result.
According to a third aspect of embodiments of the present invention, there is provided an electronic device for model simulation, including:
one or more processors;
a storage device for storing one or more programs,
when the one or more programs are executed by the one or more processors, the one or more processors are caused to implement the method provided by the first aspect of the embodiments of the present invention.
According to a fourth aspect of embodiments of the present invention, there is provided a computer readable medium, on which a computer program is stored, which when executed by a processor, implements the method provided by the first aspect of embodiments of the present invention.
FIG. 5 illustrates an exemplary system architecture 500 of a method of model simulation or an apparatus of model simulation to which embodiments of the present invention may be applied.
As shown in fig. 5, the system architecture 500 may include terminal devices 501, 502, 503, a network 504, and a server 505. The network 504 serves to provide a medium for communication links between the terminal devices 501, 502, 503 and the server 505. Network 504 may include various connection types, such as wired, wireless communication links, or fiber optic cables, to name a few.
The user may use the terminal devices 501, 502, 503 to interact with a server 505 over a network 504 to receive or send messages or the like. The terminal devices 501, 502, 503 may have installed thereon various communication client applications, such as shopping-like applications, web browser applications, search-like applications, instant messaging tools, mailbox clients, social platform software, etc. (by way of example only).
The terminal devices 501, 502, 503 may be various electronic devices having a display screen and supporting web browsing, including but not limited to smart phones, tablet computers, laptop portable computers, desktop computers, and the like.
The server 505 may be a server providing various services, such as a background management server (for example only) providing support for shopping websites browsed by users using the terminal devices 501, 502, 503. The backend management server may analyze and perform other processing on the received data such as the product information query request, and feed back a processing result (for example, target push information, product information — just an example) to the terminal device.
It should be noted that the method for model simulation provided by the embodiment of the present invention is generally executed by the server 505, and accordingly, the apparatus for model simulation is generally disposed in the server 505.
It should be understood that the number of terminal devices, networks, and servers in fig. 5 is merely illustrative. There may be any number of terminal devices, networks, and servers, as desired for implementation.
Referring now to FIG. 6, a block diagram of a computer system 600 suitable for use with a terminal device implementing an embodiment of the invention is shown. The terminal device shown in fig. 6 is only an example, and should not bring any limitation to the functions and the scope of use of the embodiments of the present invention.
As shown in fig. 6, the computer system 600 includes a Central Processing Unit (CPU)601 that can perform various appropriate actions and processes according to a program stored in a Read Only Memory (ROM)602 or a program loaded from a storage section 608 into a Random Access Memory (RAM) 603. In the RAM 603, various programs and data necessary for the operation of the system 600 are also stored. The CPU 601, ROM 602, and RAM 603 are connected to each other via a bus 604. An input/output (I/O) interface 605 is also connected to bus 604.
The following components are connected to the I/O interface 605: an input portion 606 including a keyboard, a mouse, and the like; an output portion 607 including a display such as a Cathode Ray Tube (CRT), a Liquid Crystal Display (LCD), and the like, and a speaker; a storage section 608 including a hard disk and the like; and a communication section 609 including a network interface card such as a LAN card, a modem, or the like. The communication section 609 performs communication processing via a network such as the internet. The driver 610 is also connected to the I/O interface 605 as needed. A removable medium 611 such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, or the like is mounted on the drive 610 as necessary, so that a computer program read out therefrom is mounted in the storage section 608 as necessary.
In particular, according to the embodiments of the present disclosure, the processes described above with reference to the flowcharts may be implemented as computer software programs. For example, embodiments of the present disclosure include a computer program product comprising a computer program embodied on a computer readable medium, the computer program comprising program code for performing the method illustrated in the flow chart. In such an embodiment, the computer program may be downloaded and installed from a network through the communication section 609, and/or installed from the removable medium 611. The computer program performs the above-described functions defined in the system of the present invention when executed by the Central Processing Unit (CPU) 601.
It should be noted that the computer readable medium shown in the present invention can 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 electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the foregoing. More specific examples of the computer readable storage medium may include, but are not limited to: an electrical connection having 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. In the present invention, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. In the present invention, however, a computer readable signal medium may include a propagated data signal with computer readable program code embodied therein, for example, in baseband or as part of a carrier wave. Such a propagated data signal may take many forms, including, but not limited to, electro-magnetic, optical, or any suitable combination thereof. A computer readable signal medium may also be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device. Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to: wireless, wire, fiber optic cable, RF, etc., or any suitable combination of the foregoing.
The flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present invention. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams or flowchart illustration, and combinations of blocks in the block diagrams or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
The modules described in the embodiments of the present invention may be implemented by software or hardware. The described modules may also be provided in a processor, which may be described as: a processor comprising: the task construction module is used for constructing a simulation task, and the simulation task comprises the following steps: model identification and parameter identification; the data acquisition module is used for acquiring model data of the simulation model corresponding to the model identification according to the parameter identification and a preset basic database; a task execution module that executes the simulation task based on the model data and the simulation model. Where the names of these modules do not in some cases constitute a limitation of the module itself, for example, a task building module may also be described as a "module that performs the simulation task based on the model data and the simulation model".
As another aspect, the present invention also provides a computer-readable medium that may be contained in the apparatus described in the above embodiments; or may be separate and not incorporated into the device. The computer readable medium carries one or more programs which, when executed by a device, cause the device to comprise: constructing a simulation task, wherein the simulation task comprises the following steps: model identification and parameter identification; obtaining model data of a simulation model corresponding to the model identification according to the parameter identification and a preset basic database; executing the simulation task based on the model data and the simulation model.
According to the technical scheme of the embodiment of the invention, the model data is obtained according to the parameter identification, the manual data specification in each simulation is not needed, and the construction time of the simulation task can be greatly shortened; the simulation model is determined according to the model identification, model codes do not need to be manually submitted each time simulation is simulated, and sharing of the model and related data can be achieved. The invention can realize the configurability of the simulation model and the basic data, greatly shorten the simulation time of the model simulation and improve the efficiency of the model simulation.
The above-described embodiments should not be construed as limiting the scope of the invention. Those skilled in the art will appreciate that various modifications, combinations, sub-combinations, and substitutions can occur, depending on design requirements and other factors. Any modification, equivalent replacement, and improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (10)
1. A method of model simulation, comprising:
constructing a simulation task, wherein the simulation task comprises the following steps: model identification and parameter identification;
obtaining model data of a simulation model corresponding to the model identification according to the parameter identification and a preset basic database;
executing the simulation task based on the model data and the simulation model.
2. The method of claim 1, wherein obtaining model data of the simulation model corresponding to the model identifier according to the parameter identifier and a preset basic database comprises:
judging whether model data corresponding to the parameter identification exist in a preset model database or not; if so, acquiring the model data; otherwise, acquiring basic data corresponding to the parameter identification from the preset basic database, taking the acquired basic data as model data of the simulation model, and storing the model data into the model database.
3. The method of claim 1, wherein after building the simulation task, further comprising: writing the simulation task into a message queue;
obtaining model data of the simulation model corresponding to the model identification, including: acquiring model data of each simulation task in the message queue by adopting a big data platform;
executing the simulation task based on the model data and the simulation model, including: and executing each simulation task in the message queue by adopting a distributed system based on the model data and the simulation model.
4. The method of claim 1, wherein after performing the simulation task based on the model data and the simulation model, further comprising:
displaying the simulation result of the simulation task in a visualized manner; or screening a target simulation result from the simulation results according to result constraint conditions in the simulation tasks and visually displaying the target simulation result.
5. An apparatus for model simulation, comprising:
the task construction module is used for constructing a simulation task, and the simulation task comprises the following steps: model identification and parameter identification;
the data acquisition module is used for acquiring model data of the simulation model corresponding to the model identification according to the parameter identification and a preset basic database;
a task execution module that executes the simulation task based on the model data and the simulation model.
6. The apparatus of claim 5, wherein the data obtaining module obtains model data of the simulation model corresponding to the model identifier according to the parameter identifier and a preset basic database, and includes:
judging whether model data corresponding to the parameter identification exist in a preset model database or not; if so, acquiring the model data; otherwise, acquiring basic data corresponding to the parameter identification from the preset basic database, taking the acquired basic data as model data of the simulation model, and storing the model data into the model database.
7. The apparatus of claim 5, wherein the task receiving module is further to: writing the simulation task into a message queue;
the data acquisition module is further configured to: acquiring model data of each simulation task in the message queue by adopting a big data platform;
the task execution module is further configured to: and executing each simulation task in the message queue by adopting a distributed system based on the model data and the simulation model.
8. The apparatus of claim 5, further comprising a visualization module to: after the simulation task is executed based on the model data and the simulation model, a simulation result of the simulation task is visually displayed; or screening a target simulation result from the simulation results according to result constraint conditions in the simulation tasks and visually displaying the target simulation result.
9. An electronic device for model simulation, comprising:
one or more processors;
a storage device for storing one or more programs,
the one or more programs, when executed by the one or more processors, implement the method of any of claims 1-4.
10. A computer-readable medium, on which a computer program is stored, which, when being executed by a processor, carries out the method according to any one of claims 1-4.
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