A simulation method and device for complex systems

Abstract

The present invention provides a simulation method and device for complex systems, which obtain the maximum number of load-bearing models of the complex system; when a decision enable signal is received, a corresponding priority is set for each functional model in the complex system; the decision enable signal is sent by the MX operation monitoring module after the functional model that needs to be run in the previous solution cycle is monitored to be completed; based on the maximum number of load-bearing models and the priority corresponding to each functional model, the target functional model to be run in the next solution cycle is determined; a simulation enable signal is sent to the target functional model so that the target functional model completes the simulation process. In this solution, by obtaining the maximum number of load-bearing models of the complex system, a priority is set for each functional model in the complex system, so that based on the maximum number of load-bearing models and the priority, a dynamic decision is made as to whether each model in the target simulation cycle is to be run, thereby achieving high-deterministic simulation of the complex system and improving the purpose of simulation confidence.

Description

Technical Field

[0001] The present invention relates to the technical field of system simulation, and in particular to a simulation method and device for complex systems. Background Art

[0002] System simulation is to establish a simulation model that can describe the system structure or behavior process and has certain logical or quantitative relationships based on the purpose of system analysis and the properties of each element and their interrelationships. Experiments or quantitative analysis are carried out based on this to obtain various information needed for correct decision-making.

[0003] When simulating a complex system, such as system simulation, there may be too many model elements, and the model solution and data transmission requirements may exceed the resource carrying capacity, resulting in uncertainty in model solution and data transmission during system simulation, affecting the confidence of the complex system simulation. Summary of the invention

[0004] In view of this, an embodiment of the present invention provides a simulation method and device for a complex system, so as to achieve high-deterministic simulation of the complex system and improve the confidence of the simulation.

[0005] To achieve the above objectives, the embodiments of the present invention provide the following technical solutions:

[0006] A first aspect of an embodiment of the present invention discloses a simulation method for a complex system, which is applied to an MX operation decision module, wherein the MX operation decision module is respectively connected to each functional model in the complex system and an MX operation monitoring module, and the method includes:

[0007] Obtaining the maximum number of load-bearing models of the complex system;

[0008] When a decision-making enable signal is received, a corresponding priority is set for each of the functional models in the complex system; the decision-making enable signal is sent by the MX operation monitoring module after all the functional models that need to be run in the previous solution cycle have been run;

[0009] Based on the maximum number of load-bearing models and the priority corresponding to each of the functional models, determine the target functional model to be run in the next solution cycle from each of the functional models;

[0010] A simulation enable signal is sent to the target functional model so that the target functional model completes the simulation process.

[0011] Preferably, obtaining the maximum number of load-bearing models of the complex system includes:

[0012] Triggering each functional model in the complex system to execute a simulation process, and receiving each completion flag by the MX operation monitoring module; the completion flag is sent by the functional model when the simulation process is completed;

[0013] The number of completion flags received by the MX operation monitoring module is obtained to determine the maximum number of load-bearing models of the complex system.

[0014] Preferably, when the decision enabling signal is received, a corresponding priority is set for each of the functional models in the complex system, including:

[0015] When a decision enabling signal is received, receiving a corresponding priority setting signal for any of the functional models in the complex system;

[0016] Based on the priority setting signal, the priority of the function model is set to a high priority or a low priority; the high priority is used to indicate that the corresponding function model must execute the simulation process in the next solution cycle, and the low priority is used to indicate that the simulation process is executed when the corresponding function model is extracted;

[0017] For each of the low-priority function models, if the execution status of the function model in the previous solution cycle meets a preset condition, the priority of the function model is set to the high priority.

[0018] Preferably, for each of the low-priority functional models, if the execution of the functional model in the previous solution cycle meets a preset condition, setting the priority of the functional model to the high priority includes:

[0019] For each of the functional models of the low priority, determining whether the functional module in the last solution cycle executes a simulation process;

[0020] If so, the priority of the functional module is set to the high priority.

[0021] Preferably, the priorities include: high priority and low priority. Accordingly, the target functional model to be run in the next solution cycle is determined from each functional model based on the maximum number of load-bearing models and the priority corresponding to each functional model, including:

[0022] Counting the number of the function models with high priority;

[0023] If the number of the function models with high priority is less than the maximum number of load models, the difference between the number of the function models with high priority and the maximum number of load models is calculated to obtain the target number;

[0024] Randomly selecting the target number of function models from the function models with low priorities;

[0025] The function model with the high priority and the function models of the target number screened out are determined as the target function models to be run in the next solution cycle.

[0026] A second aspect of an embodiment of the present invention discloses a simulation device for a complex system, which is applied to an MX operation decision module, wherein the MX operation decision module is respectively connected to each functional model in the complex system and the MX operation monitoring module, and the device comprises:

[0027] An acquisition unit, used for acquiring the maximum number of load-bearing models of the complex system;

[0028] A setting unit is used to set a corresponding priority for each of the functional models in the complex system when a decision enable signal is received; the decision enable signal is sent by the MX operation monitoring module after monitoring that all the functional models that need to be run in the previous solution cycle have been run;

[0029] A determination unit, configured to determine a target functional model to be run in a next solution cycle from each of the functional models based on the maximum number of load-bearing models and the priority corresponding to each of the functional models;

[0030] The sending unit is used to send a simulation enable signal to the target function model so that the target function model completes the simulation process.

[0031] Preferably, the acquisition unit is specifically used for:

[0032] Triggering each functional model in the complex system to execute a simulation process, and receiving each completion flag by the MX operation monitoring module; the completion flag is sent by the functional model when the simulation process is completed;

[0033] The number of completion flags received by the MX operation monitoring module is obtained to determine the maximum number of load-bearing models of the complex system.

[0034] Preferably, the setting unit includes:

[0035] A receiving subunit, configured to receive a corresponding priority setting signal for any of the functional models in the complex system when a decision enabling signal is received;

[0036] A first setting subunit is used to set the priority of the function model to a high priority or a low priority based on the priority setting signal; the high priority is used to indicate that the corresponding function model must execute the simulation process in the next solution cycle, and the low priority is used to indicate that the simulation process is executed when the corresponding function model is extracted;

[0037] The second setting subunit is used to set the priority of each of the low-priority function models to the high priority if the execution status of the function model in the previous solution cycle meets the preset conditions.

[0038] Preferably, the second setting subunit is specifically used for:

[0039] For each of the functional models of the low priority, determining whether the functional module in the last solution cycle executes a simulation process;

[0040] If so, the priority of the functional module is set to the high priority.

[0041] Preferably, the priority includes: high priority and low priority, and accordingly, the determination unit is specifically used to:

[0042] Counting the number of the function models with high priority;

[0043] If the number of the function models with high priority is less than the maximum number of load models, the difference between the number of the function models with high priority and the maximum number of load models is calculated to obtain the target number;

[0044] Randomly selecting the target number of function models from the function models with low priorities;

[0045] The function model with the high priority and the function models of the target number screened out are determined as the target function models to be run in the next solution cycle.

[0046] Based on the above-mentioned embodiment of the present invention, a simulation method and device for a complex system are provided, which are applied to an MX operation decision module, and the MX operation decision module is respectively connected to each functional model in the complex system and an MX operation monitoring module, and the method includes: obtaining the maximum number of load-bearing models of the complex system; when a decision enable signal is received, a corresponding priority is set for each functional model in the complex system; the decision enable signal is sent by the MX operation monitoring module after monitoring that all the functional models that need to be run in the previous solution cycle have been run; based on the maximum number of load-bearing models and the priority corresponding to each functional model, the target functional model to be run in the next solution cycle is determined from each functional model; a simulation enable signal is sent to the target functional model, so that the target functional model completes the simulation process. In this scheme, by obtaining the maximum number of load-bearing models of the complex system, a priority is set for each functional model in the complex system, so that based on the maximum number of load-bearing models and the priority, a dynamic decision is made on whether each model in the target simulation cycle is run, thereby achieving high-deterministic simulation of the complex system and improving the purpose of simulation confidence. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on the provided drawings without paying creative work.

[0048] Figure 1 An architecture diagram of a simulation system disclosed in an embodiment of the present invention;

[0049] Figure 2 A flowchart of a simulation method for a complex system disclosed in an embodiment of the present invention;

[0050] Figure 3 A structural diagram of a simulation device for complex systems disclosed in an embodiment of the present invention. DETAILED DESCRIPTION

[0051] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0052] In this application, the terms "comprises", "comprising" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device comprising a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, an element defined by the sentence "comprising a ..." does not exclude the presence of other identical elements in the process, method, article or device comprising the element.

[0053] From the background technology, we can know that when simulating a complex system, such as system simulation, there may be too many model elements, and the model solution and data transmission requirements may exceed the resource carrying capacity, resulting in uncertainty in model solution and data transmission during system simulation, affecting the confidence of the complex system simulation.

[0054] Therefore, an embodiment of the present invention discloses a simulation method and device for a complex system. In this solution, by obtaining the maximum number of load-bearing models of the complex system, a priority is set for each functional model in the complex system, so that based on the maximum number of load-bearing models and the priority, a dynamic decision is made as to whether each model runs within the target simulation cycle, thereby achieving high-deterministic simulation of the complex system and improving the simulation confidence.

[0055] like Figure 1 As shown, it is an architecture diagram of a simulation system disclosed in an embodiment of the present invention, and the system includes: an MX operation decision module 1, an MX operation monitoring module 2 and a complex system 3.

[0056] Among them, the complex system 3 can include multiple functional models. In the embodiment of the present invention, an example is given in which the complex system 3 includes 4 functional models. The 4 functional models are MX1, MX2, MX3 and MX4, and each functional model includes a functional solution unit and a data transmission unit.

[0057] The function solving unit is responsible for calculation, and the data transmission unit is responsible for data transmission, thereby completing the simulation process of the functional model.

[0058] The MX operation decision module 1 has a plurality of output interfaces for simulation enable signals. In the embodiment of the present invention, the four output interfaces SN1 to SN4 for simulation enable signals of the MX operation decision module 1 are connected to MX1 to MX4, respectively.

[0059] The MX operation decision module 1 has multiple input interfaces for priority setting signals. In an embodiment of the present invention, the four input interfaces (YX1 to YX4) for priority setting signals of the MX operation decision module 1 are respectively used to receive the priority setting signals corresponding to MX1 to MX4.

[0060] The MX operation decision module 1 has a decision enable signal input interface, which is connected to the decision enable signal output interface SN0 of the MX operation monitoring module 2.

[0061] The MX operation monitoring module 2 has a plurality of completion mark input interfaces. In the embodiment of the present invention, the four completion mark input interfaces BZ1 to BZ4 of the MX operation monitoring module 2 are connected to MX1 to MX4 respectively.

[0062] During the specific operation of the simulation system, the maximum number of load-bearing models of the complex system 3 is firstly obtained.

[0063] It should be noted that the maximum number of supported models is the number of functional models that the complex system 3 can support and run simultaneously, which can be obtained by testing the complex system 3 in advance. When the functional models in the complex system 3 do not change, the maximum number of supported models does not need to be obtained again during the next solution cycle simulation.

[0064] The specific acquisition method is as follows: by simultaneously triggering each functional model in the complex system 3 to execute the simulation process, the number of functional models that complete the simulation process within a preset time is counted to obtain the maximum number of load-bearing models.

[0065] Among them, the statistical process can be completed by the MX operation monitoring module 2, which receives the completion mark of the functional module completing the simulation process within the preset time, counts the number of completion marks, obtains the number of functional models that complete the simulation process within the preset time, and then obtains the maximum number of load-bearing models.

[0066] In the embodiment of the present invention, an example is given in which the maximum number of load-bearing models of the complex system 3 is three.

[0067] When the MX operation decision module 1 receives the decision enabling signal sent by the MX operation monitoring module 2 , corresponding priorities are set for the function models MX1 to MX4 .

[0068] Among them, when the MX operation monitoring module 2 detects that all the functional models that need to be run in the complex system 3 have been run in the previous solution cycle, it sends a decision enable signal to the MX operation decision module 1.

[0069] Exemplarily, the functional models that need to be run in the complex system 3 in the previous solution cycle are MX1 to MX4. When the MX operation monitoring module 2 detects the completion mark sent by MX1 to MX4, it determines that all the functional models that need to be run in the complex system 3 have been completed, and sends a decision enable signal to the MX operation decision module 1.

[0070] Exemplarily, the priority can be high priority and low priority, wherein the high priority functional model needs to execute the simulation process in the next solution cycle, and the low priority functional model may or may not execute in the next solution cycle, depending on the maximum number of models carried by the complex system 3.

[0071] It should be noted that the priorities mentioned in this application are all examples, and this application does not limit the specific priority settings. For example, setting that the function model corresponding to the low priority in the next solution cycle is not executed is also within the protection scope of this application.

[0072] Specific priority setting method: obtain the corresponding priorities of MX1 to MX4 through the input interface of the priority setting signal of the MX operation decision module 1, and set the corresponding priorities of MX1 to MX4 to high priority or low priority.

[0073] For low-priority functional models, a secondary judgment is performed, that is, its priority is determined based on whether the functional model was running in the previous solution cycle. For example, if MX2 is set to low priority and the simulation process is completed in the previous solution cycle, then MX2 is set to high priority, otherwise, it is set to low priority.

[0074] The MX operation decision module 1 determines the target function model to be run in the next solution cycle from MX1 to MX4 based on the maximum number of load-bearing models and the corresponding priorities of MX1 to MX4.

[0075] Assuming that the priorities of MX1 to MX4 are high priority, high priority, low priority and low priority respectively, MX1 and MX2 are determined as the target function models. Since the maximum number of bearers is 3, a target function model needs to be determined. MX3 and MX4 are both low priorities. Any one of MX3 and MX4 can be randomly determined as the target function model. Assuming that MX3 is set as the target function model, the final target function model is MX1 to MX3.

[0076] Finally, the MX operation decision module 1 sends a simulation enable signal to MX1 to MX3 through the SN1 to SN3 interface, so that MX1 to MX3 complete the simulation process.

[0077] In one embodiment, sending 1 to MX1 to MX3 represents that the simulation enable signal is valid, and sending 0 to MX4 represents that the simulation enable signal is invalid.

[0078] Based on the architecture of a simulation system disclosed in the above embodiment of the present invention, Figure 2 As shown in FIG. 1 , it is a flow chart of a simulation method for a complex system disclosed in an embodiment of the present invention. The method is applied to Figure 1 The MX shown runs the decision module 1.

[0079] The method mainly includes the following steps:

[0080] Step S201: Obtain the maximum number of load-bearing models of the complex system.

[0081] In step S201, the maximum number of supported models is the number of simultaneously running functional models that the complex system can support, which can be obtained by testing the complex system in advance. When the functional models in the complex system do not change, there is no need to re-obtain the maximum number of supported models during simulation in the next solution cycle.

[0082] In the specific implementation process of step S201, each functional model in the complex system is triggered to execute the simulation process, and each completion mark is received by the MX operation monitoring module.

[0083] Among them, the completion flag is sent by the functional model when the simulation process is completed.

[0084] Obtain the number of completion flags received by the MX operation monitoring module to determine the maximum number of models that the complex system can carry.

[0085] It should be noted that the initial state of the completion flag of the functional model is 1, indicating that the previous simulation process has ended and is now in an idle state. When the functional model is triggered to execute the simulation process, the completion flag changes from 1 to 0, indicating that the functional model is in the simulation process. When the simulation is completed, the completion flag changes from 0 to 1 and is sent to the MX operation monitoring module.

[0086] Step S202: When a decision enabling signal is received, a corresponding priority is set for each functional model in the complex system.

[0087] In step 202, the decision enable signal is sent by the MX operation monitoring module after monitoring that all the functional models that need to be run in the previous solution cycle have been run.

[0088] The completion of the function model operation means that the function model completes the simulation process, that is, the solution data is obtained by solving the solution data, and the solution data is transmitted, thus completing the simulation process of the function model.

[0089] From the above, it can be seen that when the MX operation monitoring module receives the completion mark of each functional model changing from 0 to 1, it determines that all the functional models that need to be run in the previous solution cycle have been completed, and sends a decision enable signal with a value of 1 to the MX operation decision module, indicating that the decision enable signal is valid.

[0090] In one embodiment, the priority of each functional model is input to the MX operation decision module in the form of a UI interface or a bus input signal, and the priority of the functional model includes: high priority and low priority.

[0091] Among them, high-priority functional models need to execute the simulation process in the next solution cycle. For low-priority functional models, it is necessary to decide whether to execute the simulation process based on the maximum number of load-bearing models. Please refer to the specific implementation process of step S203.

[0092] In the specific implementation process of step 202, when a decision enabling signal is received, a corresponding priority setting signal is received for any functional model in the complex system.

[0093] Based on the priority setting signal, the priority of the functional model is set to a high priority or a low priority.

[0094] Among them, the high priority is used to represent that the corresponding functional model must execute the simulation process in the next solution cycle, and the low priority is used to represent that the corresponding functional model executes the simulation process when the margin based on the maximum number of load-bearing models is extracted.

[0095] For each low-priority functional model, if the execution status of the functional model in the previous solution cycle meets the preset conditions, the priority of the functional model is set to a high priority.

[0096] It should be noted that the functional model that executed the simulation process in the previous solution cycle also needs to execute the simulation process in the next solution cycle. Therefore, it is necessary to perform a secondary judgment on the functional models that have been set to a low priority, filter out the functional models that have executed the simulation process in the previous solution cycle, and reset their priority to a high priority.

[0097] Specifically, for each low-priority functional model, it is determined whether the functional module in the previous solution cycle executes the simulation process;

[0098] If so, set the priority of the functional module to high priority.

[0099] If not, do nothing, i.e. keep the priority of the function model as low priority.

[0100] It should be noted that whether a certain functional model was executed in the previous solution cycle is determined by whether the MX operation monitoring module receives the completion mark sent by the functional model. If the completion mark of the functional model is received, it means that the functional model has executed the simulation process in the previous solution cycle.

[0101] Step S203: Based on the maximum number of load-bearing models and the priority corresponding to each functional model, determine the target functional model to be run in the next solution cycle from each functional model.

[0102] In step S203, the number of target function models finally determined needs to be equal to the maximum number of load-bearing models.

[0103] The specific implementation process of step S203 includes the following steps:

[0104] Step S11: Count the number of high-priority function models.

[0105] It should be noted that if the number of high-priority function models is equal to the maximum number of load-bearing models, the high-priority function model will be determined as the target function model to be run in the next solution cycle, and there is no need to perform the following steps.

[0106] If the number of high-priority functional models is greater than the maximum number of bearing models, it means that the priority setting is incorrect, and a reminder signal that the priority needs to be reset is generated. There is no need to perform the following steps.

[0107] Step S12: If the number of high-priority function models is less than the maximum number of load-bearing models, the difference between the number of high-priority function models and the maximum number of load-bearing models is calculated to obtain the target number.

[0108] It should be noted that the number of high-priority functional models is less than the maximum number of load-bearing models, which means that there is still margin in the complex system, and it is necessary to randomly extract functional models from the low-priority functional models so that the number of functional models executing the simulation process in the next solution cycle is equal to the maximum number of load-bearing models.

[0109] Step S13: Randomly select a target number of function models from the low-priority function models.

[0110] Step S14: Determine the high-priority function models and the screened target number of function models as the target function models to be run in the next solution cycle.

[0111] Step S204: Send a simulation enable signal to the target functional model so that the target functional model completes the simulation process.

[0112] In step S204, a simulation enable signal with a value of 1 is sent to the target function model, indicating that the simulation enable signal is valid, so that the target function model completes the simulation process.

[0113] A simulation enable signal with a value of 0 is sent to various functional models of the complex system except the target functional model, indicating that the simulation enable signal is invalid, so that the target functional model does not execute the simulation process.

[0114] Based on the above-mentioned embodiment of the present invention, a simulation method for a complex system is disclosed, the maximum number of load-bearing models of the complex system is obtained; when a decision enable signal is received, a corresponding priority is set for each functional model in the complex system; the decision enable signal is sent by the MX operation monitoring module after monitoring that all the functional models that need to be run in the previous solution cycle have been run; based on the maximum number of load-bearing models and the priority corresponding to each functional model, the target functional model to be run in the next solution cycle is determined from each functional model; a simulation enable signal is sent to the target functional model so that the target functional model completes the simulation process. In this solution, by obtaining the maximum number of load-bearing models of the complex system, a priority is set for each functional model in the complex system, so that based on the maximum number of load-bearing models and the priority, a dynamic decision is made as to whether each model in the target simulation cycle is to be run, thereby achieving high-deterministic simulation of the complex system and improving the purpose of simulation confidence.

[0115] Based on the above embodiment of the present invention, a simulation method for a complex system is disclosed, such as Figure 3 As shown in FIG. 1 , a structural diagram of a simulation device for a complex system disclosed in an embodiment of the present invention is shown in FIG. Figure 1 The MX shown runs the decision module 1.

[0116] Specifically, the simulation device for complex systems includes: an acquisition unit 301 , a setting unit 302 , a determination unit 303 and a sending unit 304 .

[0117] The acquisition unit 301 is used to acquire the maximum number of load-bearing models of the complex system;

[0118] In one embodiment, the acquisition unit 301 is specifically configured to:

[0119] Trigger each functional model in the complex system to execute the simulation process, and the MX operation monitoring module receives each completion flag; the completion flag is sent by the functional model when the simulation process is completed;

[0120] Obtain the number of completion flags received by the MX operation monitoring module to determine the maximum number of models that the complex system can carry.

[0121] The setting unit 302 is used to set a corresponding priority for each functional model in the complex system when receiving a decision enable signal; the decision enable signal is sent by the MX operation monitoring module after monitoring that all functional models that need to be run in the previous solution cycle have been run;

[0122] In one embodiment, the setting unit 302 includes:

[0123] A receiving subunit, for receiving a corresponding priority setting signal for any functional model in the complex system when a decision enabling signal is received;

[0124] A first setting subunit is used to set the priority of the function model to a high priority or a low priority based on a priority setting signal; the high priority is used to indicate that the corresponding function model must execute the simulation process in the next solution cycle, and the low priority is used to indicate that the corresponding function model executes the simulation process when it is extracted;

[0125] The second setting subunit is used to set the priority of each low-priority function model to a high priority if the execution status of the function model in the previous solution cycle meets the preset conditions.

[0126] In one embodiment, the second setting subunit is specifically used for:

[0127] For each low-priority functional model, determine whether the functional module in the previous solution cycle executes the simulation process;

[0128] If so, set the priority of the functional module to high priority.

[0129] A determination unit 303, configured to determine a target function model to be run in the next solution cycle from each function model based on the maximum number of load-bearing models and the priority corresponding to each function model;

[0130] In one embodiment, the determining unit 303 is specifically configured to:

[0131] Count the number of high-priority functional models;

[0132] If the number of high-priority function models is less than the maximum number of load-bearing models, the difference between the number of high-priority function models and the maximum number of load-bearing models is calculated to obtain the target number;

[0133] Randomly select a target number of function models from low-priority function models;

[0134] The high-priority function models and the function models with the target number screened out are determined as the target function models to be run in the next solution cycle.

[0135] The sending unit 304 is used to send a simulation enable signal to the target function model so that the target function model completes the simulation process.

[0136] Based on the above-mentioned embodiment of the present invention, a simulation device for a complex system is disclosed, which obtains the maximum number of load-bearing models of the complex system; when a decision enable signal is received, a corresponding priority is set for each functional model in the complex system; the decision enable signal is sent by the MX operation monitoring module after monitoring that all the functional models that need to be run in the previous solution cycle have been run; based on the maximum number of load-bearing models and the priority corresponding to each functional model, the target functional model to be run in the next solution cycle is determined from each functional model; a simulation enable signal is sent to the target functional model so that the target functional model completes the simulation process. In this solution, by obtaining the maximum number of load-bearing models of the complex system, a priority is set for each functional model in the complex system, so that based on the maximum number of load-bearing models and the priority, a dynamic decision is made as to whether each model in the target simulation cycle is to be run, thereby achieving high-deterministic simulation of the complex system and improving the purpose of simulation confidence.

[0137] Each embodiment in this specification is described in a progressive manner, and the same or similar parts between the embodiments can refer to each other, and each embodiment focuses on the differences from other embodiments. In particular, for the system or system embodiment, since it is basically similar to the method embodiment, the description is relatively simple, and the relevant parts can refer to the partial description of the method embodiment. The system and system embodiments described above are merely schematic, wherein the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the scheme of this embodiment. Ordinary technicians in this field can understand and implement it without creative work.

[0138] Professionals may further appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of the two. In order to clearly illustrate the interchangeability of hardware and software, the composition and steps of each example have been generally described in the above description according to function. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professionals and technicians may use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of the present invention.

[0139] The above description of the disclosed embodiments enables one skilled in the art to implement or use the present invention. Various modifications to these embodiments will be apparent to one skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention will not be limited to the embodiments shown herein, but rather to the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A simulation method for a complex system, characterized in that: Applied to the MX operation decision module, the MX operation decision module is respectively connected to each functional model in the complex system and the MX operation monitoring module, the method includes: Obtaining the maximum number of load-bearing models of the complex system; When a decision-making enable signal is received, a corresponding priority is set for each of the functional models in the complex system; the decision-making enable signal is sent by the MX operation monitoring module after all the functional models that need to be run in the previous solution cycle have been run; Based on the maximum number of load-bearing models and the priority corresponding to each of the functional models, determine the target functional model to be run in the next solution cycle from each of the functional models; Sending a simulation enable signal to the target function model so that the target function model completes the simulation process; Wherein, the priorities include: high priority and low priority. Accordingly, the target functional model to be run in the next solution cycle is determined from each functional model based on the maximum number of load-bearing models and the priority corresponding to each functional model, including: Counting the number of the function models with high priority; If the number of the high-priority function models is equal to the maximum number of load-bearing models, the high-priority function model is determined as the target function model to be run in the next solution cycle; If the number of the functional models with high priority is greater than the maximum number of bearing models, a reminder signal for resetting the priority is generated; If the number of the function models with high priority is less than the maximum number of load models, the difference between the number of the function models with high priority and the maximum number of load models is calculated to obtain the target number; Randomly selecting the target number of function models from the function models with low priorities; The function model with the high priority and the function models of the target number screened out are determined as the target function models to be run in the next solution cycle.

2. The method according to claim 1, characterized in that The obtaining of the maximum number of load-bearing models of the complex system includes: Triggering each functional model in the complex system to execute a simulation process, and receiving each completion flag by the MX operation monitoring module; the completion flag is sent by the functional model when the simulation process is completed; The number of completion flags received by the MX operation monitoring module is obtained to determine the maximum number of load-bearing models of the complex system.

3. The method according to claim 1, characterized in that When the decision enabling signal is received, setting a corresponding priority for each of the functional models in the complex system includes: When a decision enabling signal is received, receiving a corresponding priority setting signal for any of the functional models in the complex system; Based on the priority setting signal, the priority of the function model is set to a high priority or a low priority; the high priority is used to indicate that the corresponding function model must execute the simulation process in the next solution cycle, and the low priority is used to indicate that the simulation process is executed when the corresponding function model is extracted; For each of the low-priority function models, if the execution status of the function model in the previous solution cycle meets a preset condition, the priority of the function model is set to the high priority.

4. The method according to claim 3, characterized in that For each of the function models of the low priority, if the execution status of the function model in the previous solution cycle meets the preset condition, setting the priority of the function model to the high priority includes: For each of the functional models of the low priority, determining whether the functional model in the previous solution cycle executes a simulation process; If so, the priority of the functional model is set to the high priority.

5. A simulation device for complex systems, characterized in that: Applied to the MX operation decision module, the MX operation decision module is respectively connected to each functional model in the complex system and the MX operation monitoring module, and the device includes: An acquisition unit, used for acquiring the maximum number of load-bearing models of the complex system; A setting unit is used to set a corresponding priority for each of the functional models in the complex system when a decision enable signal is received; the decision enable signal is sent by the MX operation monitoring module after monitoring that all the functional models that need to be run in the previous solution cycle have been run; A determination unit, configured to determine a target functional model to be run in a next solution cycle from each of the functional models based on the maximum number of load-bearing models and the priority corresponding to each of the functional models; A sending unit, used for sending a simulation enable signal to the target function model so that the target function model completes the simulation process; The priority includes: high priority and low priority. Accordingly, the determination unit is specifically used to: Counting the number of the function models with high priority; If the number of the high-priority function models is equal to the maximum number of load-bearing models, the high-priority function model is determined as the target function model to be run in the next solution cycle; If the number of the functional models with high priority is greater than the maximum number of bearing models, a reminder signal for resetting the priority is generated; If the number of the function models with high priority is less than the maximum number of load models, the difference between the number of the function models with high priority and the maximum number of load models is calculated to obtain the target number; Randomly selecting the target number of function models from the function models with low priorities; The function model with the high priority and the function models of the target number screened out are determined as the target function models to be run in the next solution cycle.

6. The device according to claim 5, characterized in that The acquisition unit is specifically used for: Triggering each functional model in the complex system to execute a simulation process, and receiving each completion flag by the MX operation monitoring module; the completion flag is sent by the functional model when the simulation process is completed; The number of completion flags received by the MX operation monitoring module is obtained to determine the maximum number of load-bearing models of the complex system.

7. The device according to claim 5, characterized in that The setting unit comprises: A receiving subunit, configured to receive a corresponding priority setting signal for any of the functional models in the complex system when a decision enabling signal is received; A first setting subunit is used to set the priority of the function model to a high priority or a low priority based on the priority setting signal; the high priority is used to indicate that the corresponding function model must execute the simulation process in the next solution cycle, and the low priority is used to indicate that the simulation process is executed when the corresponding function model is extracted; The second setting subunit is used to set the priority of each of the low-priority function models to the high priority if the execution status of the function model in the previous solution cycle meets the preset conditions.

8. The device according to claim 7, characterized in that The second setting subunit is specifically used for: For each of the functional models of the low priority, determining whether the functional model in the previous solution cycle executes a simulation process; If so, the priority of the functional model is set to the high priority.

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