Method and system for constructing and optimizing system network activity model

Abstract

The invention belongs to the technical field of system model construction and evaluation. The invention provides a system network activity model construction optimization method and system, and the method comprises the steps: extracting various nodes of a target task based on a function dimension, constructing a respective target activity process node model, and constructing a target activity process node model based on an OODA circulation theory; abstracting an activity process node of the target task into a situation awareness node, an auxiliary decision node, an action control node and an information service node according to functions; determining a basic information link according to a target activity process node model, and forming an activity program chain representing activity efficiency according to mapping and ordered combination from the target activity to the information link; constructing a system network activity model based on the target activity process node model and the multi-information link; and performing efficiency evaluation on the system network activity model by adopting a fuzzy comprehensive evaluation method, and judging whether task activities meet task requirements or not. According to the method, a more effective system network activity model can be obtained, and more effective activity performance evaluation can be realized.

Description

Technical Field

[0001] The present invention belongs to the technical field of model system engineering, and provides a method and system for optimizing the construction of a system network activity model. Background Art

[0002] Model-based systems engineering (MBSE) has been widely applied in complex product engineering fields such as aviation, aerospace, shipbuilding, and automotive. Modeling methods are used to support system requirements, design, analysis, verification, and validation activities, and a logically coherent and consistent general system model runs through the entire life cycle stage of the system. Currently, the main MBSE methodologies include: IBM Harmony based on SysML and OOSE of INCOSE; Vitech MBSE Methodology based on SDL; OPM based on OPDs / OPL, which mainly focuses on the system engineering development domain and operation and maintenance domain. For the design domain goals such as how to efficiently respond to rapid changes in tasks and environments and effectively improve the decision-making efficiency of designers, there are problems such as insufficient theoretical guidance for model construction, overly general system models, relatively coarse model granularity, and incomplete evaluation index systems.

[0003] Currently, there are the following problems: The current activity model design method lacks pertinence, the logical chain is incomplete, and there is a lack of a relatively unified design framework; the existing activity process focuses on function description, lacks overall consideration of the overall effectiveness of activities, and decision-makers cannot comprehensively understand the roles and mutual influences of the activity process nodes in each link in a complex environment; the existing simulation evaluation indicators often fail to fully reflect each link of the OODA loop, resulting in a lack of comprehensiveness in the evaluation results.

[0004] Therefore, it is necessary to provide a new method and system for optimizing the construction of a system network activity model to solve the above problems. Summary of the Invention

[0005] The present invention provides a method and system for optimizing the construction of a system network activity model to solve the technical problems in the prior art such as insufficient theoretical guidance for model construction, overly general system models, relatively coarse model granularity, and incomplete evaluation index systems, as well as design domain goals such as how to efficiently respond to rapid changes in tasks and environments and effectively improve the decision-making efficiency of designers. The technical problems to be solved by the present invention are achieved through the following technical solutions.

[0006] In the first aspect of the present invention, an optimization method for constructing a system network activity model is proposed. The optimization method for constructing a system network activity model includes: extracting various nodes of a target task based on the functional dimension to construct respective target activity process node models, specifically including abstracting the activity process nodes of the target task into the following nodes according to the OODA loop theory: a situation awareness node, an auxiliary decision-making node, an action control node, and an information service node; determining multiple information links according to the target activity process node model, and forming an activity program chain representing activity effectiveness according to the mapping and ordered combination from the target activity to the information links; constructing a system network activity model based on the constructed target activity process node model and multiple information links; using the fuzzy comprehensive evaluation method to evaluate the effectiveness of the constructed system network activity model to determine whether the task activities in the target task meet the task requirements, specifically including: establishing an evaluation matrix based on the to-be-evaluated indicators, and calculating and determining the weight of each to-be-evaluated indicator in the to-be-evaluated system; using the calculated and determined weight and the single-factor evaluation matrix to perform a fuzzy synthesis operation to obtain a comprehensive evaluation result.

[0007] In the second aspect of the present invention, an optimization system for constructing a system network activity model is proposed. It executes the optimization method for constructing a system network activity model described in the first aspect of the present invention. The optimization system for constructing a system network activity model includes: a first construction module that extracts various nodes of a target task based on the functional dimension to construct respective target activity process node models, specifically including abstracting the activity process nodes of the target task into the following nodes according to the OODA loop theory: a situation awareness node, an auxiliary decision-making node, an action control node, and an information service node; a first determination module that determines multiple information links according to the target activity process node model, and forms an activity program chain representing activity effectiveness according to the mapping and ordered combination from the target activity to the information links; a second construction module that constructs a system network activity model based on the constructed target activity process node model and multiple information links; an evaluation and optimization module that uses the fuzzy comprehensive evaluation method to evaluate the effectiveness of the constructed system network activity model to determine whether the task activities in the target task meet the task requirements, specifically including: establishing an evaluation matrix based on the to-be-evaluated indicators, and calculating and determining the weight of each to-be-evaluated indicator in the to-be-evaluated system; using the calculated and determined weight and the single-factor evaluation matrix to perform a fuzzy synthesis operation to obtain a comprehensive evaluation result.

[0008] In the third aspect of the present invention, an electronic device is provided, 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 implement the optimization method for constructing a system network activity model described in the first aspect of the present invention.

[0009] A fourth aspect of the present invention provides a computer-readable medium storing a computer program, which when executed by a processor implements the method for optimizing the construction of the system network activity model according to the first aspect of the present invention.

[0010] The embodiments of the present invention have the following advantages: Compared with the prior art, the present invention specifically represents the activity elements involved in the target task in a concrete form by constructing an activity process node model and each information link model. Based on the observation, judgment, decision-making, and action (OODA) loop process, the information nodes (i.e., activity process nodes) and information links are integrated, refined, and reorganized to form a system network activity model, thereby realizing the effective integration and coordination of information data in a complex multi-dimensional confrontation environment. And based on the simulation evaluation index system of activity effectiveness, it can accurately reflect the effects of each link of OODA. Specifically, the fuzzy comprehensive evaluation method model is used to evaluate the effectiveness of each evaluation index involved in the task activities in the target task, effectively find the evaluation indexes that do not meet the task requirements in the system network activity model and the relevant attributes of the corresponding nodes, adjust the attribute values corresponding to each evaluation index according to the effectiveness evaluation results, and re-evaluate the system network activity model until all evaluation indexes are greater than the corresponding set thresholds, so that all evaluation indexes involved in the activities in the target task meet the task requirements, so as to optimize the system network activity model, and can more effectively optimize the system network activity model while constructing the system network activity model. BRIEF DESCRIPTION OF THE DRAWINGS

[0011] Figure 1 is a flowchart of the steps of an example of the method for optimizing the construction of the system network activity model of the present invention; Figure 2 is a schematic block diagram of an example of the system to be evaluated of the method for optimizing the construction of the system network activity model of the present invention; Figure 3 is a flowchart of the steps of an example of evaluating the effectiveness of the system network activity by using the fuzzy comprehensive evaluation method in the method for optimizing the construction of the system network activity model of the present invention; Figure 4 is a structural block diagram of the system for optimizing the construction of the system network activity model of the present invention; Figure 5 is a schematic structural diagram of an electronic device according to an embodiment of the present invention; Figure 6 is a schematic structural diagram of a computer-readable medium according to an embodiment of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0012] It should be noted that, without conflict, the embodiments in the present application and the features in the embodiments can be combined with each other. The present invention will be described in detail below with reference to the drawings and in conjunction with the embodiments.

[0013] In view of the above problems, the present invention proposes an optimization method for constructing a system network activity model. This method constructs an activity process model system based on OODA and evaluates the simulation evaluation indicators, forming a framework for the system activity process model. Specifically, by constructing an activity process node model and each information link model, the activity elements involved in the target task are concretely represented. Based on the observation, judgment, decision-making, and action (OODA) cycle process, the information nodes (i.e., activity process nodes) and information links are integrated, refined, and reorganized to form a system network activity model, thereby realizing the effective integration and coordination of information data in the complex multi-dimensional confrontation environment. And based on the simulation evaluation index system of activity effectiveness, it can accurately reflect the effects of each link of OODA. Specifically, the fuzzy comprehensive evaluation method model is used to evaluate the effectiveness of each index involved in the task activities in the target task, so as to optimize the system network activity model, and it can more effectively optimize the system network activity model while constructing the system network activity model.

[0014] It should be noted that the method of the present invention has a wide range of applications and is particularly suitable for complex system activity process systems including multiple types of devices, multiple personnel or multiple personnel groups, multiple information service types, and multiple environmental information. For example, an air group confrontation training system, a ground confrontation group system including satellite detection, a mountain search and rescue system, a group confrontation command system, and so on. The above are only illustrative examples and should not be construed as limitations on the present invention.

[0015] Embodiment 1 The following will refer to Figure 1 、 Figure 2 、 Figure 3 to describe the content of the present invention in detail.

[0016] Figure 1 is a flowchart of the steps of an example of the optimization method for constructing a system network activity model of the present invention. Figure 2 is a schematic block diagram of an example of the system to be evaluated of the optimization method for constructing a system network activity model of the present invention.

[0017] Referring to Figure 1 and Figure 2 in step S101, various nodes of the target task are extracted based on the functional dimension to construct their respective target activity process node models, specifically including abstracting the activity process nodes of the target task into the following nodes according to the OODA cycle theory: a situation awareness node, an auxiliary decision-making node, an action control node, an information service node, and an execution node.

[0018] In a specific embodiment, the target task refers to the execution task of an air group confrontation training system.

[0019] The target task includes multiple types of activity process nodes involved in task execution. In this example, an activity process node refers to a set of nodes that execute or participate in an activity process, and the nodes are various types of units (or enterprises), devices, or personnel.

[0020] Specifically, based on the OODA loop theory, the activity process nodes are abstracted into four categories according to their functions, namely, situation awareness nodes , auxiliary decision-making nodes , action control nodes , and information service nodes .

[0021] It should be noted that the OODA loop theory is fully named Observe, Orient, Decide, Act. In this example, it specifically refers to a closed loop formed by the observation stage related to the execution of the target task, the stage of adjusting and controlling actions, the stage of deciding how to execute the actions of the target task, and the stage of executing the target task.

[0022] For example, from the publicly available historical task data, based on the OODA loop theory, the activity process nodes are abstracted into situation awareness nodes , auxiliary decision-making nodes , action control nodes , and information service nodes . Each type of node contains a large amount of information data related to the target task. For example, the information service node contains communication connections between devices, communication connections between personnel and devices, data to be transmitted, data to be shared, etc.

[0023] Specifically, the situation awareness node is used to collect, organize, and analyze environmental information related to the target task to form a comprehensive understanding and perception of the system environment (in this example, the air group confrontation training system). The situation awareness node can monitor the environmental dynamics in real time, specifically including equipment deployment, actions, intentions, as well as positions, statuses, etc., and provide necessary environmental information for auxiliary decision-making. The entities corresponding to the situation awareness node are mainly various types of sensing devices, such as remote sensing satellites, radars, drones, etc.

[0024] The auxiliary decision-making node is used to formulate and execute activity plans and decide on the direction and method of decision-making actions. The auxiliary decision-making node depends on the information support provided by the situation awareness node and, through analysis, evaluation, and decision-making, is used to command various nodes to implement actions. The entities corresponding to the auxiliary decision-making node are mainly various types of command centers.

[0025] The action control node It is used to control and implement activities, receive instructions from the auxiliary decision-making nodes, execute tasks and provide real-time feedback, so as to enable the auxiliary decision-making nodes to adjust and control the actions of the target tasks. The entities corresponding to the auxiliary decision-making nodes are various information control platforms, such as ships, aircraft, special vehicles, etc.

[0026] Information service node It is used to provide various information service supports, specifically including communication, liaison, data sharing and technical support, etc. The entities corresponding to the information service nodes include communication satellites, satellite terminals, ground stations, data centers, etc. The information service nodes provide infrastructure and service supports such as communication connections, data transmissions, and data sharing.

[0027] Furthermore, according to the above four types of node attributes and functional characteristics, an activity process node model corresponding to the target task is abstracted and refined, which can be expressed as:

[0028] Among them, N represents the activity process node model corresponding to the target task; represents the unique identification ID of the equipment to which the activity process node belongs; represents the node identity identification: is the first party, such as the red side, is the second party, such as the blue side; represents the node type, that is ; represents the node functional attribute vector, which represents the various functional parameters of the node, such as a multi-dimensional vector, matrix, etc.

[0029] The functional attribute vectors of different types of nodes are different. For example, for a certain situation awareness node N S its functionality can be expressed as:

[0030]

[0031] Among them, represents the functional attribute value obtained by quantifying the functionality of a certain situation awareness node N S ; represents the maximum radius of the target task; represents the acquisition rate of important data (such as equipment deployment data required for the execution of the target task, target location data, etc.); represents the target recognition accuracy; represents the tracking accuracy, represents the update rate.

[0032] In addition, for the attribute vector, there is also an extended attribute vector, for example, it is represented by ;

[0033] For example, for various functional attributes of a certain aircraft node model (i.e., the situation awareness node model) (including multi-level attributes and vectors or numerical values after quantization representation), please refer to Table 1 for details.

[0034] Table 1

[0035] Table 1 is a diagram showing an example of the functional attributes of a certain aircraft node model.

[0036] Furthermore, the functional attributes of each node also include functional attributes such as different device types, the quantity of each device, the quantity and location of command centers, the location and quantity of information monitoring points, air tasks, sea tasks, ground tasks, etc. Each node also contains vectors or numerical values represented by quantization of each functional attribute.

[0037] It should be noted that the above is only an optional example for illustration and should not be construed as a limitation to the present invention.

[0038] Next, in step S102, according to the target activity process node model, multiple information links are determined, and an activity program chain representing activity effectiveness is formed based on the mapping and ordered combination from the target activity to the information links.

[0039] According to different emphasis functions in the activity process involved in the execution of the target task, such as executing confrontation information, monitoring changes in the deployment of participating personnel or equipment, and the withdrawal of a participating party, etc., the activity process nodes are classified and combined to form multiple types of information links.

[0040] Specifically, the activity process nodes are classified and combined to form the following information links to construct an information link model: situation awareness information link , auxiliary decision-making information link , action control information link , information service information link .

[0041] It should be noted that in this example, the above four types of information links are mutually exclusive, and the information links involved in the target task are ordered and combined to form multiple types of information links (such as situation chain, decision chain, execution chain).

[0042] The number of activity process nodes in each information link is two, and each information link includes one type of activity process node, two types of activity process nodes or more types of activity process nodes.

[0043] Specifically, for example, the number of active process nodes in the situation awareness information link is three. The situation awareness information link includes target parameters and status, and generates situation awareness information, which can be sent to all active process nodes. When communication is allowed, if the accuracy and latency of the information meet the decision-making requirements, the information can be directly provided to the relevant active process nodes. The information content of the auxiliary decision-making information link includes task planning and action execution instructions; the action control information link includes personnel command and equipment control information; the information service information link includes information that needs to be transmitted for data analysis. When direct communication between other active process nodes is not possible, the active process nodes in the information service information link can act as relay nodes to send information.

[0044] In a specific embodiment, the situation awareness information link includes at least one situation awareness node (such as the first situation awareness node), and this situation awareness node can directly share the situation information it contains with all active process nodes (specifically including situation awareness nodes different from the first situation awareness node, auxiliary decision-making nodes, action control nodes, and information service nodes).

[0045] Optionally, when communication between nodes is allowed, when the accuracy and latency of the situation awareness information meet the decision-making requirements of the current target task, the situation awareness information can be directly supplied to the auxiliary decision-making node, action control node, and information service node. For example, it can be denoted as , where is a node pair.

[0046] For example, the situation awareness information link is , where the situation information of the first situation awareness node can be directly shared with the intermediate node , or returned to the first situation awareness node after being processed by the intermediate node . For example, the situation awareness information link is , where the situation information of the first situation awareness node can be directly reported to the first auxiliary decision-making node , or reported to the first auxiliary decision-making node after being processed by other nodes . Specifically, please refer to Table 2 below. The above nodes are also simply referred to as nodes in Table 2.

[0047] For example, the number of activity process nodes of the auxiliary decision-making information link is three, specifically including at least one auxiliary decision-making node (such as the first auxiliary decision-making node). The information content of the auxiliary decision-making information link includes the task planning of the target task and the action execution instruction. Specifically, specific instructions such as adjustment instructions generated by the auxiliary decision-making node are sent to other nodes level by level. For example, the auxiliary decision-making information link is , and the adjustment instruction of the first auxiliary decision-making node is sent to the second auxiliary decision-making node , and further sent to the third auxiliary decision-making node . The level of the first auxiliary decision-making node > the level of the second auxiliary decision-making node > the level of the third auxiliary decision-making node. The auxiliary decision-making information link is denoted by, for example, , and specifically recorded as .

[0048] The information content of the action control information link includes personnel command, equipment control information, and information such as feedback control and task collaboration generated by the auxiliary decision-making node or the action control node. The above information content can be sent to the relevant action control nodes. In some cases, it can bypass other nodes , and the action control information link is denoted as .

[0049] The information content of the information service information link includes data analysis or information that other nodes need to transmit. Instructions are generated by the behavior control node. When other nodes cannot communicate directly, the information service node can be used as a relay node to send to the relevant situation awareness nodes, auxiliary decision-making nodes, behavior control nodes, and information service nodes. The information service information link is specifically recorded as .

[0050] Table 2

[0051] Table 2 shows examples of various types of information links.

[0052] Note: * indicates more than or equal to 0; + indicates more than or equal to 1.

[0053] It should be noted that the auxiliary decision-making node includes multiple levels of nodes. For example, information data is sent from the first auxiliary decision-making node of the command center to the second auxiliary decision-making node of the regional command post, and further sent to the third auxiliary decision-making node of the sub-regional command post.

[0054] Next, according to the formed information link, a situation chain, a decision chain, and an execution chain are further formed.

[0055] As the basic information flow in the activity process, each type of information link model can only reflect the specific functions and individual capabilities of the system, but cannot reflect the overall capabilities of the system or the system, nor can it independently support the completion of the target task or activity task. Taking the situation awareness information link model as an example, information such as the source, flow, and timing of can only reflect the situation awareness ability, and the communication network resource competition and mutual driving effects between information activities cannot be represented. Only using

[0056] cannot meet the task requirements. Based on the orderly combination of information links, the present invention constructs a combined information link flow model that can reflect the overall functions required for the target task, that is, the activity program chain model. Based on the OODA loop theory, according to observation and surveillance, situation judgment, auxiliary decision-making, and action control, corresponding activity program chain models are constructed according to different target tasks, specifically including: situation chain and so on.

[0057] The situation chain refers to starting from the situation awareness node and transmitting various data, voices, images, etc. related to the situation to the auxiliary decision-making node (such as various situation users such as commanders and executors). According to its node relationship, the combination method is defined as + and so on.

[0058] The decision chain refers to a link formed starting from the auxiliary decision-making node, ending at the friendly neighbor node or the subordinate node and the action control node, with the command information as the link bond, during the command and coordination process of each element of the node and the friendly neighbor node. According to its node relationship, the combination method is defined as + and + and so on.

[0059] The execution chain refers to an information link directly related to the execution task, starting from the situation awareness node and ending at the nodes corresponding to various executions. Compared with other links, the execution chain usually has the strongest timeliness. According to the data transmission relationship or transfer relationship between nodes (such as sending data or receiving data), the combination method is defined as +

[0060] Taking the satellite support for a certain ground operation task (i.e., the target task) as an example, based on this target task, the mapping and function combination from the target task (or activity task) to the information link are carried out to form an activity program chain. As shown in Table 3. ​​

[0061] Table 3

[0062] Table 3 shows an example table of information related to activities in the target task.

[0063] Specifically, sort out and decompose the target task or activity task, determine the corresponding link category, and extract the activity process nodes. According to the activity process nodes, determine the information link combination method (which needs to meet the limiting condition that the execution corresponding node or action control node is the end point), and then combine the requirements of the target task and the process description, select the activity process nodes in different information links for functional combination, so that multiple multi-category information links form an intricate tree-shaped network-like semi-closed network or closed network, and finally form an activity program chain corresponding to the target task.

[0064] According to the activity process node model, each information link, and the basic information such as the activity process name, identification, and target, construct an activity process model. Define the activity process model as a five-tuple:

[0065]

[0066] Among them, A represents the activity process model of the target task, and specifically adopts the representation method of a five-tuple; is the activity process name, which identifies the name of the specific activity process and is used to identify and distinguish different activity processes; is the activity process identification, the number that uniquely identifies each activity process, and is used to ensure the uniqueness of each activity process in the system or system (for example, " = 001" means that this is the only activity process numbered 001 in the system); is the activity process target, the goal or result that the activity process is expected to achieve, which helps to formulate a detailed action plan and evaluate the effect of the activity process; is the set of activity process nodes, which refers to the set of nodes that execute or participate in the activity process. The nodes are, for example, various types of units (enterprises or organizations), devices, or personnel, that is, situation awareness nodes and auxiliary decision-making nodes and action control nodes and information service nodes ; is the information link model combination, which describes the relationship and interaction between the nodes in the activity process, that is, the activity program chain model.

[0067] It should be noted that through the definition of the five-tuple, the current activities in the target task can be represented more clearly and intuitively, which is also convenient for users to evaluate the current activities and determine whether an activity meets the expectations, that is, to consider whether the relationship between the activity goal and the activity process nodes and the link model matches. The above is only an optional example for illustration and should not be construed as a limitation to the present invention.

[0068] Next, in step S103, based on the constructed target activity process node model and multi-information links, a system network activity model is constructed. Based on the OODA loop theory, the activity processes in the historical task data are abstracted into four typical activity processes, namely observation and monitoring, situation assessment, decision assistance, and collaborative action.

[0069] Taking the task of satellite supporting a certain ground operation as an example, the process of constructing an activity process model corresponding to each target task is described. Among them, it includes multiple participants and adversarial training between the participants.

[0070] The target task is divided into four types of activities: observation and monitoring, situation assessment, decision assistance, and collaborative action. Among the observation and monitoring activities, there is an activity of "collecting the latest intelligence", and its structured description is as follows.

[0071] First, observe and monitor the activity processes corresponding to each target task. Collect the latest intelligence information and express it in the following way: = "Collect the latest intelligence", indicating that the name of the activity process of the target task is "Collect the latest intelligence"; = 001, this number uniquely identifies this activity process and ensures no overlap in the system or system; "Continuously obtain the latest intelligence information on the personnel equipment deployment, equipment status, command system, and changes in confrontation strategies of the blue side, so as to be able to adjust in real time during the confrontation training process"; , They are 2 satellites and 2 UAVs in sequence, [[ID=2s]] is the regional command post, is the command center, is information monitoring point 1; , due to the large number and complexity of the specific transmission link relationships, limited by space, it is simplified and described with three types of nodes in the situation chain .

[0072] Then, the activity process of situation assessment is described.

[0073] For the activity process of situation assessment, it is expressed in the following way: = "Discriminate target attributes", indicating that the name of this activity process is "Discriminate target attributes"; =002, this number uniquely identifies this activity process to ensure no overlap in the system or system; "Identify and monitor the types, characteristics, and their countermeasure training values of the important targets of the opposing party, including air and ground air defense forces, command and control nodes, radar stations, communication nodes, etc."; , In sequence are 2 satellites and 2 UAVs, is the regional command post, is the intelligence station 1; , due to the numerous and complex specific transmission link relationships, it is simplified and described by the three types of nodes of the situation chain.

[0074] For the auxiliary decision-making activity process, the following expression is used: = "Formulate an action plan", indicating that the name of this activity process is "Formulate an action plan"; =003, this number uniquely identifies this activity process to ensure no overlap in the system or system; "Develop a detailed combat plan, including the primary and secondary confrontation directions, feint directions, optimal confrontation timing, and confrontation methods, providing clear action instructions for air confrontation and air confrontation"; , is the regional command post, is the command center, In sequence are information monitoring point 1, information monitoring point 2, and information monitoring point 3, is the confrontation node; , due to the numerous and complex specific transmission link relationships, it is simplified and described by the three types of nodes of the decision-making chain.

[0075] For the collaborative action activity process, the following expression is used: = "Continuously suppress the opposing party's targets", which indicates that the name of this activity process is "Continuously suppress the opposing party's targets"; =004, this number uniquely identifies this activity process to ensure no overlap in the system or system. "Continuously suppress the important air defense and command and control nodes of the opposing party with firepower, weaken its defense ability and command and control ability, create penetration conditions for our own side, and the suppression efficiency is not less than 90%"; , is the early warning aircraft, is the command center, is the information monitoring point 1, are electronic jamming equipment 1 and electronic jamming equipment 2; , due to the numerous and complex specific transmission link relationships, it is simplified and described by the A simplified description is given for three types of nodes.

[0076] Based on the target activity process node model constructed in step S1101 and the multi-information links (including activity program chains, etc.) formed in step S102, a more effective system network activity model can be constructed. Through the above modeling process, the decomposition from tasks to activities is realized, and a scientific, intuitive, and quantitative description of the system network activities is carried out, enabling the tasks and system network activities to be presented more intuitively, and providing a more effective data basis for users to carry out subsequent performance evaluation, analysis, and optimization of various indicators or data.

[0077] It should be noted that the above is only for illustrative purposes as an optional example and should not be construed as a limitation to the present invention.

[0078] Next, in step S104, the fuzzy comprehensive evaluation method is used to evaluate the performance of the constructed system network activity model to determine whether the task activities in the target task meet the task requirements. Specifically, it includes: based on the indicators to be evaluated, an evaluation matrix is established, and the weight of each indicator to be evaluated in the system to be evaluated is calculated and determined; using the calculated and determined weights and the single-factor evaluation matrix, a fuzzy synthesis operation is carried out to obtain a comprehensive evaluation result.

[0079] The fuzzy comprehensive evaluation method is used to evaluate the performance of the constructed system network activity model to optimize the system network activity model.

[0080] Specifically, first calculate and determine the weight of each indicator to be evaluated in the system to be evaluated to form a corresponding evaluation matrix, and perform consistency calculation on each indicator to be evaluated to evaluate the performance of each target task; then carry out fuzzy comprehensive evaluation to obtain a fuzzy comprehensive evaluation result, and a histogram will be drawn to determine the indicators to be optimized in the system to be evaluated, so as to further optimize the system network activity model.

[0081] It should be noted that since the system network activities are often restricted by many fuzzy factors, and the fuzzy comprehensive evaluation method can highly adapt to the complexity and variability of the environment, and can effectively integrate the fuzzy information in the system network activities to ensure the effectiveness and scientificity of the evaluation results. Therefore, the present invention uses the fuzzy comprehensive evaluation method to evaluate the activity performance of the system network activity model.

[0082] When the target task is a task to be predicted, specifically, the task activities of the task to be predicted are sorted out and decomposed, the corresponding information link categories are determined, and the activity process nodes are determined from the task activities according to the method in step S101. Then, according to the activity process nodes, the combination method of the information links is determined, and the activity process nodes in the information links are functionally combined to form an activity program chain. Thus, the mapping process from the task to be predicted to the node information chain is completed.

[0083] Next, perform an effectiveness evaluation on the prediction task.

[0084] Specifically, as Figure 3 shown, the effectiveness evaluation specifically includes the following steps.

[0085] Step S201: Determine the evaluation object and the overall evaluation goal of the target task.

[0086] Take the activity process measurement object as the activity process effectiveness, and determine the overall evaluation goal according to the selected evaluation object. The overall evaluation goal is derived from the target task or the activity process goal, such as the four types of target tasks corresponding to observation and surveillance, situation judgment, auxiliary decision-making, and coordinated action. Specifically, perform an effectiveness evaluation on the evaluation indicators or evaluation elements corresponding to these four types of target tasks. Specifically, refer to Figure 2 the quantification evaluation of each element in the evaluation element layer. Specifically, at least three evaluation elements are quantitatively evaluated to determine the effectiveness of the four types of target tasks.

[0087] In Figure 2 the example, the evaluation object layer specifically includes the effectiveness of the four types of target tasks corresponding to observation and surveillance, situation judgment, auxiliary decision-making, and coordinated action, such as the effectiveness of observation and monitoring activities, the effectiveness of situation judgment activities, the effectiveness of auxiliary decision-making activities, and the effectiveness of coordinated action activities. The evaluation element layer includes the target arrival rate, the target action efficiency, the observation coverage rate, the target discovery rate, the observation accuracy, the observation timeliness, the situation data acquisition rate, the situation judgment accuracy rate, the situation judgment timeliness, the information reception rate, the information processing efficiency, the decision-making accuracy rate, the decision-making timeliness, the coordinated action accuracy rate, and so on. The evaluation data layer specifically includes the number of target arrivals, the target time used, the area of the region, the number of discovered targets, the number of correctly identified targets, the time used to identify targets, the number of acquired situation data, the number of correct situation judgments, the time used for situation judgment, the time used for information processing, the time used for correct decision-making, the number of correct coordinated executions, the time used for coordinated action, and so on.

[0088] Step S202: Determine the system to be evaluated corresponding to the target task.

[0089] Specifically, according to the characteristics of the confrontation task, construct a system to be evaluated including on-site reconnaissance and surveillance, confrontation situation judgment, confrontation command and decision-making, and coordinated confrontation action to form the system to be evaluated corresponding to the target task (in this example, it is a simulation evaluation index system. Specifically, refer to Figure 2 ) Step S203: Determine the evaluation indicators to be evaluated.

[0090] Based on the system to be evaluated, form an evaluation element set , an evaluation set , specifically {excellent, good, medium, poor, extremely poor}.

[0091] Specifically, at least three evaluation elements involved in each target task of the system to be evaluated are used as the evaluation indicators to form an evaluation element set and an evaluation set.

[0092] Step S204: Establish an evaluation matrix according to the determined evaluation indicators.

[0093] For each evaluation indicator (for example, represented by ), make the corresponding evaluation result , and the corresponding membership degree is , which can be directly calculated according to the expert scoring table to form an evaluation matrix , where .

[0094] Step S205: Determine the weight of each evaluation indicator in the system to be evaluated.

[0095] Specifically, the analytic hierarchy process is adopted to judge the rationality of each evaluation matrix and the consistency test of the hierarchical ranking. The analytic hierarchy process is used to determine the weight of each evaluation indicator in the system to be evaluated. The 1-9 scale method in Table 4 is applied to make pairwise comparisons of the evaluation indicators, construct an evaluation matrix, and find the eigenvector corresponding to the largest eigenvalue of the evaluation matrix, which is the weight vector. For example, it is . For the evaluation matrix, select the evaluation elements corresponding to the target task to form an evaluation matrix (for example, the evaluation matrix of the observation and surveillance activity effectiveness in Table 5).

[0096] Table 4

[0097] Table 4 shows an example diagram of the "1-9" scale method.

[0098] Table 5

[0099] Table 5 shows an example schematic table of the evaluation matrix and weight of the observation and surveillance activity effectiveness.

[0100] Adopt the following expression to calculate the consistency index of each evaluation matrix corresponding to the evaluation indicators of different target tasks for consistency test:

[0101] Among them, represents the consistency index of the current evaluation matrix P; is the number of evaluation factors at the same level. Different target tasks correspond to different evaluation layers and different numbers of evaluation factors. n is a positive integer; is the largest eigenvalue of the current evaluation matrix.

[0102] When conducting consistency verification, first, the evaluation elements need to be multiplied row by row and then take the nth root to obtain After normalization processing, is obtained. The maximum eigenvalue of the current evaluation matrix is calculated using the following expression to :

[0103]

[0104]

[0105] Among them, represents the value obtained by multiplying the evaluation elements row by row and then taking the nth root; represents the weight value obtained by normalizing the ith root value; is the maximum eigenvalue of the current evaluation matrix R, where the current evaluation matrix R includes matrix terms formed by quantifying multiple evaluation elements, that is, evaluation elements, represents the evaluation element, that is, the matrix term, in the ith row and jth column of the current evaluation matrix R. i represents the ith row in the current evaluation matrix R, and j represents the jth column in the current evaluation matrix R. Both i and j are positive integers, specifically 1, 2,..., n; The kth root value; k represents the number of root values The quantity of k is a positive integer, specifically 1, 2,..., n; is the product of the current evaluation matrix R and the weight vector W, represents the ith evaluation element after the product, is composed of A vector.

[0106] Next, the following expression is used to calculate the consistency ratio to verify the consistency of each evaluation matrix:

[0107] Among them, Characterizes the consistency index of each evaluation matrix, including the current evaluation matrix; represents the average value of the consistency indices of the judgment matrices generated according to different target tasks, evaluation indicators, the number of evaluation factors, and matrix orders within a specified historical time period. Specifically, refer to Table 6 for parameters.

[0108] The specified historical time includes three months, six months, one year, two years, three years, etc. calculated backward from the current time.

[0109] When , it indicates the current evaluation matrix The degree of consistency is relatively satisfactory, and the weight vector calculation can be carried out using the eigenvector of the current evaluation matrix ; if , then the current evaluation matrix should be adjusted until the current evaluation matrix meets the consistency .

[0110] Table 6

[0111] Table 6 shows the value table of the consistency index RI Furthermore, using the weight vector and the evaluation matrix of single evaluation elements, the comprehensive evaluation result is obtained through fuzzy composition operations (such as weighted average method, main factor determination type, main factor prominence type, etc.) , where represents the fuzzy composition operator. In this example, the weighted average method is used.

[0112] Next, the element quantization processing of the index to be evaluated is carried out. According to the weighted average method, the following expression is used to calculate the evaluation representation value of the index to be evaluated reflected in the activity task to evaluate the situation of the comprehensive evaluation result:

[0113] where represents the evaluation representation value of the index to be evaluated reflected in the activity task; is the i-th evaluation element (or matrix item) in the comprehensive evaluation matrix, and i is a positive integer; is the quantization result of the scoring level obtained by evaluating or processing each index to be evaluated: = [0.9, 0.7, 0.5, 0.3, 0.1], is a undetermined coefficient, specifically in the range of 0.8 to 3.0, and the purpose is to control the role of the larger in the activity task.

[0114] Specifically, = [0.9 (excellent) 0.7 (good) 0.5 (average) 0.3 (poor) 0.1 (very poor)]. Preferably, the undetermined coefficient = 1, or the undetermined coefficient = 2, which can effectively control the role of the larger in the activity task.

[0115] Next, draw a histogram based on the finally obtained fuzzy comprehensive evaluation results to visually identify the evaluation indicators with relatively weak effectiveness, which is used to optimize the system network activity model in the next round, and continuously carry out the process of optimizing the system network activity model for multiple rounds until all the evaluation indicators in the fuzzy comprehensive evaluation results meet the consistency requirements.

[0116] Specifically, the set threshold S determined according to the nature of the activity task (such as the venue involved in the task, the risk of the task, etc.) is in the range of 60 to 80. Preferably, the set threshold S is 70.

[0117] When the calculated evaluation representation value is less than or equal to the set threshold, it indicates that the current evaluation indicator of the current activity in the target task does not meet the task requirements.

[0118] When the calculated evaluation representation value is greater than the set threshold, it indicates that the current evaluation indicator of the current activity in the target task meets the task requirements.

[0119] Further, for each evaluation indicator that does not meet the task requirements, find the relevant attributes of the corresponding nodes in the system network activity model, adjust the attribute values corresponding to each evaluation indicator, and re-evaluate the system network activity model until all the evaluation indicators are greater than the corresponding set thresholds, so that all the evaluation indicators involved in the activity in the target task meet the task requirements.

[0120] By using the fuzzy comprehensive evaluation method model to evaluate the effectiveness of each evaluation indicator involved in the task activity in the target task, effectively find the evaluation indicators that do not meet the task requirements in the system network activity model and the relevant attributes of the corresponding nodes, adjust the attribute values corresponding to each evaluation indicator according to the effectiveness evaluation results, and re-evaluate the system network activity model until all the evaluation indicators are greater than the corresponding set thresholds, so that all the evaluation indicators involved in the activity in the target task meet the task requirements, in order to optimize the system network activity model, and can more effectively realize the optimization of the system network activity model while constructing the system network activity model.

[0121] It should be noted that the above is only an optional example for illustration and should not be construed as a limitation to the present invention.

[0122] Compared with the prior art, the present invention specifically represents the activity elements involved in the target task in a concrete form by constructing an activity process node model and each information link model, and integrates, refines, and reorganizes information nodes (i.e., activity process nodes) and information links based on the observation, judgment, decision-making, and action (OODA) loop process to form a system network activity model, thereby realizing the effective integration and coordination of information data in the face of a complex multi-dimensional confrontation environment. Based on the simulation evaluation index system of activity effectiveness, it can accurately reflect the effects of each link of OODA. Specifically, the fuzzy comprehensive evaluation method model is used to evaluate the effectiveness of each evaluation index involved in the task activities in the target task, effectively find the evaluation indexes that do not meet the task requirements and the relevant attributes of the corresponding nodes in the system network activity model, adjust the attribute values corresponding to each evaluation index according to the effectiveness evaluation results, and re-evaluate the system network activity model until all evaluation indexes are greater than the corresponding set thresholds, so that all evaluation indexes involved in the activities in the target task meet the task requirements, optimize the system network activity model, and can more effectively realize optimizing the system network activity model while constructing the system network activity model.

[0123] Embodiment 2 The following is a system embodiment of the present invention, which can be used to execute the method embodiment of the present invention. For the details not disclosed in the system embodiment of the present invention, please refer to the method embodiment of the present invention.

[0124] Figure 4 It is a schematic structural diagram of an example of a system for constructing and optimizing a system network activity model according to the present invention. The following will refer to Figure 4 to describe the system for constructing and optimizing a system network activity model. The system for constructing and optimizing a system network activity model executes the method for constructing and optimizing a system network activity model described in Embodiment 1 of the present invention.

[0125] As Figure 4 shown, the system 400 for constructing and optimizing a system network activity model includes a first construction module 410, a first determination module 420, a second construction module 430, and an evaluation and optimization module 440.

[0126] In a specific embodiment, the first construction module 410 extracts various nodes of the target task based on the functional dimension to construct respective target activity process node models, specifically including abstracting the activity process nodes of the target task into the following nodes according to the OODA loop theory: a situation awareness node, an auxiliary decision-making node, an action control node, and an information service node. The first determination module 420 determines a plurality of information links according to the target activity process node model, and forms an activity program chain representing the activity efficiency according to the mapping and ordered combination from the target activity to the information links. The second construction module 430 constructs a system network activity model based on the constructed target activity process node model and multiple information links. The evaluation and optimization module 440 is used to evaluate the efficiency of the constructed system network activity model by using the fuzzy comprehensive evaluation method, and determine whether the task activities in the target task meet the task requirements, specifically including: establishing an evaluation matrix based on the indexes to be evaluated, and calculating and determining the weight of each index to be evaluated in the system to be evaluated; using the calculated weight and the single-factor evaluation matrix to perform a fuzzy synthesis operation to obtain a comprehensive evaluation result.

[0127] According to an alternative embodiment, a plurality of information links are determined according to the target activity process node model, and an activity program chain representing the activity efficiency is formed according to the mapping and ordered combination from the target activity to the information links, including: Classify and combine the activity process nodes to form the following information links to construct an information link model: a situation awareness information link, an auxiliary decision-making information link, an action control information link, and an information service information link; the situation awareness information link includes at least three activity process nodes, and the situation awareness information link includes target parameters and status, and can generate situation awareness information and send it to all activity process nodes.

[0128] The information content of the auxiliary decision-making information link includes task planning and action execution instructions; the action control information link includes personnel command and equipment control information; the information service information link includes information that needs to be transmitted for data analysis, and when other activity process nodes cannot communicate directly, the activity process nodes in the information service information link can be used as relay nodes to send information.

[0129] According to the formed information links, a situation chain, a decision chain, and an execution chain are further formed.

[0130] According to an alternative embodiment, an activity process model is constructed according to the activity process node model, the information link model, the activity process name, the identifier, and the target, and the activity process model is defined as a five-tuple; According to the activity process nodes, the information link combination mode is determined according to the limiting condition that the corresponding node or the action control node that satisfies the execution is used as the end point.

[0131] Select active process nodes in different information links for function combination, so that multiple types of information links form an intricate tree-shaped network-like semi-closed network or closed network, and finally form an activity program chain corresponding to the target task.

[0132] According to an alternative implementation, the effectiveness of the constructed system network activity model is evaluated by using the fuzzy comprehensive evaluation method, including: calculating and determining the weight of each index to be evaluated in the system to be evaluated to form a corresponding evaluation matrix, and performing consistency calculation on each index to be evaluated to evaluate the effectiveness of the activity; performing fuzzy comprehensive evaluation to obtain a fuzzy comprehensive evaluation result, and drawing a histogram to visually determine the index to be optimized for the next round of optimization of the system network activity model, and continuously performing the process of optimizing the system network activity model for multiple rounds until the task requirements are met.

[0133] According to an alternative implementation, according to the weighted average method, the following expression is used to calculate the evaluation representation value of the index to be evaluated reflected in the activity task to evaluate the situation of the comprehensive evaluation result:

[0134] where, represents the evaluation representation value of the index to be evaluated reflected in the activity task; is the i-th evaluation element (or matrix item) in the comprehensive evaluation matrix, and i is a positive integer; is the quantization result of the scoring level obtained by evaluating or processing each index to be evaluated: = [0.9, 0.7, 0.5, 0.3, 0.1], is a undetermined coefficient, specifically in the range of 0.8 to 3.0, and the purpose is to control the role of the larger in the activity task.

[0135] According to an alternative implementation, the set threshold S determined according to the nature of the activity task is in the range of 60 to 80.

[0136] When the calculated evaluation representation value is less than or equal to the set threshold, it indicates that the current evaluation index of the current activity in the target task does not meet the task requirements.

[0137] When the calculated evaluation representation value is greater than the set threshold, it indicates that the current evaluation index of the current activity in the target task meets the task requirements.

[0138] Further, for each evaluation index that fails to meet the task requirements, find the relevant attributes of the corresponding nodes in the system network activity model respectively, adjust the attribute values corresponding to each evaluation index, and re-evaluate the system network activity model until all evaluation indexes are greater than the corresponding set thresholds, so that all evaluation indexes involved in the activities in the target task meet the task requirements.

[0139] According to the optional implementation manner, the following expression is used to calculate the consistency index of each evaluation matrix corresponding to the evaluation indexes to be evaluated for different target tasks, so as to perform consistency test:

[0140] Wherein, characterizes the consistency index of the current evaluation matrix P; is the number of evaluation factors at the same level. Different target tasks correspond to different evaluation layers and different numbers of evaluation factors. n is a positive integer; is the maximum eigenvalue of the current evaluation matrix.

[0141] According to the optional implementation manner, when performing the consistency test, first, the evaluation elements need to be multiplied by rows and then take the nth root. After normalization processing, is obtained. The following expression is used to calculate to determine the maximum eigenvalue of the current evaluation matrix :

[0142]

[0143]

[0144] Wherein, means multiplying the evaluation elements by rows and then taking the nth root to obtain the root value; means the weight value obtained by normalizing the i-th root value; is the maximum eigenvalue of the current evaluation matrix R, where the current evaluation matrix R includes matrix terms formed by quantifying multiple evaluation elements, that is, evaluation elements, represents the evaluation element, that is, the matrix term, in the i-th row and j-th column of the current evaluation matrix R. i represents the i-th row in the current evaluation matrix R, and j represents the j-th column in the current evaluation matrix R. Both i and j are positive integers, specifically 1, 2,..., n; represents the k-th root vector; k represents the number of root values k is a positive integer, specifically 1, 2,..., n; is the product of the current evaluation matrix R and the weight vector W, represents the i-th evaluation element after the product, is composed of vectors

[0145] Calculate the consistency ratio , to test the consistency of each evaluation matrix:

[0146] wherein characterizes the consistency index of each evaluation matrix, including the current evaluation matrix; represents the average value of the consistency indexes of the judgment matrices generated according to different target tasks, evaluation indexes to be evaluated, the number of evaluation factors, and the matrix order within the specified historical time period.

[0147] It should be noted that since Figure 4 the system network activity model construction and optimization method executed by the system network activity model construction and optimization system of Figure 1 is substantially the same as the system network activity model construction and optimization method in the example of

[0148] Compared with the prior art, the present invention specifically represents the activity elements involved in the target task by constructing an activity process node model and each information link model, and based on the observation, judgment, decision-making, and action (OODA) loop process, integrates, refines, and reorganizes the information nodes (i.e., activity process nodes) and information links to form a system network activity model, thereby realizing the effective integration and coordination of information data in the complex multi-dimensional confrontation environment, and based on the simulation evaluation index system of activity effectiveness, can accurately reflect the effects of each link of OODA. Specifically, the fuzzy comprehensive evaluation method model is used to evaluate the effectiveness of each evaluation index involved in the task activities in the target task, effectively find the evaluation indexes that do not meet the task requirements in the system network activity model and the relevant attributes of the corresponding nodes, adjust the attribute values corresponding to each evaluation index according to the effectiveness evaluation results, and re-evaluate the system network activity model until all evaluation indexes are greater than the corresponding set thresholds, so that all evaluation indexes involved in the activities in the target task meet the task requirements, to optimize the system network activity model, and can more effectively realize the optimization of the system network activity model while constructing the system network activity model.

[0149] Figure 5 is a schematic structural diagram of an electronic device according to an embodiment of the present invention.

[0150] such as Figure 5As shown, the electronic device is presented in the form of a general-purpose computing device. The processor can be one or multiple and work collaboratively. The present invention does not exclude distributed processing, that is, the processors can be dispersed in different physical devices. The electronic device of the present invention is not limited to a single entity and can also be the sum of multiple physical devices.

[0151] The memory stores computer-executable programs, usually machine-readable code. The computer-readable program can be executed by the processor so that the electronic device can execute the method of the present invention or at least some of the steps in the method.

[0152] The memory includes volatile memory, such as a random access storage unit (RAM) and / or a cache storage unit, and can also be non-volatile memory, such as a read-only storage unit (ROM).

[0153] Optionally, in this embodiment, the electronic device further includes an I / O interface for data exchange between the electronic device and external devices. The I / O interface can represent one or more of several bus structures, including a memory unit bus or a memory unit controller, a peripheral bus, a graphics acceleration port, a processing unit, or a local bus using any of the multiple bus structures.

[0154] It should be understood that Figure 5 The electronic device shown is only an example of the present invention, and the electronic device of the present invention may also include elements or components not shown in the above example. For example, some electronic devices also include a display unit such as a display screen, and some electronic devices also include human-computer interaction elements, such as buttons, keyboards, etc. As long as the electronic device can execute the computer-readable program in the memory to implement the method of the present invention or at least some of the steps of the method, it can be considered as the electronic device covered by the present invention.

[0155] Through the description of the above embodiments, those skilled in the art can easily understand that the example embodiments described here can be implemented by software or by a combination of software and necessary hardware. Therefore, as Figure 6 shown, the technical solution according to the embodiment of the present invention can be embodied in the form of a software product, which can be stored in a non-volatile storage medium (which can be a CD-ROM, a USB flash drive, a mobile hard disk, etc.) or on a network, including several commands to enable a computing device (which can be a personal computer, a server, or a network device, etc.) to execute the above method according to the embodiment of the present invention.

[0156] The software product may employ any combination of one or more readable media. The readable media may be a readable signal medium or a readable storage medium. The readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the foregoing. More specific examples (a non-exhaustive list) of the readable storage medium include: an electrical connection having one or more wires, a portable disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0157] The computer-readable storage medium may include a data signal propagated in a baseband or as part of a carrier wave, in which the readable program code is carried. Such a propagated data signal may take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the foregoing. The readable storage medium may also be any readable medium other than the readable storage medium, which can send, propagate, or transmit a program for use by or in connection with a command execution system, apparatus, or device. The program code contained on the readable storage medium may be transmitted using any appropriate medium, including but not limited to wireless, wired, optical fiber cable, RF, etc., or any suitable combination of the foregoing.

[0158] The program code for performing the operations of the present invention may be written in any combination of one or more programming languages, including object-oriented programming languages such as Java, C++, etc., and also including conventional procedural programming languages such as the "C" language or similar programming languages. The program code may be executed entirely on the user's computing device, partially on the user's device, executed as a stand-alone software package, partially on the user's computing device and partially on a remote computing device, or entirely on a remote computing device or server. In the case of a remote computing device, the remote computing device may be connected to the user's computing device through any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computing device (e.g., through the Internet using an Internet service provider).

[0159] The above computer-readable medium carries one or more programs, which when executed by a device, cause the computer-readable medium to implement the data interaction method of the present disclosure.

[0160] Those skilled in the art can understand that the above-mentioned modules can be distributed in the device according to the description of the embodiments, or can be correspondingly changed and distributed in one or more devices that are only different from this embodiment. The modules of the above embodiments can be combined into one module, or can be further split into multiple sub-modules.

[0161] Through the description of the above embodiments, those skilled in the art can easily understand that the exemplary embodiments described herein can be implemented by software, or can be implemented by the way of software combined with necessary hardware. Therefore, the technical solution according to the embodiment of the present invention can be embodied in the form of a software product, which can be stored in a non-volatile storage medium (which can be a CD-ROM, a USB flash drive, a mobile hard disk, etc.) or on the network, including several commands to enable a computing device (which can be a personal computer, a server, a mobile terminal, or a network device, etc.) to execute the method according to the embodiment of the present invention.

[0162] It should be noted that the above detailed description is exemplary and is intended to provide further illustration of the present application. Unless otherwise specified, all technical and scientific terms used herein have the same meaning as commonly understood by those of ordinary skill in the technical field to which the present application belongs.

[0163] In the above detailed description, reference has been made to the accompanying drawings, which form a part hereof. In the drawings, like symbols typically identify like components, unless the context indicates otherwise. The illustrated embodiments described in the detailed description, the drawings, and the claims are not meant to be limiting. Other embodiments may be used and other changes may be made without departing from the spirit or scope of the subject matter presented herein.

[0164] The above are only the preferred embodiments of the present invention and are not intended to limit the present invention. For those skilled in the art, the present invention can have various changes and modifications. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. An optimization method for constructing a system network activity model, characterized in that The method for constructing and optimizing the system network activity model includes: Extracting various nodes of the target task based on the functional dimension to construct the respective target activity process node models, specifically including abstracting the activity process nodes of the target task into the following nodes according to the OODA loop theory: situation awareness node, auxiliary decision-making node, action control node, and information service node; Determining multiple information links according to the target activity process node model, and forming an activity program chain representing activity effectiveness according to the mapping and ordered combination from the target activity to the information links; Constructing a system network activity model based on the constructed target activity process node model and multiple information links; Using the fuzzy comprehensive evaluation method to evaluate the effectiveness of the constructed system network activity model, and judging whether the task activities in the target task meet the task requirements, specifically including: establishing an evaluation matrix based on the to-be-evaluated indicators, and calculating and determining the weight of each to-be-evaluated indicator in the to-be-evaluated system; using the calculated weight and the single-factor evaluation matrix to perform fuzzy synthesis operations to obtain a comprehensive evaluation result.

2. The optimization method for constructing a system network activity model according to claim 1, wherein The step of determining multiple information links according to the target activity process node model, and forming an activity program chain representing activity effectiveness according to the mapping and ordered combination from the target activity to the information links includes: Classifying and combining the activity process nodes to form the following information links to construct an information link model: situation awareness information link, auxiliary decision-making information link, action control information link, and information service information link; the situation awareness information link includes at least three activity process nodes, and the situation awareness information link includes target parameters and status, and can generate situation awareness information and send it to all activity process nodes; The information content of the auxiliary decision-making information link includes task planning and action execution instructions; the action control information link includes personnel command and equipment control information; the information service information link includes information that needs to be transmitted for data analysis, and when other activity process nodes cannot communicate directly, the activity process nodes in the information service information link can act as relay nodes to send information; Further forming a situation chain, a decision-making chain, and an execution chain according to the formed information links.

3. The optimization method for constructing the system network activity model according to claim 2, characterized in that, Including: Constructing an activity process model according to the activity process node model, the information link model, the activity process name, the identifier, and the target, and defining the activity process model as a five-tuple; Determining the information link combination method according to the activity process nodes according to the limited condition that the corresponding node or action control node that satisfies the execution is the end point; Selecting the activity process nodes in different information links for functional combination, so that multiple multi-type information links form a complex tree-shaped network-like semi-closed network or closed network, and finally form an activity program chain corresponding to the target task.

4. The optimization method for constructing a system network activity model according to claim 1, characterized in that The step of using the fuzzy comprehensive evaluation method to evaluate the effectiveness of the constructed system network activity model includes: Calculating and determining the weight of each to-be-evaluated indicator in the to-be-evaluated system to form a corresponding evaluation matrix, and performing consistency calculation on each to-be-evaluated indicator to evaluate the effectiveness of the activity; Perform fuzzy comprehensive evaluation to obtain the fuzzy comprehensive evaluation result, and draw a histogram to visually judge the evaluation indicators to be optimized for optimizing the system network activity model in the next round. Continuously perform the process of optimizing the system network activity model for multiple rounds until the task requirements are met.

5. The optimization method for constructing a system network activity model according to claim 4, wherein Including: According to the weighted average method, use the following expression to calculate the evaluation representation value of the evaluation indicator reflected in the activity task to evaluate the situation of the comprehensive evaluation result: ； Among them, represents the evaluation representation value of the index to be evaluated reflected in the activity task; is the i-th evaluation element in the comprehensive evaluation matrix, where i is a positive integer; is the quantitative result of the scoring level obtained by evaluating or processing each index to be evaluated: = [0.9, 0.7, 0.5, 0.3, 0.1], is a coefficient to be determined, specifically in the range of 0.8 to 3.0, aiming to control the relatively large role played in the activity task.

6. The optimization method for constructing a system network activity model according to claim 5, characterized in that Including: The set threshold S determined according to the nature of the activity task is in the range of 60-80; When the calculated evaluation characterization value is less than or equal to the set threshold value, it indicates that the current evaluation index of the current activity in the target task does not meet the task requirements; When the calculated evaluation characterization value is greater than the set threshold, it indicates that the current evaluation index of the current activity in the target task meets the task requirements; Further, for each evaluation indicator that does not meet the task requirements, find the relevant attributes of the corresponding nodes in the system network activity model, adjust the attribute values corresponding to each evaluation indicator, and re-evaluate the system network activity model until all evaluation indicators are greater than the corresponding set threshold, so that all evaluation indicators involved in the activities in the target task meet the task requirements.

7. The optimization method for constructing a system network activity model according to claim 4, characterized in that Further including: Use the following expression to calculate the consistency index of each evaluation matrix corresponding to the evaluation indicators of different target tasks for consistency test: ； Among them, represents the consistency index of the current evaluation matrix P; is the number of evaluation factors at the same level. Different target tasks correspond to different evaluation layers and different numbers of evaluation factors. n is a positive integer; is the maximum eigenvalue of the current evaluation matrix.

8. The optimization method for constructing a system network activity model according to claim 7, characterized in that Including: When performing consistency check, it is necessary to first calculate the product of evaluation factors row by row, and then take the nth root to obtain after normalization to get , which is calculated using the following expression to determine the maximum eigenvalue of the current evaluation matrix : ； ； ； Among them, represents the root value obtained by taking the product of the evaluation elements row by row and then taking the nth root; represents the weight value obtained by normalizing the ith root value; is the maximum eigenvalue of the current evaluation matrix R, where the current evaluation matrix R includes the matrix terms formed after quantization of multiple evaluation elements, that is, the evaluation elements, represents the evaluation element, that is, the matrix term, in the ith row and jth column of the current evaluation matrix R. i represents the ith row in the current evaluation matrix R, and j represents the jth column in the current evaluation matrix R. Both i and j are positive integers, specifically 1, 2,..., n; represents the kth root value; k represents the number of root values, and k is a positive integer, specifically 1, 2,..., n; is the product of the current evaluation matrix R and the weight vector W, represents the ith evaluation element after the product, is composed of a vector; Calculate the consistency ratio , to test the consistency of each evaluation matrix: ； Among them, characterizes the consistency index of each evaluation matrix, including the current evaluation matrix; represents the average value of the consistency indices of the judgment matrices generated according to different target tasks, indices to be evaluated, the number of evaluation factors, and the matrix order within a specified historical time period.

9. An optimization system for constructing a system network activity model, characterized in that, It executes the system network activity model construction and optimization method described in any one of claims 1 to 8. The system network activity model construction and optimization system includes: The first construction module extracts various nodes of the target task based on the function dimension to construct their respective target activity process node models. Specifically, based on the OODA loop theory, the activity process nodes of the target task are functionally abstracted into the following nodes: situation awareness node, auxiliary decision-making node, action control node, information service node; The first determination module determines multiple information links according to the target activity process node model, and forms an activity program chain representing activity effectiveness according to the mapping and ordered combination from the target activity to the information link; The second construction module constructs a system network activity model based on the constructed target activity process node model and multiple information links; The evaluation and optimization module is used to evaluate the effectiveness of the constructed system network activity model by using the fuzzy comprehensive evaluation method to judge whether the task activities in the target task meet the task requirements. Specifically, including: based on the evaluation indicators, establish an evaluation matrix, and calculate and determine the weight of each evaluation indicator in the evaluation system; use the calculated and determined weight and the single-factor evaluation matrix to perform fuzzy synthesis operation to obtain the comprehensive evaluation result.

10. The optimization system for constructing a system network activity model according to claim 9, characterized in that Including: Classify and combine the activity process nodes to form the following information links: situation awareness information link, auxiliary decision-making information link, action control information link, information service information link; the situation awareness information link contains at least three activity process nodes, and the situation awareness information link contains target parameters and status, and can generate situation awareness information and send it to all activity process nodes; The information content of the auxiliary decision-making information link includes mission planning and action execution instructions; the action control information link includes personnel command and equipment control information; the information service information link includes the information that needs to be transmitted for data analysis. When the activity process nodes in other information links cannot communicate directly, the activity process nodes in the information service information link can act as relay nodes to send information. According to the formed information links, situation chains, decision chains, and execution chains are further formed.

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