A system network activity model construction optimization method and system

Abstract

The application belongs to the technical field of system model construction and evaluation. A system network activity model construction optimization method and system are provided. The method comprises the following steps: extracting various types of nodes of a target task based on a function dimension, constructing respective target activity process node models, abstracting activity process nodes of the target task into a situation awareness node, an auxiliary decision node, an action control node and an information service node according to the OODA cycle theory, determining basic information links according to the target activity process node models, forming an activity program chain representing activity efficiency according to the mapping and ordered combination of the target activity to the information links, constructing a system network activity model based on the target activity process node models and multiple information links, and performing efficiency evaluation on the system network activity model by using a fuzzy comprehensive evaluation method to determine whether the task activity meets the task demand. The application can obtain a more effective system network activity model and realize more effective activity efficiency evaluation.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of model system engineering, and provides a system network activity model construction optimization method and system. BACKGROUND

[0002] Model-based system engineering (MBSE) has been widely applied in the fields of complex product engineering such as aviation, aerospace, ship and automobile. The modeling method is used to support system demand, design, analysis, test and confirmation activities. A logically consistent general system model is used throughout the system life cycle stage. The current MBSE methodology mainly includes: IBM Harmony and INCOSE OOSEM based on SysML; Vitech MBSE Methodology based on SDL; and OPM based on OPDs / OPL, which focuses on system engineering development domain and operation domain. For how to efficiently respond to task and environmental changes and effectively improve designer decision-making efficiency, there are problems such as insufficient model construction theory guidance, too general system model, relatively coarse model granularity, and incomplete evaluation index system.

[0003] At present, there are the following problems: the current activity model design method is not strong in pertinence, the logic chain is not complete, and there is a lack of a relatively unified design framework; the existing activity process focuses on function description, lacks overall efficiency of the activity, and decision-makers cannot fully understand the role of each link activity process node and their mutual influence in a complex environment; and the existing simulation evaluation index often fails to fully reflect each link of the OODA ring, resulting in a lack of comprehensiveness of the evaluation result.

[0004] Therefore, it is necessary to provide a new system network activity model construction optimization method and system to solve the above problems. SUMMARY

[0005] The application provides a system network activity model construction optimization method and system to solve the technical problems in the prior art such as insufficient model construction theory guidance, too general system model, relatively coarse model granularity, and incomplete evaluation index system, and how to efficiently respond to task and environmental changes and effectively improve designer decision-making efficiency. The technical problems to be solved by the application are solved by the following technical solutions.

[0006] The first aspect of the present application provides a system network activity model construction optimization method, which comprises: extracting various nodes of a target task based on a function dimension to construct respective target activity process node models, specifically comprising: based on the OODA cycle theory, abstracting the activity process nodes of the target task into the following nodes according to functions: situation awareness nodes, auxiliary decision nodes, action control nodes and information service nodes; determining a plurality of information links according to the target activity process node model, forming an activity program chain representing activity efficiency 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 the plurality of information links; and performing efficiency evaluation on the constructed system network activity model by using a fuzzy comprehensive evaluation method to determine whether the task activity in the target task meets the task demand, specifically comprising: establishing an evaluation matrix based on the to-be-evaluated indexes and calculating and determining the weight of each to-be-evaluated index in the to-be-evaluated system; and performing fuzzy synthesis operation by using the calculated and determined weight and the single-factor evaluation matrix to obtain a comprehensive evaluation result.

[0007] The second aspect of the present application provides a system network activity model construction optimization system, which executes the system network activity model construction optimization method of the first aspect of the present application, and comprises: a first construction module for extracting various nodes of a target task based on a function dimension to construct respective target activity process node models, specifically comprising: based on the OODA cycle theory, abstracting the activity process nodes of the target task into the following nodes according to functions: situation awareness nodes, auxiliary decision nodes, action control nodes and information service nodes; a first determination module for determining a plurality of information links according to the target activity process node model, forming an activity program chain representing activity efficiency according to the mapping and ordered combination from the target activity to the information links; a second construction module for constructing a system network activity model based on the constructed target activity process node model and the plurality of information links; and an evaluation optimization module for performing efficiency evaluation on the constructed system network activity model by using a fuzzy comprehensive evaluation method to determine whether the task activity in the target task meets the task demand, specifically comprising: establishing an evaluation matrix based on the to-be-evaluated indexes and calculating and determining the weight of each to-be-evaluated index in the to-be-evaluated system; and performing fuzzy synthesis operation by using the calculated and determined weight and the single-factor evaluation matrix to obtain a comprehensive evaluation result.

[0008] The third aspect of the present application provides an electronic device, which comprises: one or more processors; a storage device for storing one or more programs; and when the one or more programs are executed by the one or more processors, the one or more processors implement the system network activity model construction optimization method of the first aspect of the present application.

[0009] The fourth aspect of the present application provides a computer readable medium, which stores a computer program, and the computer program is executed by a processor to implement the system network activity model construction optimization method of the first aspect of the present application.

[0010] The embodiments of the present application have the following advantages:

[0011] Compared with the prior art, the present application specifically constructs an activity process node model and each information link model, and carries out an objectified representation on the activity elements involved in a target task, integrates, refines and reorganizes information nodes (i.e. activity process nodes) and information links based on an observation, judgment, decision and action (OODA) cycle process, forms a system network activity model, thereby realizing an effective integration and cooperation of information data in a complex multi-dimensional confrontation environment, and based on a simulation evaluation index system of activity effectiveness, the effect of each link of OODA can be accurately reflected, each evaluation index involved in a task activity in a target task is evaluated for effectiveness by using a fuzzy comprehensive evaluation method model, an evaluation index and the related attributes of the corresponding node in the system network activity model which do not meet the task requirements are effectively found, the attribute values corresponding to each evaluation index are adjusted according to the effectiveness evaluation result, the system network activity model is re-evaluated until all evaluation indexes are greater than the corresponding set threshold, so that all evaluation indexes involved in the activity in the target task meet the task requirements, and the system network activity model is optimized, which can more effectively realize the construction and optimization of the system network activity model at the same time. BRIEF DESCRIPTION OF DRAWINGS

[0012] Figure 1 is a step flow chart of an example of the system network activity model construction optimization method of the present application;

[0013] Figure 2 is a schematic block diagram of an example of a system to be evaluated in the system network activity model construction optimization method of the present application;

[0014] Figure 3 is a step flow chart of an example of the effectiveness evaluation of the system network activity by using a fuzzy comprehensive evaluation method in the system network activity model construction optimization method of the present application;

[0015] Figure 4 is a structure block diagram of the system network activity model construction optimization system of the present application;

[0016] Figure 5 is a structure schematic diagram of an electronic equipment embodiment according to the present application;

[0017] Figure 6 is a structure schematic diagram of a computer readable medium embodiment according to the present application. DETAILED DESCRIPTION

[0018] It should be noted that the embodiments in the present application and the features in the embodiments can be combined with each other without conflict. The present application will be described in detail below with reference to the accompanying drawings and in combination with the embodiments.

[0019] In view of the above problems, the present application proposes a system network activity model construction optimization method, which constructs an activity process model system based on OODA, performs evaluation of simulation evaluation indexes, and forms a framework of 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 represented concretely, the information nodes (i.e. activity process nodes) and information links are integrated, refined and reorganized based on the observation, judgment, decision and action (OODA) cycle process, the system network activity model is formed, so as to realize effective integration and collaboration of information data in a complex multi-dimensional confrontation environment, and based on the simulation evaluation index system of activity effectiveness, the effect of each link of OODA can be accurately reflected. The fuzzy comprehensive evaluation method model is used to evaluate the effectiveness of each index involved in the task activity in the target task, so as to optimize the system network activity model, which can more effectively realize the construction and optimization of the system network activity model at the same time.

[0020] It should be noted that the method of the present application is widely applicable, and is particularly suitable for complex system activity process systems containing multiple types of equipment, multiple personnel or personnel groups, multiple information service types, and multiple environmental information. For example, air group confrontation training systems, ground confrontation group systems containing satellite detection, mountain search and rescue systems, group confrontation command systems, etc. The above are only optional examples for description, and cannot be understood as a limitation of the present application.

[0021] Embodiment 1

[0022] The content of the present application will be described in detail below with reference to Figure 1 , Figure 2 , Figure 3 .

[0023] Figure 1 is a step flow chart of an example of the system network activity model construction optimization method of the present application. Figure 2 is a schematic block diagram of an example of the system to be evaluated in the system network activity model construction optimization method of the present application.

[0024] Referring to Figure 1 and Figure 2In step S101, various types of nodes of the target task are extracted based on the function dimension to construct respective target activity process node models, specifically including abstracting the activity process nodes of the target task into the following nodes based on the OODA cycle theory: a situation awareness node, an auxiliary decision node, an action control node, an information service node, and an execution node.

[0025] In an embodiment, the target task refers to an execution task of the air group confrontation training system.

[0026] The target task includes various types of activity process nodes involved in the execution task. In this example, the activity process node refers to a set of nodes that execute or participate in the activity process, and the node is various types of units (or enterprises), devices, or personnel.

[0027] Specifically, the activity process nodes are abstracted into four types based on the OODA cycle theory, namely, a situation awareness node , an auxiliary decision node , an action control node , and an information service node .

[0028] It should be noted that the OODA cycle theory, which is the full name of Observe (observation), Orient (adjustment), Decide (decision), and Act (action). In this example, it specifically refers to a closed loop formed by the observation phase related to the execution of the target task, the phase of adjusting and controlling actions, the phase of deciding how to execute the action of the target task, and the phase of executing the target task.

[0029] For example, from the disclosed historical task data, the activity process nodes are abstracted into a situation awareness node , an auxiliary decision node , an action control node , and an information service node based on the OODA cycle theory. 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.

[0030] 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 device deployment, action, intention, and location, state, etc., to 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, unmanned aerial vehicles, etc.

[0031] Assistant decision node To make and implement activity plans, the direction and way of decision action. Assistant decision node relies on the information support provided by situation awareness node, through analysis, evaluation and decision, to command various nodes to implement action. Assistant decision node The corresponding entity is mainly various command centers.

[0032] Action control node To control and implement activities, receive instructions from assistant decision nodes, execute tasks and feedback in real time, so that assistant decision nodes can adjust and control the action of target tasks. The entity corresponding to the assistant decision node is various information control platforms, such as ships, aircraft, special vehicles, etc.

[0033] Information service node To provide various information service support, including communication, liaison, data sharing and technical support, etc. The entity corresponding to information service node includes communication satellite, satellite terminal, ground station, data center, etc. Information service node provides communication connection, data transmission, data sharing and other infrastructure and service support.

[0034] Further, according to the above four types of node attributes and functional characteristics, the activity process node model corresponding to the target task is abstracted and refined, which can be represented as:

[0035]

[0036] Among them, N represents the activity process node model corresponding to the target task; represents the unique equipment identification ID to which the activity process node belongs; represents the node identity: the first party, such as the red party, the second party, such as the blue party; represents the node type, that is, ; represents the node function attribute vector, which represents the function parameters of the node, such as multi-dimensional vector, matrix, etc.

[0037] The function attribute vectors of different types of nodes are different. For example, the functionality of a certain situation awareness node N S can be represented as:

[0038]

[0039] Among them, represents the function attribute value obtained by quantifying the functionality of a certain situation awareness node N S ; a maximum radius of the target task; a rate of acquisition of important data (e.g. equipment deployment data, target location data, etc. required for the execution of the target task); a target recognition accuracy; a tracking accuracy, an update rate.

[0040] In addition, for the attribute vector, an extended attribute vector is also included, for example, using to represent.

[0041] For example, the various functional attributes (including multi-level attributes and vectors or numerical values quantitatively represented) of a certain aircraft node model (i.e. a situation awareness node model) can be seen in Table 1.

[0042] Table 1

[0043]

[0044] Table 1 is a diagram showing an example of the various functional attributes of a certain aircraft node model.

[0045] Further, the functional attributes of each node also include different device types, the number of each device, the number and location of command centers, the location and number of information monitoring points, air tasks, sea tasks, ground tasks, etc. Each node also contains vectors or numerical values quantitatively represented by the functional attributes.

[0046] It should be noted that the above is only an optional example for illustration and should not be construed as a limitation on the present application.

[0047] Next, in step S102, a plurality of information links are determined according to the target activity process node model, and an activity program chain representing the activity effectiveness is formed according to the mapping and ordered combination of the target activity to the information links.

[0048] According to different focused functions of the activity process nodes in the execution of the target task, such as the execution of counter-information, the monitoring of changes in personnel deployment or equipment deployment of participants, and information such as the withdrawal of participants, the activity process nodes are classified and combined to form a plurality of information links.

[0049] 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 .

[0050] It should be noted that in the present example, the four types of information links are mutually exclusive, and the information links involved in the target task are sequentially combined to form multiple types of information links (e.g., situation chain, decision chain, and execution chain).

[0051] The number of active process nodes in each information link is two, and each information link includes one type of active process node, two types of active process nodes, or more types of active process nodes.

[0052] Specifically, for example, the number of active process nodes of the situation awareness information link is three, the situation awareness information link contains target parameters and states, generates situation awareness information, and can be sent to all active process nodes. If the communication is allowed, if the accuracy and time delay of the information meet the decision needs, the information can be directly provided to the related active process nodes. The information content of the auxiliary decision information link includes task planning and action execution instructions; the action control information link contains personnel command and equipment control information; and the information service information link contains data analysis information that needs to be transmitted. When other active process nodes cannot directly communicate, the active process nodes in the information service information link can act as relay nodes to send information.

[0053] In a specific embodiment, the situation awareness information link contains at least one situation awareness node (e.g., a first situation awareness node), and the situation awareness node can directly share the situation information it contains to all active process nodes (including situation awareness nodes different from the first situation awareness node, auxiliary decision nodes, action control nodes, and information service nodes).

[0054] Alternatively, when the situation awareness information accuracy and time delay meet the decision needs of the current target task, the situation awareness information can be directly supplied to the auxiliary decision nodes, the action control nodes, and the information service nodes, if the communication between the nodes is allowed. For example, it can be recorded as wherein, is a pair of nodes.

[0055] For example, the situation awareness information link is wherein, the situation information of the first situation awareness node can be directly shared to 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 wherein, the situation information of the first situation awareness node can be directly reported to the first auxiliary decision node or reported to the first auxiliary decision node after being processed by other nodes . Please refer to Table 2 below for details. The nodes mentioned above are also referred to as nodes in Table 2.

[0056] For example, the number of activity process nodes in the auxiliary decision-making information link is three, specifically including at least one auxiliary decision-making node (e.g., a first auxiliary decision-making node). The information content of the auxiliary decision-making information link includes the task planning and action execution instructions for the target task. Specifically, specific instructions generated by the auxiliary decision-making node, such as adjustment instructions, are sent to other nodes level by level. For example, the auxiliary decision-making information link is... The first auxiliary decision node The adjustment instruction is sent to the second auxiliary decision node. And further sent to the third auxiliary decision 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, for example, uses... This indicates, specifically, as .

[0057] The information content of the action control information link includes personnel command, equipment control information, and feedback control and task collaboration information generated by auxiliary decision-making nodes or action control nodes. This information can be sent to the relevant action control nodes. In some cases, it may be possible to bypass other nodes. Action control information link is denoted as .

[0058] 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 act as a relay node to send information to relevant situational awareness nodes, auxiliary decision-making nodes, behavior control nodes, and other information service nodes. The information service information link is specifically denoted as... .

[0059] Table 2

[0060]

[0061] Table 2 shows examples of various types of information links.

[0062] Note: * indicates 0 or more; + indicates 1 or more.

[0063] 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 then further to the third auxiliary decision-making node of the sub-regional command post.

[0064] Then, according to the formed information link, a situation chain, a decision chain and an execution chain are further formed.

[0065] As the basic information flow of the activity process, each type of information link model can only reflect the specific function and single ability of the system, but cannot reflect the overall ability of the system or the system, and cannot support the completion of the target task or the activity task alone. Taking the situation awareness information link model as an example, the information of the source, flow and time sequence of each type of information link model can only reflect the situation awareness ability, and the communication network resource competition and mutual driving effect between information activities cannot be represented, and only using cannot meet the task demand. Based on the ordered combination of information links, the combined information link flow model reflecting the overall function required by the target task, i.e. the activity procedure chain model, is constructed.

[0066] Based on the OODA cycle theory, according to observation monitoring, situation judgment, auxiliary decision and action control, the corresponding activity procedure chain model is constructed according to the different target tasks, and specifically includes: a situation chain , a decision chain and an execution chain .

[0067] The situation chain refers to taking the situation awareness node as the starting point, transmitting various types of data, voice, images and the like related to the situation to the auxiliary decision node (for example, various situation users of command personnel, execution personnel and the like). According to the node relationship, the combination mode is defined as + and the like.

[0068] The decision chain refers to taking the auxiliary decision node as the starting point, taking the friendly neighbor node or the belonging node and the action control node as the terminal point, taking the command information as the linking link, and forming the link in the command cooperation process of the node elements and the friendly neighbor node. According to the node relationship, the combination mode is defined as + and + and the like.

[0069] The execution chain refers to taking the situation awareness node as the starting point, various types of execution corresponding nodes as the terminal point, and the information link directly related to the execution task. Compared with other links, the execution chain usually has the strongest timeliness. According to the data transmission relationship or transmission relationship (for example, sending data or receiving data) between nodes, the combination mode is defined as + .

[0070] Taking satellite support for a ground operation mission (i.e., the target mission) as an example, based on the target mission, a mapping and functional combination from the target mission (or activity mission) to the information link is carried out to form an activity procedure chain, as shown in Table 3.

[0071] Table 3

[0072]

[0073] Table 3 shows an example table of information related to activities in the target task.

[0074] Specifically, the target task or activity task is sorted out and decomposed to determine the corresponding link category and extract the activity process nodes. Based on the activity process nodes, the information link combination method is determined (it must meet the constraint that the execution is terminated at the corresponding node or action control node). Then, combined with the target task requirements and process description, activity process nodes in different information links are selected for functional combination, so that multiple information links of various types form a complex tree-like semi-closed network or closed network, and finally form an activity procedure chain corresponding to the target task.

[0075] Based on the activity process node model, each information link, and basic information such as activity process name, identifier, and objective, an activity process model is constructed. The activity process model is defined as a quintuple:

[0076]

[0077] Where A represents the activity process model of the target task, specifically using a five-tuple representation. The activity process name identifies the specific activity process and is used to distinguish different activity processes. A unique identifier for each activity process is a number used to ensure the uniqueness of each activity process within the system or framework (e.g., " = 001 indicates that this is the only activity process in the system with the unique number 001); The objectives of an activity process are the goals or results that the activity process is expected to achieve, in order to help develop a detailed action plan and evaluate the effectiveness of the activity process; The activity process node set refers to the set of nodes that execute or participate in the activity process. Nodes can be various types of units (enterprises or organizations), equipment, or personnel, i.e., situational awareness nodes. Decision support nodes Action control node and information service nodes ; This is an information link model combination that describes the relationships and interactions between nodes during an activity, i.e., an activity program chain model.

[0078] It should be noted that through the definition of the five-tuple, the current activity in the target task can be more clearly and intuitively represented, and it is also convenient for the user to evaluate the current activity and evaluate whether the activity meets the expectation, that is, whether the relationship between the activity target and the activity process node, link model matches. The above is only described as an optional example and cannot be understood as a limitation of the present application.

[0079] Next, in step S103, a system network activity model is constructed based on the constructed target activity process node model and multiple information links.

[0080] Based on the OODA cycle theory, the activity process in the historical task data is abstracted into four typical activity processes, namely observation and monitoring, situation judgment, auxiliary decision-making, and coordinated action.

[0081] Taking a satellite supporting a certain ground action task 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 the counter-training between participants.

[0082] The target task is divided into four activities of observation and monitoring, situation judgment, auxiliary decision-making, and coordinated action. One of the activities in the observation and monitoring type is “collecting the latest intelligence”, which is structurally described.

[0083] First, observe and monitor the activity process corresponding to each target task. Collect the latest intelligence information and express it in the following way: “Collecting the latest intelligence” indicates that the activity process name of the target task is “collecting the latest intelligence”; 001, which uniquely identifies this activity process and ensures that there is no overlap in the system or system; “Continuously obtain the latest intelligence information of the personnel and equipment deployment, equipment status, command system and countermeasures of Blue, so as to adjust in real time during the counter-training process”; , In turn, two satellites, two unmanned aerial vehicles, Regional command post, Command center, Information monitoring point 1; Since the specific transmission link relationship is numerous and redundant, limited by the length, the Three types of nodes are described simply.

[0084] Next, the situation judgment activity process is described.

[0085] For the situation judgment activity process, express it in the following way: “Determine target attributes”, which indicates that the activity process name is “determine target attributes”; =002, this number uniquely identifies this activity process, ensuring no overlap in the system or system; “determine and monitor the type, characteristics and counter-training value of the important targets of the opponent, including air and ground air defense forces, command and control nodes, radar stations, communication nodes, etc.”; , In turn, two satellites, two unmanned aerial vehicles, for regional command, for intelligence station 1;

[0086] , because the specific transmission link relationship is numerous and miscellaneous, with the three types of nodes are described simply.

[0087] For the auxiliary decision-making activity process, the following expression is used to represent: =“draft action plan”, indicating that the activity process name is“draft action plan”; =003, this number uniquely identifies this activity process, ensuring no overlap in the system or system; “develop detailed operational plans, including major and secondary counter-attack directions, feint directions, optimal counter-attack opportunities and counter-attack methods, to provide clear action instructions for air counter-attack and air counter-attack”; , for regional command, for command center, in turn, information monitoring point 1, information monitoring point 2, information monitoring point 3, for the counter node; , because the specific transmission link relationship is numerous and miscellaneous, with the three types of nodes are described simply.

[0088] For the cooperative action activity process, the following expression is used to represent: =“sustained suppression of the opponent's target”, which indicates that the activity process name is“sustained suppression of the opponent's target”; =004, this number uniquely identifies this activity process, ensuring no overlap in the system or system. “sustain fire suppression on the opponent's important air defense and command and control nodes, weaken their defense and command and control capabilities, and create conditions for breakthrough, suppression efficiency not less than 90%”; , for early warning aircraft, for command center, for information monitoring point 1, for electronic jamming equipment 1, electronic jamming equipment 2; , because the specific transmission link relationship is numerous and miscellaneous, with the Three types of nodes are described briefly.

[0089] Through the target activity process node model constructed based on step S1101 and the multi-information link (also including activity program chain, etc.) formed by step S102, a more effective system network activity model can be constructed. Through the above modeling process, the decomposition from task to activity is realized, and the system network activity is scientifically, intuitively and quantitatively described, so that the task and the system network activity can be more intuitively displayed, and a more effective data basis is provided for the user to carry out subsequent performance evaluation, analysis and optimization of various indicators or data.

[0090] It should be noted that the above is only described as an optional example and cannot be understood as a limitation of the present application.

[0091] 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 activity in the target task meets the task requirements, which specifically includes: based on the to-be-evaluated indicators, an evaluation matrix is established, and the weight of each to-be-evaluated indicator in the to-be-evaluated system is calculated and determined; the calculated and determined weight and the single-factor evaluation matrix are used for fuzzy synthesis operation to obtain a comprehensive evaluation result.

[0092] 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.

[0093] Specifically, the weight of each to-be-evaluated indicator in the to-be-evaluated system is calculated first to form a corresponding evaluation matrix, and consistency calculation is performed on each to-be-evaluated indicator to evaluate the performance of each target task; then fuzzy comprehensive evaluation is performed to obtain a fuzzy comprehensive evaluation result, a histogram is drawn to determine the to-be-optimized to-be-evaluated indicators to further optimize the system network activity model.

[0094] It should be noted that the system network activity is often restricted by many fuzzy factors, and the fuzzy comprehensive evaluation method can highly adapt to the complexity and variability of the environment, effectively integrate the fuzzy information in the system network activity, and ensure the effectiveness and scientificity of the evaluation result. Therefore, the fuzzy comprehensive evaluation method is used to evaluate the activity performance of the system network activity model.

[0095] When the target task is a to-be-predicted task, the task activity of the to-be-predicted task is specifically combed and decomposed, the corresponding information link categories are determined, and the activity process nodes are determined from the task activity according to the method of step S101. Next, the combination method of the information link is determined according to the activity process nodes, and the activity process nodes in the information link are functionally combined to form an activity program chain, thereby completing the mapping process of the to-be-predicted task to the node information link.

[0096] Then, the performance of the to-be-predicted task is evaluated.

[0097] Specifically, as shown in the table, the performance evaluation specifically includes the following steps. Figure 3

[0098] Step S201: Determine the evaluation object and the evaluation total target of the target task.

[0099] The activity process performance is taken as the activity process performance, and the evaluation total target is determined according to the selected evaluation object. The evaluation total target is derived from the target task or the activity process target, such as the four types of target tasks corresponding to observation monitoring, situation judgment, auxiliary decision-making, and cooperative action. The performance of the four types of target tasks is evaluated according to the evaluation indicators or evaluation elements. For details, please refer to Figure 2 The elements in the evaluation element layer are quantitatively evaluated, and at least three evaluation elements are quantitatively evaluated to determine the performance of the four types of target tasks.

[0100] In the example of Figure 2 , the evaluation object layer specifically includes the performance of the four types of target tasks corresponding to observation monitoring, situation judgment, auxiliary decision-making, and cooperative action, such as observation monitoring activity performance, situation judgment activity performance, auxiliary decision-making activity performance, and cooperative action activity performance. The evaluation element layer includes target arrival rate, target action efficiency, observation coverage rate, target discovery rate, observation accuracy, observation timeliness, situation data acquisition rate, situation judgment accuracy, situation judgment timeliness, information reception rate, information processing efficiency, decision-making accuracy, decision-making timeliness, and cooperative action accuracy, etc. The evaluation data layer specifically includes target arrival quantity, target time, area, discovered target quantity, correctly identified target quantity, identified target time, acquired situation data quantity, correctly situation judged quantity, situation judgment time, information processing time, correctly decision-making time, correctly cooperative execution quantity, and cooperative action time, etc.

[0101] Step S202: Determine the to-be-evaluated system corresponding to the target task.

[0102] According to the characteristics of the confrontation task, a to-be-evaluated system including field reconnaissance monitoring, confrontation situation judgment, confrontation command decision-making, and cooperative confrontation action is constructed to form the to-be-evaluated system corresponding to the target task (in this example, a simulation evaluation index system, for details, please refer to Figure 2 )

[0103] Step S203: Determine the to-be-evaluated index.

[0104] Based on the to-be-evaluated system, the evaluation element set , the evaluation set , specifically {excellent, good, medium, poor, very poor}.​

[0105] Specifically, at least three evaluation elements involved in each target task of the to-be-evaluated system are taken as to-be-evaluated indexes to form an evaluation element set and an evaluation set.

[0106] Step S204: An evaluation matrix is established according to the determined to-be-evaluated indexes.

[0107] For each to-be-evaluated index (for example, using , a corresponding evaluation result is made, and the corresponding membership degree is , which can be directly calculated according to the expert scoring table to form an evaluation matrix , where .

[0108] Step S205: The weight of each to-be-evaluated index in the to-be-evaluated system is determined.

[0109] Specifically, the analytic hierarchy process is used to judge the rationality of each evaluation matrix and the consistency test of hierarchical ordering. The analytic hierarchy process is used to determine the weight of each to-be-evaluated index in the to-be-evaluated system. The 1-9 scale method in Table 4 is used to compare each to-be-evaluated index with each other to-be-evaluated index, an evaluation matrix is constructed, the maximum eigenvalue corresponding to the eigenvalue of the evaluation matrix is calculated, and the corresponding eigenvector, i.e., the weight vector, is obtained, for example, . For the evaluation matrix, the evaluation elements corresponding to the target task are selected to form an evaluation matrix (for example, the evaluation matrix for observing the effectiveness of the monitoring activity in Table 5).

[0110] Table 4

[0111]

[0112] Table 4 shows an example of the “1-9” scale method.

[0113] Table 5

[0114]

[0115] Table 5 shows a schematic table of an example of the evaluation matrix for observing the effectiveness of the monitoring activity and the weight.

[0116] The following expression is used to calculate the consistency index of each evaluation matrix corresponding to the to-be-evaluated index of different target tasks to perform a consistency test:

[0117]

[0118] wherein, the consistency index of the current evaluation matrix P is represented; n represents the number of evaluation factors at the same level. Different target tasks correspond to different evaluation levels and different numbers of evaluation factors. n is a positive integer. It is the largest eigenvalue of the current evaluation matrix.

[0119] When performing a consistency check, it is first necessary to multiply the evaluation elements row by row, and then take the nth root. After normalization, we get The following expression is used to calculate and determine the largest eigenvalue of the current evaluation matrix. :

[0120]

[0121]

[0122]

[0123] in, This represents the root value obtained by multiplying the evaluation elements by row and then taking the nth root. This represents the weight value obtained by normalizing the i-th root value; The largest eigenvalue of the current evaluation matrix R is given by the matrix term formed by quantifying multiple evaluation elements, i.e., the evaluation elements themselves. This represents the evaluation element, or matrix item, in the i-th row and j-th column of the current evaluation matrix R. i represents the i-th row of the current evaluation matrix R, and j represents the j-th column of the current evaluation matrix R. i and j are both positive integers, specifically 1, 2, ..., n. The k-th root value; k represents the root value. The quantity, k is a positive integer, specifically 1, 2, ..., n; The product of the current evaluation matrix R and the weight vector W. This represents the i-th evaluation element after multiplication. For the reason The vector formed by the vector.

[0124] The consistency ratio is calculated using the following expression. To verify the consistency of each evaluation matrix:

[0125]

[0126] in, A consistency index characterizing all evaluation matrices, including the current evaluation matrix; This represents the average consistency index of the judgment matrix generated within a specified historical period based on different target tasks, evaluation indicators, the number of evaluation factors, and the matrix order. Specific parameters are shown in Table 6.

[0127] The specified historical time includes three months, six months, one year, two years, three years, etc. from the current time to the past.

[0128] When , it indicates that the consistency degree of the current evaluation matrix is relatively satisfactory, and the eigenvector calculation of the current evaluation matrix can be carried out; if , the current evaluation matrix should be adjusted until the current evaluation matrix satisfies the consistency .

[0129] Table 6

[0130]

[0131] Table 6 shows the value table of the consistency index RI

[0132] Further, by using the weight vector and the evaluation matrix of the single evaluation element, the comprehensive evaluation result is obtained by fuzzy synthesis operation (such as weighted average method, principal factor determination type, principal factor highlighting type, etc.) , wherein represents a fuzzy synthesis operator, and in the present example, the weighted average method is used.

[0133] Next, the element quantization processing of the to-be-evaluated index is carried out, and according to the weighted average method, the following expression is used to calculate the evaluation representation value of the to-be-evaluated index embodied in the activity task, so as to evaluate the comprehensive evaluation result:

[0134]

[0135] , wherein represents the evaluation representation value of the to-be-evaluated index embodied in the activity task; is the ith evaluation element (or matrix element) in the comprehensive evaluation matrix, and i is a positive integer; is the quantization result of the score level obtained by evaluating or processing each to-be-evaluated index: = [0.9, 0.7, 0.5, 0.3, 0.1], is a to-be-determined coefficient, which is specifically in the range of 0.8-3.0, and the purpose is to control the greater role of the activity task.

[0136] Specifically, = [0.9 (excellent) 0.7 (good) 0.5 (general) 0.3 (poor) 0.1 (very poor)]. Preferably, the to-be-determined coefficient = 1, or pending coefficient = 2, can effectively control the larger The role played in the active task.

[0137] Then, a histogram is drawn according to the finally obtained fuzzy comprehensive evaluation result, so as to intuitively determine the evaluation indexes with weaker performance, so as to optimize the next round of system network activity model, and continuously optimize the system network activity model until all the evaluation indexes in the fuzzy comprehensive evaluation result meet the consistency requirement.

[0138] Specifically, the set threshold S determined according to the nature of the active task (for example, the task involves a site, the risk of the task, etc.) is in the range of 60-80. Preferably, the set threshold S is 70.

[0139] When the calculated evaluation characteristic 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 requirement.

[0140] When the calculated evaluation characteristic 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 requirement.

[0141] Further, the evaluation indexes that do not meet the task requirement are respectively found to find the related attributes of the corresponding nodes in the system network activity model, the attribute values corresponding to the evaluation indexes are adjusted, the system network activity model is re-evaluated until all the evaluation indexes are greater than the corresponding set threshold, so that all the evaluation indexes involved in the activity of the target task meet the task requirement.

[0142] By using the fuzzy comprehensive evaluation method model to evaluate the performance of each evaluation index involved in the task activity of the target task, the evaluation index that does not meet the task requirement in the system network activity model and the related attributes of the corresponding node are effectively found, the attribute values corresponding to the evaluation indexes are adjusted according to the performance evaluation result, the system network activity model is re-evaluated until all the evaluation indexes are greater than the corresponding set threshold, so that all the evaluation indexes involved in the activity of the target task meet the task requirement, so as to optimize the system network activity model, which can more effectively realize the construction and optimization of the system network activity model at the same time.

[0143] It should be noted that the above is only described as an optional example, and cannot be understood as a limitation of the present application.

[0144] Compared with the prior art, the system for constructing and optimizing a system network activity model specifically realizes effective integration and cooperation of information data in a complex multi-dimensional confrontation environment by constructing an activity process node model and each information link model, integrating, refining and reorganizing information nodes (i.e., activity process nodes) and information links based on an observation, judgment, decision and action (OODA) cycle process, and forming a system network activity model, and can accurately reflect the effect of each link of OODA based on a simulation evaluation index system of activity effectiveness, specifically uses a fuzzy comprehensive evaluation method model to evaluate the effectiveness of each evaluation index involved in a task activity in a target task, effectively finds an evaluation index that does not meet the task requirements and the related attributes of the corresponding node in the system network activity model, adjusts the attribute values corresponding to each evaluation index according to the effectiveness evaluation result, reevaluates the system network activity model until all evaluation indexes are greater than the corresponding set threshold, so that all evaluation indexes involved in the activity in the target task meet the task requirements, and the system network activity model is optimized, which can more effectively realize the construction and optimization of the system network activity model at the same time.

[0145] Embodiment 2

[0146] The following is an embodiment of the system of the present application, which can be used to execute the method embodiment of the present application. For details not disclosed in the system embodiment of the present application, please refer to the method embodiment of the present application.

[0147] Figure 4 is a structural schematic diagram of an example of a system for constructing and optimizing a system network activity model according to the present application. The following will be described with reference to Figure 4 , a system for constructing and optimizing a system network activity model, which executes the method for constructing and optimizing a system network activity model described in Embodiment 1 of the present application.

[0148] As shown in Figure 4 , the system for constructing and optimizing a system network activity model 400 includes a first constructing module 410, a first determining module 420, a second constructing module 430 and an evaluation and optimization module 440.

[0149] In a specific embodiment, the first construction module 410 extracts various types of nodes of the target task based on the functional dimension to construct respective target activity process node models, specifically including based on the OODA cycle theory, abstracting the activity process nodes of the target task according to functions into the following nodes: situation awareness nodes, auxiliary decision nodes, action control nodes, and information service nodes. The first determination module 420 determines a plurality of information links according to the target activity process node model, forms an activity program chain representing activity effectiveness according to 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 the plurality of information links. The evaluation and optimization module 440 is configured to perform effectiveness evaluation on the constructed system network activity model by using a fuzzy comprehensive evaluation method to determine whether the task activities in the target task meet the task requirements, specifically including: based on the to-be-evaluated indexes, establishing an evaluation matrix and calculating and determining the weight of each to-be-evaluated index in the to-be-evaluated system; and performing fuzzy synthesis operation by using the calculated and determined weight and the single-factor evaluation matrix to obtain a comprehensive evaluation result.

[0150] According to an optional embodiment, the plurality of information links are determined according to the target activity process node model, and the activity program chain representing activity effectiveness is formed according to mapping and ordered combination from the target activity to the information links, including:

[0151] The activity process nodes are classified and combined to form the following information links to construct an information link model: situation awareness information links, auxiliary decision information links, action control information links, and information service information links. The situation awareness information links contain at least three activity process nodes, and the situation awareness information links contain target parameters and states, and can be sent to all activity process nodes to generate situation awareness information.

[0152] The information content of the auxiliary decision information links includes task planning and action execution instructions; the action control information links contain personnel command and equipment control information; and the information service information links contain information that needs to be transmitted for data analysis. When other activity process nodes cannot directly communicate, the activity process nodes in the information service information links can act as relay nodes to send information.

[0153] According to the formed information links, a situation chain, a decision chain, and an execution chain are further formed.

[0154] According to an optional embodiment, the activity process model is constructed according to the activity process node model and the information link model, the activity process name, the identifier, and the target, and the activity process model is defined as a five-tuple.

[0155] According to the activity process node, according to the satisfaction of the execution corresponding node or the action control node as the end point of the defined condition, the information link combination mode is determined.

[0156] The activity process nodes in different information links are selected for functional combination, so that multiple multi-type information links form a complex tree network-shaped semi-closed network or closed network, and finally form an activity program chain corresponding to the target task.

[0157] According to the optional implementation, the fuzzy comprehensive evaluation method is used to evaluate the performance of the constructed system network activity model, including: calculating the weight of each to-be-evaluated index in the to-be-evaluated system to form a corresponding evaluation matrix, and performing consistency calculation on each to-be-evaluated index to evaluate the performance of the activity; fuzzy comprehensive evaluation is performed to obtain a fuzzy comprehensive evaluation result, and a histogram is drawn to intuitively determine the to-be-optimized to-be-evaluated index, which is used to optimize the next round of system network activity model, and the process of continuously optimizing the system network activity model is continued until the task requirements are met.

[0158] According to the optional implementation, according to the weighted average method, the following expression is used to calculate the evaluation characteristic value of the to-be-evaluated index in the activity task to evaluate the comprehensive evaluation result:

[0159]

[0160] Among them, represents the evaluation characteristic value of the to-be-evaluated index in the activity task; is the i-th evaluation element (or matrix element) in the comprehensive evaluation matrix, and i is a positive integer; is the quantization result of the score level obtained by evaluating or processing each to-be-evaluated index: = [0.9, 0.7, 0.5, 0.3, 0.1], is a to-be-determined coefficient, specifically in the range of 0.8-3.0, and the purpose is to control the larger role in the activity task.

[0161] According to the optional implementation, the set threshold S determined according to the nature of the activity task is in the range of 60-80.

[0162] When the calculated evaluation characteristic 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.

[0163] When the calculated evaluation characteristic 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.

[0164] Further, the evaluation indexes that do not meet the task requirements are respectively found to be corresponding to the attributes of the nodes in the system network activity model, the attribute values corresponding to the evaluation indexes are adjusted, the system network activity model is re-evaluated until all the evaluation indexes are greater than the corresponding set threshold, so that all the evaluation indexes involved in the activities in the target task meet the task requirements.

[0165] According to an optional embodiment, the consistency indexes of the evaluation matrices corresponding to the evaluation indexes of different target tasks are calculated by using the following expression to perform consistency checking:

[0166]

[0167] wherein, the consistency index of the current evaluation matrix P is represented; n is a positive integer, and different target tasks correspond to different evaluation layers and different numbers of evaluation factors; is the maximum eigenvalue of the current evaluation matrix.

[0168] According to an optional embodiment, when performing consistency checking, the evaluation elements are first multiplied by rows, and then the nth root is taken, and is obtained after normalization processing , and the following expression is used to calculate to determine the maximum eigenvalue of the current evaluation matrix :

[0169]

[0170]

[0171]

[0172] wherein, represents the square root value obtained by multiplying the evaluation elements by rows and then taking the nth root; represents the weight value obtained by normalizing the ith square root value; is the maximum eigenvalue of the current evaluation matrix R, wherein the current evaluation matrix R includes the matrix items formed by quantifying the plurality of evaluation elements, i.e., the evaluation elements, represents the evaluation element in the ith row and jth column of the current evaluation matrix R, i.e., the matrix item, i represents the ith row of the current evaluation matrix R, j represents the jth column of the current evaluation matrix R, and i and j are positive integers, specifically 1, 2,..., n; represents the kth square root vector; k represents the number of square root values, and k is a positive integer, specifically 1, 2,..., n; is the maximum eigenvalue of the current evaluation matrix R, wherein the current evaluation matrix R includes the matrix items formed by quantifying the plurality of evaluation elements, i.e., the evaluation elements, is the product of the current evaluation matrix R and the weight vector W, represents the i-th evaluation element after multiplication, is a vector composed of .

[0173] The consistency ratio is calculated to check the consistency of each evaluation matrix:

[0174]

[0175] wherein, characterizes the consistency index of each evaluation matrix, including the current evaluation matrix; represents the average value of the consistency index of the judgment matrix generated according to the number of different target tasks, evaluation indexes, evaluation factors and matrix order within a specified historical time period.

[0176] It should be noted that, since Figure 4 the system network activity model construction optimization method performed by the system network activity model construction optimization system is substantially the same as the system network activity model construction optimization method in the example of Figure 1 , the same part is omitted.

[0177] Compared with the prior art, the present application specifically constructs an activity process node model and each information link model, and concretely represents the activity elements involved in the target task, integrates, refines and reorganizes the information nodes (i.e. activity process nodes) and information links based on the observe, judge, decide and act (OODA) cycle process, forms a system network activity model, thereby realizing effective integration and collaboration of information data in a complex and multi-dimensional confrontation environment, and based on the simulation evaluation index system of activity effectiveness, the effect of each link of OODA can be accurately reflected, each evaluation index involved in the task activity in the target task is evaluated for effectiveness by using a fuzzy comprehensive evaluation method model, the evaluation index in the system network activity model that does not meet the task requirements and the related attributes of the corresponding node are effectively found, the attribute values corresponding to each evaluation index are adjusted according to the effectiveness evaluation result, the system network activity model is re-evaluated until all evaluation indexes are greater than the corresponding set threshold, so that all evaluation indexes involved in the activity in the target task meet the task requirements, and the system network activity model is optimized, which can more effectively realize the construction and optimization of the system network activity model at the same time.

[0178] Figure 5 is a structural schematic diagram of an electronic device embodiment according to the present application.

[0179] As Figure 5As shown, the electronic device is in the form of a general computing device. The processor can be one or multiple and work cooperatively. The present application does not exclude distributed processing, i.e. the processor can be dispersed in different physical devices. The electronic device of the present application is not limited to a single physical device, but can also be the sum of multiple physical devices.

[0180] The memory stores computer executable programs, usually machine readable codes. The computer readable programs can be executed by the processor to enable the electronic device to perform the method of the present application, or at least some steps of the method.

[0181] The memory includes volatile memory, such as random access memory (RAM) and / or cache memory, and / or non-volatile memory, such as read only memory (ROM).

[0182] Optionally, the electronic device further comprises an I / O interface for data exchange between the electronic device and external devices. The I / O interface can be one or more of several types of bus structures, including memory bus or memory controller, peripheral bus, graphics acceleration port, processing unit, or local bus using any of the bus structures.

[0183] It should be understood that Figure 5 The electronic device shown is only an example of the present application, and the electronic device of the present application can also include elements or components not shown in the above examples. For example, some electronic devices also include display units such as display screens, and some electronic devices also include human-computer interaction elements such as buttons and keyboards. As long as the electronic device can execute the computer readable programs in the memory to implement the method of the present application or at least some steps of the method, it can be considered as an electronic device covered by the present application.

[0184] From the above description of the embodiments, those skilled in the art can easily understand that the example embodiments described herein can be implemented by software, or by software combined with necessary hardware. Therefore, as long as the embodiments of the present application are not affected, the specific operating methods of the software and hardware can be modified by those skilled in the art. Figure 6 As shown, the technical solution according to the embodiments of the present application 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 U disk, a mobile hard disk, etc.) or on a network, and includes a number of commands to make a computing device (which can be a personal computer, a server, or a network device, etc.) execute the above method according to the embodiments of the present application.

[0185] The software product can employ any combination of one or more readable media. The readable media can be a readable signal medium or a readable storage medium. The readable storage medium, for example, can be, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable 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 disc, 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.

[0186] The computer readable storage medium can include a data signal transported over a carrier wave and can be baseband or propagated along with carriers. The propagated carrier can take any suitable form, including but not limited to electro-magnetic, optical, or any suitable combination thereof. A computer readable storage medium can be any medium (tangible or non-tangible) that can store data for use by or in connection with the computer system or device. The program code embodied on the computer readable storage medium can be transmitted using any carrier wave appropriate to the communication context, including but not limited to wireless, wire line, optical, radio frequency (RF), or any suitable combination thereof.

[0187] The program code can be executed by one or more programmable processors, which can be implemented as one or more microprocessors, microcontrollers, digital signal processors, application specific integrated circuits, field programmable gate arrays, processors of embedded systems, or the like. The program code can be downloaded from an external source, such as a website, via a network, such as the Internet, or via any other external source. The program code can be downloaded via a wired medium or a wireless medium. The program code can be downloaded from a removable storage medium, such as a CD-ROM, a DVD, a memory stick, or the like.

[0188] The computer readable medium described above can bear one or more programs, which, when executed by the device, cause the computer readable medium to implement the data interaction method of the present disclosure.

[0189] 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, and can also be changed in one or more devices different from the embodiments. The modules of the above-mentioned embodiments can be combined into one module, or can be further split into a plurality of sub-modules.

[0190] Through the above description of the embodiments, those skilled in the art can easily understand that the example embodiments described herein can be implemented by software, or by software combined with necessary hardware. Therefore, the technical solutions according to the embodiments of the present application 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 U disk, a mobile hard disk, etc.) or a network, and includes a plurality of commands to make a computing device (which can be a personal computer, a server, a mobile terminal, or a network device, etc.) execute the method according to the embodiments of the present application.

[0191] It should be noted that the above detailed description is exemplary and is intended to provide further explanation of the present application. Unless otherwise specified, all technical and scientific terms used herein have the same meaning as understood by those skilled in the art to which the present application belongs.

[0192] In the above detailed description, reference is made to the accompanying drawings, which form a part hereof. In the drawings, similar symbols typically identify similar components, unless context dictates otherwise. The illustrative embodiments described in the detailed description, drawings, and claims are not meant to be limiting. Other embodiments can be used, and other changes can be made, without departing from the spirit or scope of the subject matter presented herein.

[0193] The above only describes the preferred embodiments of the present application and is not intended to limit the present application. For those skilled in the art, the present application can have various modifications and changes. Any modification, equivalent replacement, improvement, etc. made within the spirit and principles of the present application shall be included in the protection scope of the present application.

Claims

1. A method for constructing and optimizing a system network activity model, characterized in that, The method for constructing and optimizing the network activity model of the system includes: Based on the functional dimension, various nodes of the target task are extracted 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 abstracted into the following nodes according to their functions: situational awareness node, decision support node, action control node, and information service node. Based on the target activity process node model, multiple information links are identified. Through the mapping and orderly combination of the target activities and information links, an activity procedure chain representing activity effectiveness is formed, including: The activity process nodes are categorized and combined to form the following information links to construct an information link model: situational awareness information link, decision support information link, action control information link, and information service information link; the situational awareness information link contains at least three activity process nodes, and the situational awareness information link contains target parameters and status, and generates situational awareness information that can be sent 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. 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. Based on the established information links, a situational chain, a decision-making chain, and an execution chain are further formed; based on the constructed target activity process node model and multiple information links, a system network activity model is constructed; based on the activity process node model and information link model, activity process name, identifier, and target, an activity process model is constructed, and the activity process model is defined as a quintuple; Based on the activity process nodes and the constraints that the execution endpoint is the corresponding node or action control node, determine the information link combination method. Selecting activity process nodes in different information links to combine functions, so that multiple information links of various types form an intricate tree-like semi-closed network or closed network, and finally forming an activity program chain corresponding to the target task; The fuzzy comprehensive evaluation method is used to evaluate the effectiveness of the constructed system network activity model and determine whether the task activities in the target task meet the task requirements. Specifically, it includes: establishing an evaluation matrix based on the indicators to be evaluated and calculating the weight of each indicator in the system to be evaluated; using the calculated weights and the single-factor evaluation matrix, fuzzy synthesis operation is performed to obtain the comprehensive evaluation result.

2. The method for constructing and optimizing a system network activity model according to claim 1, characterized in that, The effectiveness evaluation of the constructed system network activity model using the fuzzy comprehensive evaluation method includes: The weight of each indicator to be evaluated in the system to be evaluated is calculated to form a corresponding evaluation matrix, and a consistent calculation is performed on each indicator to evaluate the effectiveness of the activity. Fuzzy comprehensive evaluation is performed to obtain fuzzy comprehensive assessment results. Histograms are then drawn to visually identify the evaluation indicators to be optimized, which are then used to optimize the next round of the system network activity model. This process of optimizing the system network activity model continues for multiple rounds until the task requirements are met.

3. The method for constructing and optimizing a system network activity model according to claim 2, characterized in that, include: The weighted average method is used to calculate the evaluation value of the indicator to be evaluated in the activity task using the following expression, in order to evaluate the overall evaluation results: Where μ represents the evaluation value of the indicator to be evaluated in the activity task; b i Let be the i-th evaluation element in the comprehensive evaluation matrix, where i is a positive integer; v is the quantitative result of the rating level obtained by evaluating or processing each indicator to be evaluated: v = [0.9, 0.7, 0.5, 0.3, 0.1], and k is an undetermined coefficient, specifically in the range of 0.8 to 3.0, with the aim of controlling for larger values ​​of b. i The role played in the activity tasks.

4. The method for constructing and optimizing a system network activity model according to claim 3, characterized in that, include: The threshold value S, determined based on the nature of the activity task, is in the range of 60 to 80. When the calculated evaluation value μ 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. When the calculated evaluation value μ 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. Furthermore, for each evaluation indicator that fails to meet the task requirements, the relevant attributes of the corresponding nodes in the system network activity model are identified, the attribute values ​​corresponding to each evaluation indicator are adjusted, and the system network activity model is re-evaluated until all evaluation indicators are greater than the corresponding set thresholds, so that all evaluation indicators involved in the activities of the target task meet the task requirements.

5. The method for constructing and optimizing a system network activity model according to claim 2, characterized in that, Further includes: The following expression is used to calculate the consistency index of each evaluation matrix corresponding to the evaluation indicators of different target tasks, in order to perform consistency verification: Among them, CI 当前 The consistency index represents the current evaluation matrix P; n is the number of evaluation factors at the same level. Different target tasks correspond to different evaluation levels and different numbers of evaluation factors. n is a positive integer. λ max It is the largest eigenvalue of the current evaluation matrix.

6. The method for constructing and optimizing a system network activity model according to claim 5, characterized in that, include: When performing a consistency check, it is first necessary to multiply the evaluation elements row by row, and then take the nth root. After normalization, we get W i The following expression is used to calculate and determine the largest eigenvalue λ of the current evaluation matrix. max : in, This represents the root value obtained by multiplying the evaluation elements by rows and then taking the nth root; W i λ represents the weight value obtained by normalizing the i-th root value; max The largest eigenvalue of the current evaluation matrix R is r, where the current evaluation matrix R includes matrix terms formed by quantifying multiple evaluation elements, i.e., evaluation elements. ij This represents the evaluation element, or matrix item, in the i-th row and j-th column of the current evaluation matrix R. i represents the i-th row of the current evaluation matrix R, and j represents the j-th column of the current evaluation matrix R. i and j are both positive integers, specifically 1, 2, ..., n. This represents the k-th root value; k represents the number of root values, which is a positive integer, specifically 1, 2, ..., n; R×W is the product of the current evaluation matrix R and the weight vector W, where (R×W) i Let W represent the i-th evaluation element after multiplication, where W is the product of W. i The vector formed; Calculate the consistency ratio (CR) to verify the consistency of the evaluation matrices: Among them, CI represents the consistency index of each evaluation matrix, including the current evaluation matrix; RI represents the average consistency index of the judgment matrix generated within a specified historical period based on different target tasks, evaluation indicators, the number of evaluation factors, and the matrix order.

7. A system for constructing and optimizing a network activity model, characterized in that, The system implements the network activity model construction and optimization method according to any one of claims 1 to 6, wherein the network activity model construction and optimization system comprises: The first construction module extracts various nodes of the target task based on the functional 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 abstracted into the following nodes according to their functions: situational awareness node, auxiliary decision-making node, action control node, and information service node. The first determining module identifies multiple information links based on the target activity process node model, and forms an activity procedure chain that characterizes the activity effectiveness based on the mapping and orderly combination from the target activity to the information links. The second construction module constructs a system network activity model based on the constructed target activity process node model and multi-information links. The evaluation and optimization module is used to evaluate the effectiveness of the constructed system network activity model using the fuzzy comprehensive evaluation method, and to determine whether the task activities in the target task meet the task requirements. Specifically, it includes: establishing an evaluation matrix based on the indicators to be evaluated, and calculating and determining the weight of each indicator to be evaluated in the system to be evaluated; using the calculated weights and the single-factor evaluation matrix, performing fuzzy synthesis operation to obtain the comprehensive evaluation result.

8. The system for constructing and optimizing a network activity model according to claim 7, characterized in that, include: The activity process nodes are categorized and combined to form the following information links: situational awareness information link, decision support information link, action control information link, and information service information link; the situational awareness information link contains at least three activity process nodes, and the situational awareness information link contains target parameters and status, and can be sent to all activity process nodes by generating situational awareness information. 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 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. Based on the established information links, further develop situational chains, decision-making chains, and execution chains.

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