CN112884289B - Weapon equipment combination selection method and system based on system contribution rate - Google Patents

Weapon equipment combination selection method and system based on system contribution rate Download PDF

Info

Publication number
CN112884289B
CN112884289B CN202110099990.9A CN202110099990A CN112884289B CN 112884289 B CN112884289 B CN 112884289B CN 202110099990 A CN202110099990 A CN 202110099990A CN 112884289 B CN112884289 B CN 112884289B
Authority
CN
China
Prior art keywords
combat
weapon equipment
capability
weapon
equipment
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Active
Application number
CN202110099990.9A
Other languages
Chinese (zh)
Other versions
CN112884289A (en
Inventor
刘鹏
李际超
杨从林
杨克巍
姜江
杨志伟
葛冰峰
夏博远
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
National University of Defense Technology
Original Assignee
National University of Defense Technology
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by National University of Defense Technology filed Critical National University of Defense Technology
Priority to CN202110099990.9A priority Critical patent/CN112884289B/en
Publication of CN112884289A publication Critical patent/CN112884289A/en
Application granted granted Critical
Publication of CN112884289B publication Critical patent/CN112884289B/en
Active legal-status Critical Current
Anticipated expiration legal-status Critical

Links

Images

Classifications

    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00—Administration; Management
    • G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
    • G06Q10/067—Enterprise or organisation modelling
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00—Administration; Management
    • G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
    • G06Q10/063—Operations research, analysis or management
    • G06Q10/0631—Resource planning, allocation, distributing or scheduling for enterprises or organisations
    • G06Q10/06311—Scheduling, planning or task assignment for a person or group
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00—Administration; Management
    • G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
    • G06Q10/063—Operations research, analysis or management
    • G06Q10/0639—Performance analysis of employees; Performance analysis of enterprise or organisation operations
    • G06Q10/06393—Score-carding, benchmarking or key performance indicator [KPI] analysis
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
    • Y02P90/00—Enabling technologies with a potential contribution to greenhouse gas [GHG] emissions mitigation
    • Y02P90/30—Computing systems specially adapted for manufacturing

Abstract

The invention discloses a weapon equipment combination selection method and a weapon equipment combination selection system based on a system contribution rate, wherein the weapon equipment combination selection method comprises the following steps: constructing a weapon equipment system combat network model based on the thought of the functional chain; acquiring a combat capability comprehensive index of a combat network based on the thought of a functional chain; acquiring comprehensive combat capability indexes before and after adding the weapon equipment combination into the combat network, and calculating a system contribution rate of the weapon equipment combination based on cost constraint conditions; and constructing a weapon equipment combination selection model according to the preset objective function and the preset constraint condition, and acquiring the objective weapon equipment combination from the combat network through the weapon equipment combination selection model. Based on the system contribution rate of the equipment system combat network and the weapon equipment combination, the weapon equipment combination capable of maximally improving the combat capability of the whole weapon equipment system is found out under the preset constraint condition, the simplicity and reliability of weapon equipment combination selection are improved, and the feasible combination space of the weapon equipment is effectively reduced.

Description

Weapon equipment combination selection method and system based on system contribution rate
Technical Field
The invention belongs to the technical field of weapon equipment systems, and particularly relates to a weapon equipment combination selection method and system based on a system contribution rate.
Background
The system contribution rate is mainly used as an evaluation index for measuring the possible 'functional perfection', 'performance improvement', 'capability gain' or 'efficiency improvement' and the like of a weapon equipment system on the whole weapon equipment combat system, and is mainly used for measuring the change and fluctuation of the function/performance/capability/efficiency generated at the system level due to the addition of the weapon equipment into the combat system, and particularly emphasizing the forward influence, namely contribution, of the weapon equipment.
The current weapon equipment system contribution rate evaluation method comprises two methods: firstly, evaluating system contribution rate of heterogeneous weaponry, and evaluating the heterogeneous contribution rate according to the role of the weaponry in a combat system; and secondly, evaluating the system contribution rate of similar weaponry. For the system contribution rate evaluation method of heterogeneous weaponry, the reconnaissance equipment, the decision-making equipment, the striking equipment and the weapon platform contained in one complete combat unit are considered to be the most important, and the four are compared to obtain a certain weapon equipment or a certain weapon platform, so that the contribution rate is the largest. In fact, as a component of a combat unit, the series collaboration runs to accomplish mission tasks, the contribution rates of these components being the same. The contribution rate evaluation of heterogeneous weapons and equipment can be based on machine deep learning analysis by combining artificial intelligence technology with combat simulation, but at present, some technical difficulties still exist. Therefore, in the current system contribution rate evaluation method of heterogeneous weapons, although the weapons are put in the whole weapons system to evaluate the contribution, the evaluation object is still single weapons, and the joint action among the heterogeneous weapons is ignored, so that the system contribution rate evaluation requirement of taking the heterogeneous weapons as the evaluation object cannot be met.
In addition, the current weapon equipment combination selection method for the weapon equipment system can lead to exponential increase of complexity of combination selection and explosive increase of feasible combination space and large occupied space due to increase of the number of candidate weapon equipment for a large-scale complex weapon equipment combat network system.
Disclosure of Invention
The invention provides a weapon equipment combination selection method and system based on system contribution rate, which are used for solving the problems that the system contribution rate evaluation requirement of heterogeneous weapon equipment combination cannot be met by the existing weapon equipment system contribution rate evaluation method, and the existing weapon equipment combination selection method for a weapon equipment system is large in combination selection complexity and large in feasible combination space for a large-scale complex weapon equipment combat network system.
Based on the above object, in a first aspect, the present invention provides a weapon equipment combination selection method based on a system contribution rate, including:
constructing a weapon equipment system combat network model based on the thought of the functional chain;
acquiring a combat capability comprehensive index of the combat network of the weapon equipment system based on the thought of the functional chain;
acquiring comprehensive combat capability indexes before and after each weapon equipment combination is added into the weapon equipment system combat network, and calculating system contribution rates of each weapon equipment combination based on cost constraint conditions;
And constructing a weapon equipment combination selection model according to a preset objective function and a preset constraint condition, and acquiring an objective weapon equipment combination from the weapon equipment system combat network through the weapon equipment combination selection model.
Preferably, the constructing a weapon equipment system combat network model based on the idea of the functional chain includes:
dividing the weapon equipment entities into reconnaissance type, decision type and striking type equipment entities according to different roles played by each weapon equipment entity in the weapon equipment system in the combat;
acquiring interaction information among the reconnaissance class, the decision class and the hit class equipment entity;
abstracting a reconnaissance class, a decision class and a hit class equipment entity into equipment nodes, abstracting interaction information into edges, and constructing a weapon equipment system combat network;
mathematical descriptions of the weapon equipment architecture network are provided.
Preferably, the acquiring the comprehensive combat capability index of the combat network of the weapon equipment system based on the thought of the functional chain includes:
the functional chain definition is that a reconnaissance class, a decision class and a striking class equipment entity in a weapon equipment system form a link capable of playing a combat capability through interaction in order to complete a specific combat task;
Constructing a capability index system of weapon equipment;
determining a mission task, and acquiring the capability requirement for completing the mission task based on a capability index system of the weapon equipment;
calculating the combat capability of the single functional chain according to the capability requirement for completing the mission task and the existing capability of the weapon equipment corresponding to all the equipment nodes contained in the single functional chain;
and acquiring all the functional chains in the weapon equipment system combat network, and acquiring the combat capability comprehensive index of the weapon equipment system combat network through a combat capability evaluation model matched with the number of the functional chains so as to acquire the combat capability of the weapon equipment system.
Preferably, the calculation formula of the combat capability of the single functional chain is as follows:
E L ＝ΠE S ×ΠE D ×ΠE B ，
wherein E is L For the operational capacity of a single functional chain, E S 、E D And E is B The investigation equipment node, the decision equipment node and the hit equipment node contained in the single functional chain are respectively oriented to the combat capability embodied by the mission task.
Preferably, the acquiring all the functional chains in the weapon equipment system combat network, and acquiring the combat capability comprehensive index of the weapon equipment system combat network through the combat capability assessment model matched with the number of the functional chains, includes:
Acquiring all the functional chains in the weapon equipment system combat network, and detecting whether the number of the functional chains is smaller than a preset threshold;
when the number of functional chains is smaller than a preset threshold, a combat capability comprehensive index of the combat network of the weapon equipment system is obtained through a first combat capability evaluation model, wherein the first combat capability evaluation model is as follows:
Figure BDA0002915472880000031
wherein E is the comprehensive index of the combat capability of the combat network of the weapon equipment system,
Figure BDA0002915472880000038
the operational capacity of the ith functional chain is obtained, and m is the number of the functional chains;
when the number of the functional chains is larger than or equal to a preset threshold value, the combat capability comprehensive index of the combat network of the weapon equipment system is obtained through a second combat capability evaluation model, wherein the second combat capability evaluation model is as follows:
Figure BDA0002915472880000032
preferably, the calculation formula of the system contribution rate is as follows:
Figure BDA0002915472880000033
wherein,
Figure BDA0002915472880000039
combination V for weapon equipment x System contribution rate of->
Figure BDA00029154728800000310
To add the weapon equipment combination V x Combat capability comprehensive index of weapon equipment system combat network facing mission, E S For not adding the weapon equipment combination V x Is based on the comprehensive combat capability index, cost (V x ) Combining V for said weapon equipment x Cost of->
Figure BDA0002915472880000034
The total cost of all the weaponry in the network is the weaponry hierarchy.
Preferably, the preset objective function is:
Figure BDA00029154728800000311
wherein argmax () is a function for optimizing the problem;
the preset constraint conditions comprise cost budget constraint and capacity requirement constraint.
Preferably, the set of possible combinations of weapons obtained from the cost budget constraint is:
Figure BDA0002915472880000035
wherein,
Figure BDA0002915472880000036
for a combined set of possible weaponry, C (V x ) Combining V for said weapon equipment x B is a budget limit;
the set of possible weapon equipment combinations obtained according to the capacity requirement constraint is:
Figure BDA0002915472880000037
wherein CA k (V x ) Combining V for said weapon equipment x The kth capacity level, N k Is the kth capability requirement.
In a second aspect, the present invention provides a weapon equipment combination selection system based on a system contribution rate, comprising:
the network construction module is used for constructing a weapon equipment system combat network model based on the thought of the functional chain;
the capability assessment module is used for acquiring a combat capability comprehensive index of the combat network of the weapon equipment system based on the thought of the functional chain;
the contribution rate evaluation module is used for acquiring the comprehensive combat capability indexes before and after each weapon equipment combination joins the combat network of the weapon equipment system, and calculating the system contribution rate of each weapon equipment combination based on the cost constraint condition;
And the combination selection module is used for constructing a weapon equipment combination selection model according to a preset target function and a preset constraint condition, and acquiring a target weapon equipment combination from the weapon equipment system combat network through the weapon equipment combination selection model.
Preferably, the capability assessment module comprises:
the functional chain definition unit is used for defining functional chains, wherein the functional chains are defined as links capable of playing the combat capability through interaction among detection class, decision class and hit class equipment entities in the weapon equipment system for completing specific combat tasks;
the index system construction unit is used for constructing a capability index system of the weapon equipment;
the requirement determining unit is used for determining a mission task and acquiring the capability requirement for completing the mission task based on the capability index system of the weapon equipment;
the function chain capability assessment unit is used for calculating the combat capability of the single function chain according to the capability requirement for completing the mission task and the existing capability of the weapon equipment corresponding to all the equipment nodes contained in the single function chain;
the comprehensive capability evaluation unit is used for acquiring all the functional chains in the weapon equipment system combat network, and acquiring the combat capability comprehensive index of the weapon equipment system combat network through the combat capability evaluation model matched with the number of the functional chains so as to acquire the combat capability of the weapon equipment system.
According to the weapon equipment combination selection method and system based on the system contribution rate, firstly, an equipment system combat network is built based on the thought of a functional chain, secondly, combat capability comprehensive indexes of the weapon equipment system combat network are obtained based on the thought of the functional chain, the capability contribution rate of weapon equipment combination to the weapon equipment system is calculated based on the combat capability comprehensive indexes, and finally, a weapon equipment combination selection model is built under preset constraint conditions and preset objective functions, so that target weapon equipment combination is obtained. Compared with the existing system contribution rate evaluation method of the weaponry, the system contribution rate evaluation method provided by the invention can meet the system contribution rate evaluation requirement of heterogeneous weaponry combinations by calculating the comprehensive combat capability change situation of the weaponry combinations added into the old weaponry system combat network and calculating the system contribution rate of the weaponry combinations by considering the equipment cost factors. Secondly, compared with the existing weapon equipment combination selection method for the weapon equipment system, the weapon equipment combination selection method based on the system contribution rate provided by the invention finds the weapon equipment combination which maximally improves the fight capability of the whole weapon equipment system under the preset constraint condition based on the system contribution rate of the equipment system fight network and the weapon equipment combination, improves the simplicity and reliability of weapon equipment combination selection, and effectively reduces the feasible combination space of the weapon equipment.
Drawings
In order to more clearly illustrate the embodiments of the invention or the technical solutions in the prior art, the drawings that are required in the embodiments or the description of the prior art will be briefly described, it being obvious that the drawings in the following description are only some embodiments of the invention, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a flowchart of a method for selecting a combination of weapons based on a system contribution rate according to one embodiment of the present invention;
FIG. 2 is a second flowchart of a method for selecting a combination of weapons based on a system contribution rate according to one embodiment of the present invention;
FIG. 3 is a flowchart III of a method for selecting a combination of weapons based on a system contribution rate according to one embodiment of the present invention;
FIG. 4 is a schematic diagram of a network of weapon equipment architecture operations provided in an embodiment of the present invention;
FIG. 5 is a schematic diagram of a weapon equipment combination selection system based on system contribution rate according to an embodiment of the present invention;
fig. 6 is a schematic structural diagram of a weapon equipment combination selection system based on a system contribution rate according to an embodiment of the present invention.
Detailed Description
In order that those skilled in the art will better understand the present invention, a technical solution in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in which it is apparent that the described embodiments are only some embodiments of the present invention, not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the present invention without making any inventive effort, shall fall within the scope of the present invention.
It should be noted that the terms "first," "second," and the like in the description and the claims of the present invention and the above figures are used for distinguishing between similar objects and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used may be interchanged where appropriate such that the embodiments of the invention described herein may be implemented in sequences other than those illustrated or otherwise described herein. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.
As shown in fig. 1, an embodiment of the present invention provides a weapon equipment combination selection method based on a system contribution rate, which includes:
and step S10, constructing a weapon equipment system combat network model based on the thought of the functional chain.
The functional chain is that each weapon entity (W) in the weapon equipment system interacts to form a link capable of exerting certain combat capability in order to complete specific combat tasks. Based on the different roles each weapon equipment entity plays in the combat, the weapon equipment entity (W) can be divided into a scout class equipment entity (S), a decision class equipment entity (D) and a hit class equipment entity (B). The entity (S) of the reconnaissance equipment refers to weapon equipment which utilizes sensors to collect target and battlefield information, and the main functions are target reconnaissance, information acquisition and battlefield monitoring. The decision-making equipment entity (D) is weapon equipment with information processing and analysis, auxiliary decision making and command control function on interference equipment. The striking equipment entity (B) is weapon equipment which mainly performs fight and damage actions and has the functions of accurate striking, fire damage, electronic interference and the like.
It can be understood that in the functional chain and the combat ring, the equipment nodes corresponding to the weapon equipment entities (W) can realize cooperative combat through an information network, so that a hard hinge among the traditional combat platform, the sensors and the weapon equipment entities can be broken, a complete chain of detection-decision-hitting is constructed in a loose coupling mode, and cooperative combat among the equipment is realized. Network modeling analysis of a weapon equipment system based on the ideas of functional chains or operational loops is an expansion of the ideas of the Boyder loop (OODA cycle). The combat loop is a closed loop formed by equipment entities such as reconnaissance, decision-making, striking and the like and enemy targets in a weapon equipment system in order to complete a specific combat task.
Preferably, as shown in fig. 2, the step S10 specifically includes the following steps:
step S101, dividing the weaponry entities into reconnaissance (S), decision (D) and hit (B) weaponry entities according to different roles played by each weaponry entity in the weaponry system in the combat.
Step S102, interaction information among the reconnaissance class (S), the decision class (D) and the hit class (B) equipment entities is obtained.
Step S103, abstracting equipment entities of the reconnaissance class (S), the decision class (D) and the hit class (B) into equipment nodes, abstracting interaction information into sides, and constructing a weapon equipment system combat network.
Step S104, carrying out mathematical description on the weapon equipment system combat network.
In step S104, the weapon equipment hierarchy combat network may be abstracted as a complex network, which may be denoted as g= (V, E), where v=sjd j i= { V 1 ,v 2 ,…,v |V| E= { E } is a set containing all equipment nodes 1 ,e 2 ,…,e |E| And is a set containing all edges.
Figure BDA0002915472880000061
To contain a set of all scout class equipped nodes,
Figure BDA0002915472880000062
equipping a set of nodes for all decision classes>
Figure BDA0002915472880000063
The set of points is equipped to contain all the shock knots.
It should be noted that, based on the definition of the functional chain, each weapon equipment entity in the weapon equipment system does not need to form a closed loop with the enemy object, so that the above embodiment does not need to consider the enemy equipment entity when constructing the equipment system combat network model.
The network modeling description is carried out on the weapon equipment system based on the idea of the functional chain, the association relation among various weapon equipment in the weapon equipment system and the heterogeneity of the weapon equipment types can be fully considered, and a foundation is provided for weapon equipment contribution rate evaluation and weapon equipment combination selection.
Step S20, acquiring the comprehensive combat capability index of the combat network of the weapon equipment system based on the thought of the functional chain.
The combat capability comprehensive index is used for measuring combat capability embodied by a weapon equipment system facing mission tasks. Step S20 is based on the functional chain, wherein the weapon equipment system combat capability assessment is a basis of the system contribution rate assessment, and the object of assessment is the weapon equipment system, which is a theoretical value assessment of the capability of the weapon equipment system in static and non-countermeasure scenes.
It is understood that the definition of the functional chain and the fight ring shows that the functional chain comprises the fight ring, and the functional chain is an expansion of the fight ring and is wider and more comprehensive than the fight ring. In addition, in the weapon equipment system combat capability assessment, the functional chain is the only link for connecting the equipment self capability assessment, the equipment interrelated collaborative capability level assessment and the combat task completion capability assessment. Therefore, the weapon equipment system combat capability assessment method based on the functional chain is a new thought for weapon equipment system combat capability assessment.
Preferably, as shown in fig. 3, the step S20 specifically includes the following steps:
in step S201, a functional chain is defined, where the functional chain is defined as a link capable of playing a battle capability by interaction between the scout class, decision class and hit class equipment entities in the weapon equipment system in order to complete a specific battle task.
Step S202, constructing a capability index system of the weapon equipment.
The capability index system comprises a plurality of (two or more) primary capability indexes, and each primary capability index comprises a plurality of secondary capability indexes. In this embodiment, the capability index system includes three primary capability indexes, which are reconnaissance capability, decision capability, and striking capability, respectively. The reconnaissance capability refers to the capability of acquiring, transmitting, processing and effectively utilizing various types of information through various approaches, and includes, but is not limited to, intelligence reconnaissance capability, information transmission capability, information processing capability and information sharing capability. Decision making capability refers to the capability of helping decision making equipment to complete activities such as situation awareness, combat deployment, implementation effect assessment and the like in combat processes, and includes, but is not limited to, auxiliary decision making capability, comprehensive control coordination capability and fire coordination support capability. The striking capability refers to the capability of striking a set enemy by using various fight means to lose the fight capability of the enemy, and the striking capability includes but is not limited to fire damage capability, electronic interference capability and accurate striking capability.
Step S203, determining a mission task, and acquiring a capability requirement for completing the mission task based on a capability index system of the weapon equipment.
Preferably, after determining a future mission task, on the one hand, the specific capability requirement for completing the mission task is obtained through expert experience evaluation, on the other hand, a specific task list is obtained through decomposition, and the specific capability requirement for completing the mission task is obtained based on the mapping relation between the task list and the capability. It is understood that the capability index system is the basis for determining the specific capability requirements to complete a mission.
In step S203, the capability requirement for completing the mission task includes a scout capability requirement
Figure BDA0002915472880000073
Decision capability requirement
Figure BDA0002915472880000074
And the need for striking ability->
Figure BDA0002915472880000075
And scout ability requirement->
Figure BDA0002915472880000076
Decision capability requirement->
Figure BDA0002915472880000077
And the need for striking ability->
Figure BDA0002915472880000078
May contain multiple sub-capability requirements.
Step S204, calculating the combat capability of the single functional chain according to the capability requirement for completing the mission task and the existing capability of the weapon equipment corresponding to all the equipment nodes contained in the single functional chain.
Based on the idea of the functional chain, when the detection type equipment completes detection and early warning of an enemy target, information is transmitted to the decision type equipment, the decision type equipment processes the information and transmits a decision command to the striking type equipment, the striking type equipment destroys the enemy target by utilizing the striking capability of the striking type equipment, and each weapon equipment can be considered to exert the fight capability of the weapon equipment only when the process of the whole functional chain is successfully completed. Therefore, in step S204, the calculation formula of the combat capability of the single function chain is specifically expressed as:
E L ＝∏E S ×ΠE D ×ΠE B (1)
In the formula (1), E L For the operational capacity of a single functional chain, E S 、E D And E is B The investigation equipment node, the decision equipment node and the hit equipment node contained in the single functional chain are respectively oriented to the combat capability embodied by the mission task.
Wherein, the scout equipment node faces to the combat capability E embodied by the mission task S The calculation formula of (2) is specifically expressed as:
Figure BDA0002915472880000071
in the formula (2), C S To detect the reconnaissance capability of the reconnaissance equipment corresponding to the reconnaissance equipment node,
Figure BDA0002915472880000072
and F ()' is a capability satisfaction function for the scout capability requirement of the scout equipment facing the mission task corresponding to the scout equipment node. Optionally, for each weapon equipment in the weapon equipment system, the corresponding capability is provided according to a system module or a functional module of the weapon equipment.
Decision-making equipment node oriented mission task embodied combat capability E D The calculation formula of (2) is specifically expressed as:
Figure BDA0002915472880000081
in the formula (3), C D Decision-making capability of decision-making equipment corresponding to the decision-making equipment node,
Figure BDA0002915472880000082
decision-making capability requirements for mission-oriented tasks of the scout class equipment corresponding to the scout class equipment nodes.
Battle ability E embodied by battle equipment node for mission-oriented task B The calculation formula of (2) is specifically expressed as:
Figure BDA0002915472880000083
In the formula (4), C B To hit the hit capability of the hit class device corresponding to the hit class device node,
Figure BDA0002915472880000084
the hit capability requirement of the hit task facing to the hit class equipment is provided for the hit class equipment node.
The calculation formula of the capability satisfaction function f () is specifically expressed as:
Figure BDA0002915472880000085
in the formula (5), a is the existing capability of the weapon equipment, and b is the capability requirement of the weapon equipment for mission-oriented tasks. The capability satisfaction function indicates that as the capability index of the weapon equipment is increased, the combat capability of the weapon equipment for a specific task is increased, but the increasing trend is slow. When the capability index of the weapon equipment reaches a higher level, even if the capability index is reinforced again, the capability index cannot play a larger role for a specific combat task.
With functional chain L 1 For example, the node of the equipment including reconnaissance class, decision class and hit class is described as the task M for completing the future mission 1 Assume that the 2 sub-capability requirements of the scout capability are respectively
Figure BDA0002915472880000086
And->
Figure BDA0002915472880000087
The 2 sub-capability requirements of decision capability are respectively +.>
Figure BDA0002915472880000088
And->
Figure BDA0002915472880000089
The 2 sub-capacity demands for percussion capacity are +.>
Figure BDA00029154728800000810
And->
Figure BDA00029154728800000811
And assume that the scout equipment V corresponds to the scout equipment node 1 Is +.>
Figure BDA00029154728800000812
And->
Figure BDA00029154728800000813
Decision device V corresponding to decision class equipment node 2 Is +.>
Figure BDA00029154728800000814
And
Figure BDA00029154728800000815
striking equipment V corresponding to striking equipment node 3 Is +.>
Figure BDA00029154728800000816
And->
Figure BDA00029154728800000817
Then the functional chain L 1 Mission-oriented task M 1 The operational capabilities embodied may be expressed as:
Figure BDA00029154728800000818
Figure BDA00029154728800000819
step S204, all functional chains in the weapon equipment system combat network are obtained, and the combat capability comprehensive index of the weapon equipment system combat network is obtained through the combat capability assessment model matched with the number of the functional chains, so that the combat capability of the weapon equipment system is obtained.
Specifically, a function chain set L= { L is obtained according to all function chain combinations in a weapon equipment system combat network i I=1, 2, …, m, where m is the number of all functional chains in the network of the weapon equipment system, detecting if the number of functional chains m is less than a preset threshold T m When the number m of the functional chains is smaller than the preset threshold T m And obtaining the combat competence of the weapon equipment system through the first combat competence assessment model. Preferably, the first operational capability assessment model is expressed specifically as:
Figure BDA0002915472880000091
in the formula (7), E is the comprehensive combat capability index of the combat network of the weapon equipment system,
Figure BDA0002915472880000092
for the functional chain set l= { L i The combat capability of the ith functional chain in i=1, 2, …, m }. It can be understood that, as shown in the formula (7), the first operational capability evaluation model is suitable for parallel relation calculation of a small number of functional chains, and in the case of a large functional chain scale, the first operational capability evaluation model is shown in the formula (7)
Figure BDA0002915472880000093
The value of the (c) will tend to zero, and the value of the combat ability E after adding the weapon equipment system to each new equipment combination is close to 1, so that the aim of sorting cannot be achieved. Thus when the number of functional chains m is greater than or equal to the preset threshold T m Obtaining weapon equipment through a second combat competence assessment modelCapacity of the backup system. Preferably, the second combat capability evaluation model is expressed specifically as:
Figure BDA0002915472880000094
that is, 1-E in the formula (7) Li The resistance of each functional chain is considered, and the combat capability after a plurality of functional chains are connected in parallel is shown in a formula (8).
It will be appreciated that in other embodiments, the second operational capability assessment model is directly employed to calculate the operational capability composite index of the weapon equipment system operational network without comparing the number of functional chains to a preset threshold.
It should be noted that, in the weapon equipment system combat capability evaluation process, the foothold of the system combat capability evaluation is faced with future equipment development planning, and the requirement capability constraint based on future mission tasks is considered, so that the specific target defensive capability of the enemy can not be considered in the system combat capability evaluation process.
In the above embodiment, based on the complex network idea, the system capability is aggregated by providing the combat capability evaluation index, i.e. the combat capability comprehensive index, of the weapon equipment system based on the functional chain, and the idea of adopting the functional chain is adopted, so that the method can be applied to the analysis of the weapon equipment system capability in the weapon equipment use stage, and can also be applied to the situation that only capability requirements are needed in the equipment development planning stage without defining target equipment.
Step S30, obtaining comprehensive combat capability indexes before and after each weapon equipment combination joins the combat network of the weapon equipment system, and calculating the system contribution rate of each weapon equipment combination based on cost constraint conditions.
The calculation formula of the system contribution rate is as follows:
Figure BDA0002915472880000101
formula (VI)(9) In the process,
Figure BDA0002915472880000102
combination V for weapon equipment x System contribution rate of->
Figure BDA0002915472880000103
To add weapon equipment combination V x Combat capability comprehensive index of weapon equipment system combat network facing mission, E S For not adding weapon equipment combination V x Is based on the comprehensive combat capability index, cost (V x ) Combination V for weapon equipment x Cost of->
Figure BDA0002915472880000104
The total cost of all the weaponry in the network is the weaponry hierarchy. The numerator part of the formula (9) is a traditional system contribution rate calculation formula, and the denominator part is the cost ratio of the added weapon equipment combination relative to all the weapon equipment of the whole weapon equipment system.
It can be understood that, first, the comprehensive combat capability index E of the old weapon equipment system combat network is obtained by the weapon equipment system combat capability evaluation method based on the functional chain in step S20 S Namely, the fight capability of the weapon equipment system fight network which is not added with the weapon equipment combination is embodied in the mission-oriented task, then a new weapon equipment combination is added into the weapon equipment system, and the weapon equipment system fight network which is added with the new weapon equipment combination is reconstructed to obtain a new weapon equipment system fight network, such as the weapon equipment system fight network shown in fig. 4, wherein the newly added weapons are provided with 4 weapons, and the original weapons are provided with 6 weapons. Finally, obtaining the comprehensive combat capability index of the new weapon equipment system combat network by the weapon equipment system combat capability assessment method based on the functional chain in the step S20
Figure BDA0002915472880000105
And calculating by a system contribution rate calculation formula based on cost constraint conditionsThe contribution rate of the added weapon equipment combination to the weapon equipment system.
In this embodiment, when analyzing the contribution rate of the weapon equipment combination in the weapon equipment system, by analyzing the contribution effect of the weapon equipment combination to be developed on the weapon equipment system under the investment of the same cost, the method is more suitable for the weapon equipment development planning compared with the system contribution rate calculation method without considering the cost factors.
And S40, constructing a weapon equipment combination selection model according to a preset objective function and a preset constraint condition, and acquiring an objective weapon equipment combination from a weapon equipment system combat network through the weapon equipment combination selection model.
In this embodiment, after the system contribution rate of the weapon equipment combination is calculated on the basis of the weapon equipment system combat network, analysis and optimization are required to be performed on the combination selection of the weapon equipment system under the system vision by putting the weapon equipment system into the system vision, that is, the weapon equipment combination with the maximum contribution rate for improving the combat capability of the whole weapon equipment system is found out from the whole weapon equipment system, so as to be used as the target weapon equipment combination for development planning, and the combat capability of the future weapon equipment system is maximized.
The preset objective function specifically represents:
Figure BDA0002915472880000111
in the formula (10) of the present invention,
Figure BDA0002915472880000112
combination V for weapon equipment x The system contribution rate to the weapon equipment system combat network combat capability, argmax () is a function for optimizing the problem.
It can be appreciated that for a viable weapon equipment combination set
Figure BDA0002915472880000113
Limited by various constraints, such as availability of resources, cost budget, capacity demand category and technology maturityEtc. In this embodiment, the preset constraint conditions are set as a cost budget constraint and a capacity demand constraint.
For a cost budget constraint, when the cost of a combination of weapons does not exceed a budget limit, determining that the combination of weapons is a viable combination of weapons, and thus the set of viable combinations of weapons that are available based on the cost budget constraint can be expressed as:
Figure BDA0002915472880000114
in the formula (11), C (V x ) Combination V for weapon equipment x B is the budget limit.
For the capability requirement constraint, when a weapon equipment combination meets the capability requirement in k, determining that the weapon equipment combination is a viable weapon equipment combination, and thus the set of viable weapon equipment combinations available based on the capability requirement constraint can be expressed as:
Figure BDA0002915472880000115
in the formula (12), CA k (V x ) Combination V for weapon equipment x The kth capacity level, N k Is the kth capability requirement.
In this embodiment, a set of possible combinations of weapons is first obtained from all combinations of weapons using preset constraints (including cost budget constraints and capacity requirement constraints)
Figure BDA0002915472880000116
Then use the objective function from the set of possible weapon equipment combinations +.>
Figure BDA0002915472880000117
And acquiring the weapon equipment combination with the maximum system contribution rate to the combat network combat capability of the weapon equipment system. It can be appreciated that when a plurality of weapon equipment are combined, the system tribute of the capability of the weapon equipment system to fight the network is provided When the effect of improving the donation rate is consistent, the target weapon equipment can be used as a target weapon equipment combination at the same time. .
In summary, according to the weapon equipment combination selection method based on the system contribution rate of the embodiment, firstly, an equipment system combat network is constructed based on the idea of the functional chain, secondly, combat capability comprehensive indexes of the weapon equipment system combat network are obtained based on the idea of the functional chain, capability contribution rates of weapon equipment combinations to the weapon equipment system are calculated based on the combat capability comprehensive indexes, and finally, a weapon equipment combination selection model is constructed on preset constraint conditions and preset objective functions, so that target weapon equipment combinations are obtained. Compared with the existing system contribution rate evaluation method of the weaponry, the system contribution rate evaluation method provided by the embodiment can meet the system contribution rate evaluation requirement of heterogeneous weaponry combinations by calculating the comprehensive combat capability change situation of adding the weaponry combinations into the old weaponry system combat network and calculating the system contribution rate of the weaponry combinations by considering the equipment cost factors. Secondly, compared with the existing weapon equipment combination selection method for the weapon equipment system, the weapon equipment combination selection method based on the system contribution rate of the embodiment finds the weapon equipment combination which maximally improves the fight capability of the whole weapon equipment system under the preset constraint condition based on the system contribution rate of the equipment system fight network and the weapon equipment combination, improves the simplicity and the reliability of weapon equipment combination selection, and effectively reduces the feasible combination space of the weapon equipment.
In other embodiments, during the selection process of the weapon equipment combination, firstly, the capability value of each weapon equipment to be developed for a mission task is calculated, and each group of weapon equipment combination obtained by combination is screened by utilizing a preset constraint condition to obtain a weapon equipment combination (namely a feasible weapon equipment combination) meeting the constraint condition, so that the problem that the data volume is increased due to the addition of an infeasible weapon equipment combination, and the calculation efficiency is reduced can be avoided; and then calculating the combat capability of the feasible weapon equipment combination added into the combat network of the old weapon equipment system respectively, namely calculating the combat capability of each functional chain respectively by using a calculation formula (1) of the combat capability of the single functional chain, and calculating the combat capability comprehensive index of the combat network of the weapon equipment system by using a calculation formula (8) of the second combat capability evaluation model. And finally, calculating the influence of the feasible weapon equipment combination on the fight capability of the weapon equipment system when facing the mission task according to a calculation formula (9) of the system contribution rate, namely, the change degree of the fight capability of the weapon equipment system under the condition of the feasible weapon equipment combination, and sequencing and fetching the preset number of weapon equipment combinations according to the system contribution rate.
In addition, as shown in fig. 5, the implementation of the present invention further provides a weapon equipment combination selection system based on a system contribution rate, and the system specifically includes a network construction module 110, a capability assessment module 120, a contribution rate assessment module 130 and a combination selection module 140, where the detailed descriptions of the functional modules are as follows:
the network construction module 110 is configured to construct a weapon equipment system combat network model based on the idea of the functional chain.
The capability assessment module 120 is configured to obtain a comprehensive combat capability index of the combat network of the weapon equipment system based on the idea of the functional chain.
And the contribution rate evaluation module 130 is used for acquiring the comprehensive combat capability indexes before and after each weapon equipment combination joins the combat network of the weapon equipment system, and calculating the system contribution rate of each weapon equipment combination based on the cost constraint condition.
The combination selection module 140 is configured to construct a weapon equipment combination selection model according to a preset objective function and a preset constraint condition, and obtain a target weapon equipment combination from the weapon equipment system combat network through the weapon equipment combination selection model.
Further, the network construction module 110 includes a classification unit, an information acquisition unit, a network construction unit, and a network description unit, and detailed descriptions of the functional units are as follows:
The classifying unit is used for classifying the weapon equipment entities into reconnaissance type, decision type and hit type equipment entities according to different roles played by each weapon equipment entity in the weapon equipment system in the combat.
The information acquisition unit is used for acquiring interaction information among the reconnaissance class, the decision class and the hitting class equipment entity.
The network construction unit is used for abstracting the reconnaissance class, the decision class and the hit class equipment entity into equipment nodes, abstracting the interaction information into sides and constructing a weapon equipment system combat network.
And the network description unit is used for carrying out mathematical description on the weapon equipment system combat network.
Further, as shown in fig. 6, the capability assessment module 120 includes a functional chain definition unit 121, an index system construction unit 122, a demand determination unit 123, a functional chain capability assessment unit 124, and a comprehensive capability assessment unit 125, and the detailed descriptions of the functional units are as follows:
the functional chain definition unit 121 is configured to define a functional chain that is defined as a link capable of playing a battle by interacting between the scout class, decision class, and hit class equipment entities in the weapon equipment system in order to complete a specific battle task.
An index system construction unit 122 for constructing a capability index system of the weapon equipment.
A demand determining unit 123, configured to determine a mission task, and obtain a capability demand for completing the mission task based on a capability index system of the weapon equipment.
A function chain capability assessment unit 124, configured to calculate the combat capability of the single function chain according to the capability requirement for completing the mission task and the existing capability of the weapon equipment corresponding to all the equipment nodes included in the single function chain.
And the comprehensive capability evaluation unit 125 is configured to obtain all the functional chains in the weapon equipment system combat network, and obtain a combat capability comprehensive index of the weapon equipment system combat network through a combat capability evaluation model matched with the number of the functional chains, so as to obtain the combat capability of the weapon equipment system.
Further, the contribution rate evaluation module 130 includes a detection unit, a first calculation unit, and a second calculation unit, and detailed descriptions of the functional units are as follows:
the detection unit is used for acquiring all the functional chains in the weapon equipment system combat network and detecting whether the number of the functional chains is smaller than a preset threshold value.
The first calculation unit is used for obtaining the combat capability comprehensive index of the combat network of the weapon equipment system through a first combat capability evaluation model when the number of functional chains is smaller than a preset threshold, wherein the first combat capability evaluation model is as follows:
Figure BDA0002915472880000131
Wherein E is the comprehensive index of the combat capability of the combat network of the weapon equipment system,
Figure BDA0002915472880000132
and (3) the combat capability of the functional chain in the ith item, and m is the number of the functional chains.
The second calculation unit is configured to obtain, when the number of functional chains is greater than or equal to a preset threshold, a combat capability comprehensive index of the combat network of the weapon equipment system through a second combat capability evaluation model, where the second combat capability evaluation model is:
Figure BDA0002915472880000133
in summary, the system contribution rate-based weapon equipment combination selection system provided in the present embodiment is used to implement the weapon equipment combination selection method based on the system contribution rate corresponding to the foregoing embodiment, and has the beneficial effects of the corresponding method embodiment, which is not described herein.
Those of ordinary skill in the art will appreciate that: the discussion of any of the embodiments above is merely exemplary and is not intended to suggest that the scope of the disclosure, including the claims, is limited to these examples; combinations of features of the above embodiments or in different embodiments are also possible within the idea of the invention, and there are many other variations of the different aspects of the invention as described above, which are not provided in detail for the sake of brevity. Therefore, any omission, modification, equivalent replacement, improvement, etc. of the present invention should be included in the scope of the present invention.

Claims (3)

1. The weapon equipment combination selection method based on the system contribution rate is characterized by comprising the following steps of:
constructing a weapon equipment system combat network model based on the thought of the functional chain;
acquiring the comprehensive combat capability index of the combat network of the weapon equipment system based on the thought of the functional chain, wherein the comprehensive combat capability index comprises the following components:
the functional chain definition is that a reconnaissance class, a decision class and a striking class equipment entity in a weapon equipment system form a link capable of playing a combat capability through interaction in order to complete a specific combat task; constructing a capability index system of weapon equipment; determining a mission task, and acquiring the capability requirement for completing the mission task based on a capability index system of the weapon equipment; calculating the fight capability of the single functional chain according to the capability requirement for completing the mission task and the existing capability of the weapon equipment corresponding to all the equipment nodes contained in the single functional chain, wherein the calculation formula of the fight capability of the single functional chain is as follows: e (E) L ＝ΠE S ×ΠE D ×ΠE B Wherein E is L For the operational capacity of a single functional chain, E S 、E D And E is B The investigation equipment node, the decision equipment node and the hit equipment node contained in the single functional chain are respectively oriented to the combat capability reflected by the mission task; acquiring all the functional chains in the weapon equipment system combat network, and acquiring the combat capability comprehensive index of the weapon equipment system combat network through a combat capability evaluation model matched with the number of the functional chains to acquire the combat capability of the weapon equipment system, wherein the method comprises the following steps: acquiring all the functional chains in the weapon equipment system combat network, and detecting whether the number of the functional chains is smaller than a preset threshold; when the number of the functional chains is smaller than the preset threshold value, the method passes through the first The combat capability evaluation model obtains a combat capability comprehensive index of the combat network of the weapon equipment system, and the first combat capability evaluation model is as follows:
Figure FDA0004229701120000011
wherein E is the comprehensive combat capability index of the combat network of the weapon equipment system, and +.>
Figure FDA0004229701120000012
The operational capacity of the ith functional chain is obtained, and m is the number of the functional chains; when the number of the functional chains is larger than or equal to a preset threshold value, the combat capability comprehensive index of the combat network of the weapon equipment system is obtained through a second combat capability evaluation model, wherein the second combat capability evaluation model is as follows: />
Figure FDA0004229701120000013
Acquiring comprehensive indexes of the combat competence before and after each weapon equipment combination is added into the weapon equipment system combat network, and calculating system contribution rates of each weapon equipment combination based on cost constraint conditions, wherein a calculation formula of the system contribution rates is as follows:
Figure FDA0004229701120000014
wherein (1)>
Figure FDA0004229701120000015
Combination V for weapon equipment x System contribution ratio of ES+V x To add the weapon equipment combination V x Combat capability comprehensive index of weapon equipment system combat network facing mission, E S For not adding the weapon equipment combination V x Is based on the comprehensive combat capability index, cost (V x ) Combining V for said weapon equipment x Cost of->
Figure FDA0004229701120000021
The total cost of all the weapons in the weapons architecture combat network;
constructing a weapon equipment combination selection model according to a preset objective function and a preset constraint condition, and acquiring a target weapon equipment combination from the weapon equipment system combat network through the weapon equipment combination selection model, wherein the preset objective function is as follows:
Figure FDA0004229701120000022
wherein argmax () is a function for optimizing the problem; the preset constraint conditions comprise cost budget constraint and capability requirement constraint, and the feasible weapon equipment combination set obtained according to the cost budget constraint is as follows: />
Figure FDA0004229701120000023
Wherein (1)>
Figure FDA0004229701120000024
For a combined set of possible weaponry, C (V x ) Combining V for said weapon equipment x B is a budget limit; the set of possible weapon equipment combinations obtained according to the capacity requirement constraint is:
Figure FDA0004229701120000025
wherein CA k (V x ) Combining V for said weapon equipment x The kth capacity level, N k Is the kth capability requirement.
2. The weapon equipment combination selection method based on the system contribution rate according to claim 1, wherein the function chain-based concept constructs a weapon equipment system combat network model, comprising:
dividing the weapon equipment entities into reconnaissance type, decision type and striking type equipment entities according to different roles played by each weapon equipment entity in the weapon equipment system in the combat;
Acquiring interaction information among the reconnaissance class, the decision class and the hit class equipment entity;
abstracting a reconnaissance class, a decision class and a hit class equipment entity into equipment nodes, abstracting interaction information into edges, and constructing a weapon equipment system combat network;
mathematical descriptions of the weapon equipment architecture network are provided.
3. A system contribution rate-based weapon equipment combination selection system, comprising:
the network construction module is used for constructing a weapon equipment system combat network model based on the thought of the functional chain;
the capability assessment module is used for acquiring the comprehensive combat capability index of the combat network of the weapon equipment system based on the thought of the functional chain, and comprises the following components: the functional chain definition unit is used for defining functional chains, wherein the functional chains are defined as links capable of playing the combat capability through interaction among detection class, decision class and hit class equipment entities in the weapon equipment system for completing specific combat tasks; the index system construction unit is used for constructing a capability index system of the weapon equipment; the requirement determining unit is used for determining a mission task and acquiring the capability requirement for completing the mission task based on the capability index system of the weapon equipment; the function chain capability assessment unit is used for calculating the fight capability of the single function chain according to the capability requirement for completing the mission task and the existing capability of the weapon equipment corresponding to all the equipment nodes contained in the single function chain, and the calculation formula of the fight capability of the single function chain is as follows: e (E) L ＝ΠE S ×ΠE D ×ΠE B Wherein E is L For the operational capacity of a single functional chain, E S 、E D And E is B The investigation equipment node, the decision equipment node and the hit equipment node contained in the single functional chain are respectively oriented to the combat capability reflected by the mission task; the comprehensive capability evaluation unit is used for acquiring all the functional chains in the weapon equipment system combat network, and acquiring the operations of the weapon equipment system combat network through the combat capability evaluation model matched with the number of the functional chainsA combat competence composite index to obtain combat competence of the weapon equipment system, comprising: acquiring all the functional chains in the weapon equipment system combat network, and detecting whether the number of the functional chains is smaller than a preset threshold; when the number of functional chains is smaller than a preset threshold, a combat capability comprehensive index of the combat network of the weapon equipment system is obtained through a first combat capability evaluation model, wherein the first combat capability evaluation model is as follows:
Figure FDA0004229701120000031
wherein E is the comprehensive combat capability index of the combat network of the weapon equipment system, and +.>
Figure FDA0004229701120000032
The operational capacity of the ith functional chain is obtained, and m is the number of the functional chains; when the number of the functional chains is larger than or equal to a preset threshold value, the combat capability comprehensive index of the combat network of the weapon equipment system is obtained through a second combat capability evaluation model, wherein the second combat capability evaluation model is as follows:
Figure FDA0004229701120000033
The contribution rate evaluation module is used for acquiring the comprehensive combat capability indexes before and after each weapon equipment combination joins the weapon equipment system combat network, and calculating the system contribution rate of each weapon equipment combination based on the cost constraint condition, wherein the calculation formula of the system contribution rate is as follows:
Figure FDA0004229701120000034
wherein,
Figure FDA0004229701120000035
combination V for weapon equipment x System contribution ratio of ES+V x To add the weapon equipment combination V x Combat capability comprehensive index of weapon equipment system combat network facing mission, E S For not adding the weapon equipment combination V x Is a weapon of (2)The combat network of equipment system is based on the comprehensive combat capability index, cost (V x ) Combining V for said weapon equipment x Cost of->
Figure FDA0004229701120000036
The total cost of all the weapons in the weapons architecture combat network;
the combination selection module is used for constructing a weapon equipment combination selection model according to a preset objective function and a preset constraint condition, and acquiring a target weapon equipment combination from the weapon equipment system combat network through the weapon equipment combination selection model, wherein the preset objective function is as follows:
Figure FDA0004229701120000037
wherein argmax () is a function for optimizing the problem;
the preset constraint conditions comprise cost budget constraint and capability requirement constraint, and the feasible weapon equipment combination set obtained according to the cost budget constraint is as follows:
Figure FDA0004229701120000038
Wherein (1)>
Figure FDA0004229701120000039
For a combined set of possible weaponry, C (V x ) Combining V for said weapon equipment x B is a budget limit; the set of possible weapon equipment combinations obtained according to the capacity requirement constraint is: />
Figure FDA0004229701120000041
Wherein CA k (V x ) Combining V for said weapon equipment x The kth capacity level, N k Is the kth capability requirement.
CN202110099990.9A 2021-01-25 2021-01-25 Weapon equipment combination selection method and system based on system contribution rate Active CN112884289B (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN202110099990.9A CN112884289B (en) 2021-01-25 2021-01-25 Weapon equipment combination selection method and system based on system contribution rate

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN202110099990.9A CN112884289B (en) 2021-01-25 2021-01-25 Weapon equipment combination selection method and system based on system contribution rate

Publications (2)

Publication Number Publication Date
CN112884289A CN112884289A (en) 2021-06-01
CN112884289B true CN112884289B (en) 2023-06-16

Family

ID=76051264

Family Applications (1)

Application Number Title Priority Date Filing Date
CN202110099990.9A Active CN112884289B (en) 2021-01-25 2021-01-25 Weapon equipment combination selection method and system based on system contribution rate

Country Status (1)

Country Link
CN (1) CN112884289B (en)

Families Citing this family (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN113296413B (en) * 2021-06-02 2022-06-14 中国人民解放军国防科技大学 Multi-stage equipment development planning method and system based on deep reinforcement learning
CN113469565B (en) * 2021-07-21 2023-08-22 中国人民解放军国防科技大学 Multifunctional equipment scheme selection method under capability uncompensated mechanism and related equipment
CN114912763B (en) * 2022-04-18 2023-04-07 中国兵器科学研究院 Method and device for determining comprehensive capacity of weapon equipment system
CN116108613B (en) * 2022-11-07 2023-12-01 中山大学 Method, system, equipment and medium for quickly constructing interpretable equipment combination

Citations (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
RU113385U1 (en) * 2011-08-03 2012-02-10 Федеральное государственное учреждение "27 Центральный научно-исследовательский институт Министерства обороны Российской Федерации" AUTOMATED SYSTEM FOR EVALUATING THE REALIZED BATTLE POTENTIAL OF MILITARY FORMATION, TAKING INTO ACCOUNT THE TACTICAL AND TECHNICAL CHARACTERISTICS OF MEANS FOR EXPLORATION, COMMUNICATION AND RADIO ELECTRON BATTLE
CN110989343A (en) * 2019-11-25 2020-04-10 中国人民解放军国防科技大学 Multi-stage equipment combination planning method based on reinforcement learning

Family Cites Families (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US6945780B2 (en) * 2001-04-02 2005-09-20 United Defense, L.P. Integrated performance simulation system for military weapon systems
US8248933B2 (en) * 2008-03-07 2012-08-21 The Boeing Company Methods and systems for capability-based system collaboration

Patent Citations (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
RU113385U1 (en) * 2011-08-03 2012-02-10 Федеральное государственное учреждение "27 Центральный научно-исследовательский институт Министерства обороны Российской Федерации" AUTOMATED SYSTEM FOR EVALUATING THE REALIZED BATTLE POTENTIAL OF MILITARY FORMATION, TAKING INTO ACCOUNT THE TACTICAL AND TECHNICAL CHARACTERISTICS OF MEANS FOR EXPLORATION, COMMUNICATION AND RADIO ELECTRON BATTLE
CN110989343A (en) * 2019-11-25 2020-04-10 中国人民解放军国防科技大学 Multi-stage equipment combination planning method based on reinforcement learning

Non-Patent Citations (1)

* Cited by examiner, † Cited by third party
Title
"基于武器装备体系作战网络模型的装备贡献度评估";李际超 等;《复杂系统与复杂性科学》;第13卷(第3期);全文 *

Also Published As

Publication number Publication date
CN112884289A (en) 2021-06-01

Similar Documents

Publication Publication Date Title
CN112884289B (en) Weapon equipment combination selection method and system based on system contribution rate
CN105550323B (en) Load balance prediction method and prediction analyzer for distributed database
Alhusain et al. Towards machine learning based design pattern recognition
JP2008537262A (en) Decision support method and system
CN107944694A (en) A kind of equipment Safeguard operational process analysis method towards operational performance
CN109960863B (en) Complex simulation system credibility evaluation method based on network topology path
CN107609084A (en) One kind converges convergent resource correlation method based on gunz
CN112632744A (en) Combat system architecture modeling method and space exploration algorithm based on hyper-network model
CN110152298A (en) Realize equipment recommended method, device and the computer equipment of virtual role
CN109995592A (en) Quality of service monitoring method and equipment
CN114268981A (en) Network fault detection and diagnosis method and system
CN110059948B (en) Hierarchical network analysis method of OODA (optical on-off digital data acquisition) ring
CN110465086B (en) Game article display method and device and storage medium
CN104092503A (en) Artificial neural network spectrum sensing method based on wolf pack optimization
Simões et al. Towards setplays learning in a multiagent robotic soccer team
CN111652673B (en) Intelligent recommendation method, device, server and storage medium
CN112749516A (en) System combination model reliability intelligent evaluation method suitable for multi-type data characteristics
Liu et al. Exploring functional dependency network based order-degree analysis for resilient system-of-systems architecture design
CN114201199B (en) Protection upgrading method based on big data of information security and information security system
CN113408137B (en) System combat effectiveness analysis method based on task completion degree and loss ratio
CN114238992A (en) Threat vulnerability mining method based on big information security data and information security system
Pang et al. Detecting continual anomalies in monitoring data stream based on sampling GPR algorithm
CN115619105B (en) Dynamic evolution system capacity analysis method and system based on simulation big data
Satapathy et al. Early stage software effort estimation using random forest technique based on optimized class point approach
Vanitha Taylor based Neuro-Genetic Algorithm for Secure and Energy aware multi hop routing protocol in WSN

Legal Events

Date Code Title Description
PB01 Publication
PB01 Publication
SE01 Entry into force of request for substantive examination
SE01 Entry into force of request for substantive examination
GR01 Patent grant
GR01 Patent grant