CN110505080B - Hybrid structure-based command control hyper-network dynamic evolution model construction method - Google Patents
Hybrid structure-based command control hyper-network dynamic evolution model construction method Download PDFInfo
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Abstract
The invention discloses a command control hyper-network dynamic evolution model construction method based on a mixed structure, which comprises the following steps of firstly, analyzing limiting factors existing in a network evolution process, and proposing network modeling constraints; secondly, based on a network framework with a mixed structure, a network evolution rule is formulated according to the addition and deletion processes of nodes and connecting edges and by combining with the rule conditions of actual military evolution; and finally, providing a model evolution step according to network evolution constraints and rules to generate a final network evolution model, and effectively and accurately reflecting the internal mechanism and the external behavior of the command control network evolution.
Description
Technical Field
The invention belongs to the field of military command and control, and particularly relates to a command control super-network dynamic evolution model construction method based on a mixed structure.
Background
The command control network is used as a hub for command issuing and information transmission of the command control system and is the key for winning in war. With the continuous improvement of the information degree of the battlefield, the organization structure of the command control network is increasingly complex, the information interaction is more frequent, the characteristics of node diversity and heterogeneity, link multiple interleaving and the like are shown, and the command control network has the characteristics of a typical complex network. The command control network has strong topological time variation in the operation process, and the military organization generates structural change due to dynamic adjustment of the structure of the military organization on one hand because of complex battlefield environment and instantaneous and variable operation relation. The network structure change comprises the addition and deletion of nodes and the addition and deletion of connecting edges, and corresponds to the actual combat behaviors of the support of the combat units, the destruction of the combat units, the establishment of communication among the combat units and the destruction of the communication among the combat units. Therefore, the dynamic evolution modeling research on the combat unit can provide good theoretical support for resource integration and structure optimization of the internal structure of the command and control network, and becomes the key point of the military field and network science research. However, the existing evolution model of the command and control network has certain limitations, and the problem that the internal mechanism of the dynamic change of the command and control network is difficult to effectively analyze is solved.
The command control network is continuously evolved along with the changes of the battle tasks and the confrontation environment, and then the node attributes and the edge attributes are influenced. The establishment of the evolution model of the command control network needs to consider the following evolution characteristics:
(1) node and connecting edge dynamic elimination
The firepower increase and the capacity increase in the command control network can lead to the new addition of nodes in the network; structure adjustment and service expansion in the command control network enable the network to add a connecting edge; the command control unit is attacked and destroyed in the fire attack, and resource integration is carried out on the command control unit for optimizing the structure, so that some nodes and connecting edges in the command control network are deleted.
(2) Node and connecting edge have heterogeneity
The nodes in the command control network show the heterogeneity of the nodes under different connection conditions, and the connection has different meanings in different sub-networks. For example, the connected nodes between the sensing nodes are used as information sharers, and the connected edges represent the cooperative information flow between the combat entities. When the perception node is connected with the command node, the perception node is used as an information collector, and the connection edge represents the information flow between the combat entities. Under different relationships, nodes and edges exhibit significant heterogeneity.
(3) Topological feature and node attribute jointly influence evolution process
When the factors causing the dynamic evolution of the network are explored, analysis shows that not only the topological characteristics of the network play roles, such as the degree and betweenness of nodes, but also the attribute values of the network nodes play a certain role in influence, and when the network capacity is strong, the fighting capacity and the command capacity are better, and the network nodes are more easily selected for connection. Therefore, in the process of exploring the dynamic evolution of the network, not only the topological characteristics of the network are considered, but also the attribute values of the nodes are analyzed.
In view of the fact that the existing command control network evolution is mostly based on a two-dimensional network, the problem of the multi-dimensional cross relationship in the command control network evolution process is difficult to accurately describe. Therefore, it is necessary to establish a new evolution model suitable for the command and control network to analyze the evolution mechanism in the command and control network.
Disclosure of Invention
Aiming at the defects of the existing command control network evolution model, the application provides a command control super-network dynamic evolution model construction method based on a mixed structure, and firstly, limiting factors existing in the network evolution process are analyzed, and network modeling constraints are provided; secondly, based on a network framework with a mixed structure, a network evolution rule is formulated according to the addition and deletion processes of nodes and connecting edges and by combining with the rule conditions of actual military evolution; and finally, providing a model evolution step according to network evolution constraints and rules to generate a final network evolution model, and effectively and accurately reflecting the internal mechanism and the external behavior of the command control network evolution.
In order to achieve the purpose, the technical scheme of the invention is as follows: a command control hyper-network dynamic evolution model construction method based on a mixed structure comprises the following specific steps:
s1: proposing modeling constraints of a command control network;
s2: formulating evolution rules of a command control network;
s3: and establishing a command control network evolution model.
Further, a command control network modeling constraint is proposed, specifically: the military command control network is not formed by the mutual communication of any two nodes, and the connection of the nodes has certain restriction, namely the nodes can be connected only when certain restriction conditions are met. There are various constraints on node connections, including physical topology constraints, organizational structure constraints, node attribute constraints, and the like. In order to analyze the evolution mechanism of the command and control network more accurately, constraint conditions in the network need to be considered, so that the connection between the nodes meets the actual evolution process. The invention proposes the following constraints for command control over-network evolution:
the nodes are connected with edge limit constraints. Each node has limited ability to accept and process information, and thus there is an upper limit on the edges of the node.
② physical continuous edge constraint. The investigation information obtained by the sensing node is processed and analyzed by the command node, and then a combat command is formed and sent to the firepower node. Therefore, no physical connection exists between the firepower node and the sensing node, and the connecting edges of the firepower node and the sensing node do not need to exist in the evolution process.
Command rule constraint. In the actual operation process, in order to ensure the high efficiency and the orderliness of the operation, the firepower node can only receive the command of the command node. Therefore, one command node can be connected with a plurality of firepower nodes, but one firepower node must correspond to one command node.
And fourthly, restraining the isolated nodes. Each node has practical interactive significance and cannot exist in isolation. Therefore, in the process of setting the evolution rule, a certain processing method should be provided for the isolated node, such as deleting the node or adding the connecting edge.
Further, a command control network evolution rule is formulated, specifically: network evolution is a dynamic process of changing the existing network structure according to certain rules. Due to activities such as firepower assistance and organizational structure adjustment, the situation that nodes and connecting edges are increased exists in the command control network; meanwhile, in military operations, activities such as entity attack, army resource integration and the like exist, and the node and the connecting edge deletion exist. The network needs to evolve according to a certain rule, and the invention combines the actual military operation process and sets the corresponding network evolution rule.
a. Node addition rule
Adding command nodes. Because the commanding nodes have a hierarchical relationship, such as army, teacher, travel, etc., the probability of adding the nodes of different levels is unequal. The higher the rank, the fewer the number of director nodes, and the relatively lower the probability of a new higher rank node in the network. The probability of the grade of the newly added command node is as follows:
wherein L is the set of all existing levels and L is the level to which the current node belongs.
② fire nodes are increased. The node has two types of attributes of function Attr and performance Cap. The function and performance of the newly added fire node are distributed according to the following formula:
PF Attrthe probability vector represents the probability that the newly added fire node has different functions. Wherein N isaThe number of existing fire nodes is N.
CapFThe new heat increasing power node is a numerical value vector and has different performance values. Wherein Random (a, b) is a Random number between values a and b.
And thirdly, adding a sensing node. The perception node increasing rule is the same as the fire node increasing rule.
b. Rule of increasing connected edges
The upper and lower level command nodes are connected with edges. To represent the uniqueness of the organization's affiliation, the node selects only one superior node to connect to. The probability that the superior node is selected to be connected with the newly added node is as follows:
wherein
Indicates the number of the child nodes owned by the superior node i, NL-1Representing the upper set of all nodes.
And secondly, commanding nodes to cross cascade edges. The command node not only commands the subordinate units directly but also carries out cross-level command. The higher the hierarchy of the command node is, the greater the command authority and command capability of the command node are, the more easily the cross-cascade edge is initiated, and the probability of the selected initiating node is as follows:
where L is the set of all levels present, L is the selected level value, NlIs the total number of the selected level nodes.
The larger the lower node value is, the easier the node is connected, and the probability of the connected node being selected is:
wherein N islIs the set of all nodes of the selected hierarchy, and D (j) is the degree of node j.
And thirdly, the command nodes are connected with edges in a coordinated mode. The command nodes at the same level have activities such as information sharing, cooperative combat and the like, and the command subnets need to be cooperatively connected. The selected probability of the cooperative edge-connected initiating node is as follows:
the probability of the selected connected nodes of the cooperative connection edge is as follows:
Wherein AttriFor initiating a function vector of a node, CapiFor the performance vector of the initiating node, x is the multiplication of corresponding elements of the two vectors, and Dis () is a function of the euclidean distance between the two vectors.
And fourthly, adding fire nodes and connecting edges. The probability of selecting the existing node connecting edges by the newly added fire node is as follows:
Wherein N isFAnd j is a newly added fire node.
Adding new sensing node connecting edges. The probability of selecting the existing node connecting edges by the newly added sensing node is as follows:
Wherein N isSAnd j is a newly added sensing node.
And sixthly, connecting the fire power with the command node. The commander node is as being connected the node, and the ability is stronger can command more firepower nodes, and its probability of being connected is also big more, and the selected probability of commander node is:
Wherein
Is the transpose of the performance vector of node i.
And seventhly, sensing the edges connected with the command nodes. The smaller the total capacity of the sensing nodes connected with the command nodes is, the stronger the demand on intelligence is, and the easier the sensing nodes are connected with. The selected probability of the command nodes is as follows:
wherein
For the function vector of the sensing node k connected with the command node i,
transpose of performance vector for the perception node k connected to the command node i, NCSFor all sensing node sets connected with the selected command nodes, NCAll nodes are aggregated for the director node.
c. Node deletion rules
And (6) deleting the command nodes. The lower the rank of the command node, the weaker the action of the command node, the lower the value of the command node, the weaker the information processing and command fighting capabilities of the command node, and the more easily the nodes conforming to the characteristics are deleted. The selected probability of the nodes is as follows:
after the node is deleted, all the connecting edges connecting with the node are also deleted.
And eliminating fire nodes. The lower the firepower node capacity value is, the more easily the node is deleted, and the selected probability is as follows:
after the node is deleted, all the connecting edges connecting with the node are also deleted.
Deleting the sensing nodes. The deleted mechanism of the sensing node is consistent with that of the fire node, so the selected probability of the node is as follows:
d. continuous edge deletion rules
Deleting command nodes and connecting edges. The probability that the connecting edges between the command nodes are selected to be deleted is as follows:
wherein eijIs the connecting edge of nodes i and j, ECAll edges in the network are aggregated for command control.
And eliminating fire node connecting edges. The probability of selecting the edges among the fire nodes is as follows:
wherein EFSet of all connected edges of fire subnet, BeIs the median value of the connecting edge e.
Deleting the sensing node connecting edge. The probability of selecting the connecting edges among the perception nodes is as follows:
wherein ESTo sense all sets of contiguous edges of a subnet, eijRepresenting the connecting edge of nodes i and j.
And fourthly, fire power and command connection are deleted. The probability of selecting the fire node and the command node is as follows:
wherein ECFAll connecting edges representing command-fire subnets, eijRepresenting the connecting edge of nodes i and j.
Deleting the perception and command connection edge. The probability of selecting the connecting edges between the perception nodes and the command nodes is as follows:
wherein
The number of all connected edges is commanded and sensed.
Further, establishing a command control network evolution model, specifically:
initializing a network model. Setting the number of initial nodes N0Taking a typical command control hyper-network as an initial model, and comparing different types of nodes according to n1:n2:n3Initialise 3:4:3, n1+n2+n3＝N0；
② with a certain probability p1Various nodes are added. Respectively as follows: with probability p11Increase command nodes by probability p12Increase the fire node by the probability p13And perception nodes are added, and the probabilities meet the following conditions:
p1＝p11+p12+p13 (21)
③ at a certain probability p2And adding a connecting edge. The increase of the base network connecting edge comprises the following steps: with probability p21Increasing the finger-controlled continuous edge with probability p22Increase the fire power and connect the edges with the probability p23Adding a sensing connecting edge; adding the command subnet connection edge comprises: with probability p24Increasing the cross-level command connecting edge of command subnet with probability p25Adding command subnet cooperative connection edges; adding cross subnet connection edges includes: with probability p26Increase firepower and command linking side by probability p27And increasing the perception and command connecting edge. The probabilities satisfy:
p2＝p21+p22+p23+p24+p25+p26+p27 (22)
fourthly, with a certain probability p3And deleting the nodes. With probability p31Deleting command nodes with probability p32Deleting fire node by probability p33Deleting the perception nodes, and satisfying the following conditions between probabilities:
p3＝p31+p32+p33 (23)
fifthly, with a certain probability p4And deleting the continuous edges. With probability p41Deleting edges with probability p42Remove fire-connected edges with probability p43Deleting perceptual edges with probability p44Remove fire and command edges with probability p45Deleting the perception and command connection edge. The probabilities satisfy:
p4＝p41+p42+p43+p44+p45 (24)
and looping over two to five, executing one item of evolution according to probability in each time step, and stopping the evolution when the evolution step T is larger than the set step T value. The probabilities satisfy:
p1+p2+p3+p4＝1 (25)
and seventhly, finishing.
Due to the adoption of the technical method, the invention can obtain the following technical effects: the command control network evolution model construction method provides a command control super-network dynamic evolution model based on a mixed structure by considering the multilayer mixed structure characteristics of the command control network, has higher accuracy, and is further favorable for improving the combat efficiency and the survivability of the command control network.
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In order to more clearly illustrate the embodiments of the present invention or the technical solutions of the prior art, the drawings needed to be used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts.
FIG. 1 is a command control hyper-network model;
FIG. 2 is a schematic diagram of a command control super-network evolution process.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer, the following describes the technical solutions of the embodiments of the present invention clearly and completely with reference to the accompanying drawings in the embodiments of the present invention:
the command control network is used as a hub for command issuing and information transmission of the command control system and is the key for winning in war. With the continuous improvement of the information degree of the battlefield, the organization structure of the command control network is increasingly complex, the information interaction is more frequent, the characteristics of node diversity and heterogeneity, link multiple interleaving and the like are shown, and the command control network has the characteristics of a typical complex network. The command control network has strong topological time variation in the operation process, and the military organization generates structural change due to dynamic adjustment of the structure of the military organization on one hand because of complex battlefield environment and instantaneous and variable operation relation. The network structure change comprises the addition and deletion of nodes and the addition and deletion of connecting edges, and corresponds to the actual combat behaviors of the support of the combat units, the destruction of the combat units, the establishment of communication among the combat units and the destruction of the communication among the combat units. Therefore, the dynamic evolution modeling research on the combat unit can provide good theoretical support for resource integration and structure optimization of the internal structure of the command and control network, and becomes the key point of the military field and network science research. However, the existing evolution model of the command and control network has certain limitations, and the problem that the internal mechanism of the dynamic change of the command and control network is difficult to effectively analyze is solved.
In view of the fact that the existing command control network evolution is mostly based on a two-dimensional network, the problem of the multi-dimensional cross relationship in the command control network evolution process is difficult to accurately describe. The application provides a command control hyper-network dynamic evolution model construction method based on a mixed structure, which comprises the steps of firstly, analyzing limiting factors existing in a network evolution process and providing network modeling constraints; secondly, based on a network framework with a mixed structure, a network evolution rule is formulated according to the addition and deletion processes of nodes and connecting edges and by combining with the rule conditions of actual military evolution; and finally, providing a model evolution step according to network evolution constraints and rules to generate a final network evolution model, and effectively and accurately reflecting the internal mechanism and the external behavior of the command control network evolution.
Examples
A command control hyper-network dynamic evolution model construction method based on a mixed structure comprises the following specific steps:
s1: proposing a command control network modeling constraint, specifically: the military command control network is not formed by the mutual communication of any two nodes, and the connection of the nodes has certain restriction, namely the nodes can be connected only when certain restriction conditions are met. There are various constraints on node connections, including physical topology constraints, organizational structure constraints, node attribute constraints, and the like. In order to analyze the evolution mechanism of the command and control network more accurately, constraint conditions in the network need to be considered, so that the connection between the nodes meets the actual evolution process. The invention proposes the following constraints for command control over-network evolution:
the nodes are connected with edge limit constraints. Each node has limited ability to accept and process information, and thus there is an upper limit on the edges of the node.
② physical continuous edge constraint. The investigation information obtained by the sensing node is processed and analyzed by the command node, and then a combat command is formed and sent to the firepower node. Therefore, no physical connection exists between the firepower node and the sensing node, and the connecting edges of the firepower node and the sensing node do not need to exist in the evolution process.
Command rule constraint. In the actual operation process, in order to ensure the high efficiency and the orderliness of the operation, the firepower node can only receive the command of the command node. Therefore, one command node can be connected with a plurality of firepower nodes, but one firepower node must correspond to one command node.
And fourthly, restraining the isolated nodes. Each node has practical interactive significance and cannot exist in isolation. Therefore, in the process of setting the evolution rule, a certain processing method should be provided for the isolated node, such as deleting the node or adding the connecting edge.
S2: formulating evolution rules of the command control network, which specifically comprises the following steps: network evolution is a dynamic process of changing the existing network structure according to certain rules. Due to activities such as firepower assistance and organizational structure adjustment, the situation that nodes and connecting edges are increased exists in the command control network; meanwhile, in military operations, activities such as entity attack, army resource integration and the like exist, and the node and the connecting edge deletion exist. The network needs to evolve according to a certain rule, and the invention combines the actual military operation process and sets the corresponding network evolution rule.
a. Node addition rule
Adding command nodes. Because the commanding nodes have a hierarchical relationship, such as army, teacher, travel, etc., the probability of adding the nodes of different levels is unequal. The higher the rank, the fewer the number of director nodes, and the relatively lower the probability of a new higher rank node in the network. The probability of the grade of the newly added command node is as follows:
wherein L is the set of all existing levels and L is the level to which the current node belongs.
② fire nodes are increased. The node has two types of attributes of function Attr and performance Cap. The function and performance of the newly added fire node are distributed according to the following formula:
PF Attrthe probability vector represents the probability that the newly added fire node has different functions. Wherein N isaThe number of existing fire nodes is N.
CapFThe new heat increasing power node is a numerical value vector and has different performance values. Wherein Random (a, b) is a Random number between values a and b.
And thirdly, adding a sensing node. The perception node increasing rule is the same as the fire node increasing rule.
b. Rule of increasing connected edges
The upper and lower level command nodes are connected with edges. To represent the uniqueness of the organization's affiliation, the node selects only one superior node to connect to. The probability that the superior node is selected to be connected with the newly added node is as follows:
wherein
Indicates the number of the child nodes owned by the superior node i, NL-1Representing the upper set of all nodes.
And secondly, commanding nodes to cross cascade edges. The command node not only commands the subordinate units directly but also carries out cross-level command. The higher the hierarchy of the command node is, the greater the command authority and command capability of the command node are, the more easily the cross-cascade edge is initiated, and the probability of the selected initiating node is as follows:
where L is the set of all levels present, L is the selected level value, NlIs the total number of the selected level nodes.
The larger the lower node value is, the easier the node is connected, and the probability of the connected node being selected is:
wherein N islIs the set of all nodes of the selected hierarchy, and D (j) is the degree of node j.
And thirdly, the command nodes are connected with edges in a coordinated mode. The command nodes at the same level have activities such as information sharing, cooperative combat and the like, and the command subnets need to be cooperatively connected. The selected probability of the cooperative edge-connected initiating node is as follows:
the probability of the selected connected nodes of the cooperative connection edge is as follows:
Wherein AttriFor initiating a function vector of a node, CapiFor the performance vector of the initiating node, x is the multiplication of corresponding elements of the two vectors, and Dis () is a function of the euclidean distance between the two vectors.
And fourthly, adding fire nodes and connecting edges. The probability of selecting the existing node connecting edges by the newly added fire node is as follows:
Wherein N isFAnd j is a newly added fire node.
Adding new sensing node connecting edges. The probability of selecting the existing node connecting edges by the newly added sensing node is as follows:
Wherein N isSAnd j is a newly added sensing node.
And sixthly, connecting the fire power with the command node. The commander node is as being connected the node, and the ability is stronger can command more firepower nodes, and its probability of being connected is also big more, and the selected probability of commander node is:
Wherein
Is the transpose of the performance vector of node i.
And seventhly, sensing the edges connected with the command nodes. The smaller the total capacity of the sensing nodes connected with the command nodes is, the stronger the demand on intelligence is, and the easier the sensing nodes are connected with. The selected probability of the command nodes is as follows:
wherein
For the function vector of the sensing node k connected with the command node i,
transpose of performance vector for the perception node k connected to the command node i, NCSFor all sensing node sets connected with the selected command nodes, NCAll nodes are aggregated for the director node.
c. Node deletion rules
And (6) deleting the command nodes. The lower the rank of the command node, the weaker the action of the command node, the lower the value of the command node, the weaker the information processing and command fighting capabilities of the command node, and the more easily the nodes conforming to the characteristics are deleted. The selected probability of the nodes is as follows:
after the node is deleted, all the connecting edges connecting with the node are also deleted.
And eliminating fire nodes. The lower the firepower node capacity value is, the more easily the node is deleted, and the selected probability is as follows:
after the node is deleted, all the connecting edges connecting with the node are also deleted.
Deleting the sensing nodes. The deleted mechanism of the sensing node is consistent with that of the fire node, so the selected probability of the node is as follows:
d. continuous edge deletion rules
Deleting command nodes and connecting edges. The probability that the connecting edges between the command nodes are selected to be deleted is as follows:
wherein eijIs the connecting edge of nodes i and j, ECAll edges in the network are aggregated for command control.
And eliminating fire node connecting edges. The probability of selecting the edges among the fire nodes is as follows:
whereinEFSet of all connected edges of fire subnet, BeIs the median value of the connecting edge e.
Deleting the sensing node connecting edge. The probability of selecting the connecting edges among the perception nodes is as follows:
wherein ESTo sense all sets of contiguous edges of a subnet, eijRepresenting the connecting edge of nodes i and j.
And fourthly, fire power and command connection are deleted. The probability of selecting the fire node and the command node is as follows:
wherein ECFAll connecting edges representing command-fire subnets, eijRepresenting the connecting edge of nodes i and j.
Deleting the perception and command connection edge. The probability of selecting the connecting edges between the perception nodes and the command nodes is as follows:
wherein
The number of all connected edges is commanded and sensed.
S3: establishing a command control network evolution model, specifically:
initializing a network model. Setting the number of initial nodes N0Taking a typical command control hyper-network as an initial model, and comparing different types of nodes according to n1:n2:n3Initialise 3:4:3, n1+n2+n3＝N0；
② with a certain probability p1Various nodes are added. Respectively as follows: with probability p11Increase ofCommanding nodes with probability p12Increase the fire node by the probability p13And perception nodes are added, and the probabilities meet the following conditions:
p1＝p11+p12+p13 (21)
③ at a certain probability p2And adding a connecting edge. The increase of the base network connecting edge comprises the following steps: with probability p21Increasing the finger-controlled continuous edge with probability p22Increase the fire power and connect the edges with the probability p23Adding a sensing connecting edge; adding the command subnet connection edge comprises: with probability p24Increasing the cross-level command connecting edge of command subnet with probability p25Adding command subnet cooperative connection edges; adding cross subnet connection edges includes: with probability p26Increase firepower and command linking side by probability p27And increasing the perception and command connecting edge. The probabilities satisfy:
p2＝p21+p22+p23+p24+p25+p26+p27 (22)
fourthly, with a certain probability p3And deleting the nodes. With probability p31Deleting command nodes with probability p32Deleting fire node by probability p33Deleting the perception nodes, and satisfying the following conditions between probabilities:
p3＝p31+p32+p33 (23)
fifthly, with a certain probability p4And deleting the continuous edges. With probability p41Deleting edges with probability p42Remove fire-connected edges with probability p43Deleting perceptual edges with probability p44Remove fire and command edges with probability p45Deleting the perception and command connection edge. The probabilities satisfy:
p4＝p41+p42+p43+p44+p45 (24)
and looping over two to five, executing one item of evolution according to probability in each time step, and stopping the evolution when the evolution step T is larger than the set step T value. The probabilities satisfy:
p1+p2+p3+p4＝1 (25)
and seventhly, finishing.
Claims (1)
1. A command control hyper-network dynamic evolution model construction method based on a mixed structure is characterized by comprising the following specific steps:
s1: proposing modeling constraints of a command control network;
s2: formulating evolution rules of a command control network;
s3: establishing a command control network evolution model;
proposing a command control network modeling constraint, specifically:
connecting nodes with edge boundary constraint: an upper limit value exists on the connecting edge of the node;
secondly, physical edge connection constraint: no physical connection exists between the firepower node and the sensing node;
command rule constraint: one command node can be connected with a plurality of fire nodes, but one fire node is required to correspond to one command node;
and fourthly, constraint of isolated nodes: processing the isolated node, namely deleting the node or adding a connecting edge;
formulating evolution rules of the command control network, which specifically comprises the following steps:
a. node addition rule
Increasing command nodes: the probability of the grade of the newly added command node is as follows:
wherein L is all existing grade sets, L is the grade to which the current node belongs, and k is an element in the L set;
increasing firepower nodes: the node has two types of attributes of function Attr and performance Cap; the function and performance of the newly added fire node are distributed according to the following formula:
PF Attrthe probability vector represents the probability that the newly added fire node has different functions; wherein N isaThe method comprises the following steps of (1) setting an existing fire node set, wherein N is the number of existing fire nodes;
CapFa numerical value vector is used for indicating that the new heat increasing power node has different performance values; wherein Random (a, b) is a Random number between values a and b;
adding a sensing node: the rule of adding the sensing node is the same as the rule of adding the firepower node;
b. rule of increasing connected edges
Connecting upper and lower level command nodes with edges: in order to represent the uniqueness of the organization attribution, the nodes only select one superior node to be connected, and the probability that the superior node is selected to be connected with the newly added node is as follows:
wherein
The number of the child nodes owned by the upper node i is shown,
representing the number of the child nodes owned by the superior node k;
commanding nodes to cross cascade edges: the probability that the initiating node is selected is as follows:
where L is all existing rank sets, k is one of the rank sets, L is selected mediumValue of rank, NlThe total number of the selected grade nodes is shown;
the probability of being selected by the connected node is as follows:
wherein N islIs the set of all nodes of the selected hierarchy, D (j) is the degree of the node j, and D (i) is the degree of the node i;
and thirdly, the command nodes are connected with the edges in a coordinated manner: the selected probability of the cooperative edge-connected initiating node is as follows:
the probability of the selected connected nodes of the cooperative connection edge is as follows:
wherein AttriTo initiate a function vector, Cap, of node iiFor initiating a Performance vector of node i, AttrjTo initiate a function vector, Cap, of node jjFor the Performance vector of the initiating node j, AttrkTo initiate a function vector of node k, CapkFor the performance vector of the initiating node k, Dis () is a function for solving Euclidean distance between two vectors;
fourthly, adding a fire node connecting edge: the probability of selecting the existing node connecting edges by the newly added fire node is as follows:
wherein N isFAll firepower nodes are set, and j is a newly added firepower node;
adding a sensing node connecting edge: the probability of selecting the existing node connecting edges by the newly added sensing node is as follows:
wherein N isSAll sensing node sets are defined, and j is a newly added sensing node;
connecting the firepower and the command nodes: the selected probability of the command nodes is as follows:
wherein
Is a transpose of the performance vector of node i, where
Is the transpose of the performance vector of node k;
and seventhly, sensing and connecting edges with the command nodes: the selected probability of the command nodes is as follows:
wherein
For the function vector of the sensing node k connected with the command node i,
transpose of performance vector for the perception node k connected to the command node i, NCSFor all sensing node sets connected with the selected command nodes, NCAll the nodes are collected for command nodes;
c. node deletion rules
Deleting command nodes: the selected probability of the nodes is as follows:
after deleting the node, deleting all the connecting edges connected with the node;
deleting firepower nodes: the selected probability is:
after deleting the node, deleting all the connecting edges connected with the node;
deleting the sensing node: the selected probability is:
d. continuous edge deletion rules
Deleting command nodes and connecting edges: the probability that the connecting edges between the command nodes are selected to be deleted is as follows:
wherein eijIs the connecting edge of nodes i and j, ECCollecting all connected edges in the command control network;
deleting fire nodes and connecting edges: the probability of selecting the edges among the fire nodes is as follows:
wherein EFSet of all connected edges of fire subnet, BeIs the median value of the connecting edge e;
deleting the sensing node connecting edges: the probability of selecting the connecting edges among the perception nodes is as follows:
wherein ESTo sense all sets of contiguous edges of a subnet, eijRepresenting the connecting edge of the nodes i and j;
fourthly, fire power and command connection are deleted: the probability of selecting the fire node and the command node is as follows:
wherein ECFAll connecting edges representing command-fire subnets, eijRepresenting the connecting edge of the nodes i and j;
deleting the perception and command connection edge: the probability of selecting the connecting edges between the perception nodes and the command nodes is as follows:
wherein
The number of all connected edges is commanded and sensed;
establishing a command control network evolution model, specifically:
firstly, initializing a network model: setting the number of initial nodes N0Taking a typical command control hyper-network as an initial model, and comparing different types of nodes according to n1:n2:n3Initialise 3:4:3, n1+n2+n3＝N0；
② with a certain probability p1Various nodes are added; respectively as follows: with probability p11Increase command nodes by probability p12Increase the fire node by the probability p13And perception nodes are added, and the probabilities meet the following conditions:
p1＝p11+p12+p13 (21)
③ at a certain probability p2Adding a connecting edge: the increase of the base network connecting edge comprises the following steps: with probability p21Increasing the finger-controlled continuous edge with probability p22Increase the fire power and connect the edges with the probability p23Adding a sensing connecting edge; adding the command subnet connection edge comprises: with probability p24Increasing the cross-level command connecting edge of command subnet with probability p25Adding command subnet cooperative connection edges; adding cross subnet connection edges includes: with probability p26Increase firepower and command linking side by probability p27Increasing a perception and command connecting edge; the probabilities satisfy:
p2＝p21+p22+p23+p24+p25+p26+p27 (22)
fourthly, with a certain probability p3And deleting the nodes: with probability p31Deleting command nodes with probability p32Deleting fire node by probability p33Deleting the perception nodes, and satisfying the following conditions between probabilities:
p3＝p31+p32+p33 (23)
fifthly, with a certain probability p4Deleting the connecting edge: with probability p41Deleting edges with probability p42Remove fire-connected edges with probability p43Deleting perceptual edges with probability p44Remove fire and command edges with probability p45Deleting the perception and command connecting edge; the probabilities satisfy:
p4＝p41+p42+p43+p44+p45 (24)
and looping the two to the fifth step, executing one evolution item according to the probability at each time step, stopping the evolution when the evolution step T is larger than the set step T value, and meeting the following conditions among the probabilities:
p1+p2+p3+p4＝1 (25)
and seventhly, finishing.
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