CN112581340A - Crowd evacuation simulation method and system based on emotional infection recurrence model SIRS - Google Patents
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Abstract
The invention provides a crowd evacuation simulation method and system based on a mood infection recurrence model SIRS, which belongs to the technical field of crowd evacuation simulation and determines a mood recurrence infection rule of a virtual space individual; wherein, the types of the virtual space individuals comprise susceptible persons, infected persons and temporary immune persons; establishing a virtual space emotion recurrence infection model according to the emotion recurrence infection rule of the virtual space individual and by combining the mean field theory; and solving the virtual space emotion recurrence infection model by adopting a finite difference method, simulating the virtual space emotion recurrence infection model by combining the WS small world network, calculating the state transition probability of each node in the WS small world network, and determining the state of the node at the next moment according to the state transition probability. The method analyzes the influence of emotion recurrence on the crowd emotion infection process in the virtual space in an emergency state, more truly simulates individual emotion change and crowd movement, and improves the reality of crowd evacuation.
Description
Technical Field
The invention relates to the technical field of crowd evacuation simulation, in particular to a crowd evacuation simulation method and system based on a emotional infection recurrence model SIRS.
Background
With the rapid development of economy, the crowd density and mobility in public places are high, and a crowded trampling accident often occurs in an emergency state, so that a large number of casualties and severe social influences are caused. Simulated crowd evacuation is also of increasing interest to researchers.
In the existing crowd evacuation methods, the influence of various factors in a physical space on the emotion is researched in some people, and the influence of various factors in a virtual space on the emotion is researched in some people. However, in reality, the emotion is unstable during evacuation of the crowd and a relapse situation may occur. When the surrounding people are in the anxious state or new critical conditions occur after the self emotion is stabilized, the people with the stabilized emotion can relapse and become the anxious state again. The existing crowd evacuation method does not consider the influence of emotional relapse, so that the crowd evacuation under the emergency condition cannot be accurately simulated.
Disclosure of Invention
The invention aims to provide a crowd evacuation simulation method and a crowd evacuation simulation system based on a sentiment infection recurrence model SIRS, which can simulate individual sentiment change and crowd movement more truly and improve the reality of crowd evacuation, so as to solve at least one technical problem in the background technology.
In order to achieve the purpose, the invention adopts the following technical scheme:
in one aspect, the invention provides a crowd evacuation simulation method based on an emotional infection recurrence model SIRS, which comprises the following steps:
establishing emotional relapse infection rules of the individual in the virtual space; wherein the types of the virtual space individuals comprise susceptible persons, infected persons and temporary immune persons;
establishing a virtual space emotion recurrence infection model according to the emotion recurrence infection rule of the virtual space individual and by combining the mean field theory;
and solving the virtual space emotion recurrence infection model by adopting a finite difference method, simulating the virtual space emotion recurrence infection model by combining the WS small world network, calculating the state transition probability of each node in the WS small world network, and determining the state of the node at the next moment according to the state transition probability.
Preferably, establishing the rules of emotional recurring infection for individuals in the virtual space comprises:
the attribute of an individual i in the virtual space is represented by a triplet s (i) ═ (State (i, t), μ, δ); where State (i, t) denotes the class of the individual i at the time t; state (i, t) ═ x, XI, XR, XS indicates a susceptible, XI indicates an infected, XR indicates a temporary immunized; then:
XS is infected with XI with probability β; XI cured by XR with probability μ; XR reverts to XS with probability δ.
Preferably, establishing the virtual space emotional relapse infection model comprises:
determining individual number changes of XI, XS and XR in unit time respectively by combining the emotion recurrence infection rule;
and determining a mean field equation about the triplets according to the individual number change of XI, XS and XR in unit time and combining a mean field theory, and establishing a virtual space emotion recurrent infection model.
Preferably, the number of individuals of the infected person XI per unit time varies:
N[XI(t+Δt)-XI(t)]＝βXS(t)NXI(t)Δt-μNXI(t)Δt+P0XS(t)NΔt；
the number of individuals in the infected person XS per unit time becomes:
N[XS(t+Δt)-XS(t)]＝-βXS(t)NXI(t)Δt-P0XS(t)NΔt+δXR(t)NΔt；
the number of individual XRs per unit time of infected persons varies:
N[XR(t+Δt)-XR(t)]＝μNXI(t)Δt-δXR(t)NΔt；
wherein N represents the total number of individuals, XI(t) represents the individual proportion of XI at time t, XR(t) denotes the individual proportion of XR at time t, XS(t) represents the individual proportion of XS at the time t, P0Indicating probability of spontaneous emotion, XI(t + Δ t) represents the individual proportion of XI at time t + Δ t, XR(t + Δ t) denotes the individual proportion of XR at time t + Δ t, XS(t + Δ t) represents the individual proportion of XS at time t + Δ t.
Preferably, the mean field equation for the triplet is determined as:
preferably, solving the virtual space emotion recurrence infection model by using a finite difference method comprises: using a finite difference method to carry out numerical solution on the virtual space emotion recurrence infection model, and obtaining the change of the numbers of susceptible persons, infected persons and temporary immune persons in the virtual space emotion recurrence infection model along with time to obtain the individual numbers of the susceptible persons, the infected persons and the temporary immune persons at any time; wherein the content of the first and second substances,
at time t, XIThe mean field equation for (t) is:
XI(t+Δt)＝[βXS(t)XI(t)-μXI(t)+P0XS(t)]Δt+XI(t)
at time t, XSThe mean field equation for (t) is:
XS(t+Δt)＝[-βXS(t)XI(t)-P0XS(t)+δXR(t)]Δt+XS(t)
at time t, XRThe mean field equation for (t) is:
XR(t+Δt)＝[μXI(t)-δXR(t)]Δt+XR(t)。
preferably, simulating the virtual space emotional relapse infection model in combination with the WS worldlet network comprises: setting X according to the number of individuals of susceptible persons, infected persons and temporary immune persons as the number of nodes of the WS worlds network, wherein each node has k neighbors, the edge reconnection probability of the node is pSQuilt XIProbability of infection beta, XIQuilt XRProbability of cure μ and XRIs recovered to XSThe probability of (d).
In a second aspect, the invention provides a crowd evacuation simulation system based on SIRS (emotional relapse model), comprising:
the infection rule module is used for establishing emotion recurrence infection rules of the virtual space individuals; wherein the types of the virtual space individuals comprise susceptible persons, infected persons and temporary immune persons;
the model construction module is used for establishing a virtual space emotion recurrence infection model according to the emotion recurrence infection rule of the virtual space individual and by combining the mean field theory;
and the simulation calculation module is used for solving the virtual space emotion recurrence infection model by adopting a finite difference method, simulating the virtual space emotion recurrence infection model by combining the WS small world network, calculating the state transition probability of each node in the WS small world network, and determining the state of the node at the next moment according to the state transition probability.
In a third aspect, the invention also provides a computer device comprising a memory and a processor, the processor and the memory being in communication with each other, the memory storing program instructions executable by the processor, the processor invoking the program instructions to perform a method for crowd evacuation simulation based on SIRS as described above.
In a fourth aspect, the present invention also provides a computer-readable storage medium storing a computer program which, when executed by a processor, implements the method for simulating people evacuation based on SIRS, which is a model of emotional relapse, as described above.
The invention has the beneficial effects that: the influence of emotion recurrence on the crowd emotion infection process in an emergency state in the virtual space is analyzed, individual emotion change and crowd movement are simulated more truly, and the reality of crowd evacuation is improved.
Additional aspects and advantages of the invention will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention.
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In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings needed to be used in the description of the embodiments are briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without creative efforts.
FIG. 1 is a flow chart of a crowd evacuation simulation method based on SIRS of a recurrence of emotional infection model in embodiment 1 of the present invention.
FIG. 2 is a flow chart of a crowd evacuation simulation method based on the SIRS model of emotional infection recurrence according to embodiment 3 of the present invention.
Fig. 3 is a schematic diagram of the rules of emotional relapse infection according to the embodiment of the invention.
Detailed Description
Reference will now be made in detail to embodiments of the present invention, examples of which are illustrated in the accompanying drawings, wherein like or similar reference numerals refer to the same or similar elements or elements having the same or similar function throughout. The embodiments described below by way of the drawings are illustrative only and are not to be construed as limiting the invention.
It will be understood by those skilled in the art that, unless otherwise defined, all terms (including technical and scientific terms) used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs.
It will be further understood that terms, such as those defined in commonly used dictionaries, should be interpreted as having a meaning that is consistent with their meaning in the context of the prior art and will not be interpreted in an idealized or overly formal sense unless expressly so defined herein.
As used herein, the singular forms "a", "an", "the" and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise. It will be further understood that the terms "comprises" and/or "comprising," when used in this specification, specify the presence of stated features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof.
In the description herein, references to the description of the term "one embodiment," "some embodiments," "an example," "a specific example," or "some examples," etc., mean that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the invention. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples. Furthermore, various embodiments or examples and features of different embodiments or examples described in this specification can be combined and combined by one skilled in the art without contradiction.
For the purpose of facilitating an understanding of the present invention, the present invention will be further explained by way of specific embodiments with reference to the accompanying drawings, which are not intended to limit the present invention.
It should be understood by those skilled in the art that the drawings are merely schematic representations of embodiments and that the elements shown in the drawings are not necessarily required to practice the invention.
Example 1
As shown in fig. 1, embodiment 1 of the present invention provides a crowd evacuation simulation method based on SIRS, which includes: establishing emotional relapse infection rules of the individual in the virtual space; wherein the types of the virtual space individuals comprise susceptible persons, infected persons and temporary immune persons;
establishing a virtual space emotion recurrence infection model according to the emotion recurrence infection rule of the virtual space individual and by combining the mean field theory;
and solving the virtual space emotion recurrence infection model by adopting a finite difference method, simulating the virtual space emotion recurrence infection model by combining the WS small world network, calculating the state transition probability of each node in the WS small world network, and determining the state of the node at the next moment according to the state transition probability.
Establishing rules for emotional recurring infections for individuals in virtual spaces includes:
the attribute of an individual i in the virtual space is represented by a triplet s (i) ═ (State (i, t), μ, δ); where State (i, t) denotes the class of the individual i at the time t; state (i, t) ═ x, XI, XR, XS indicates a susceptible, XI indicates an infected, XR indicates a temporary immunized; then:
XS is infected with XI with probability β; XI cured by XR with probability μ; XR reverts to XS with probability δ.
The establishment of the virtual space emotion recurrence infection model comprises the following steps:
determining individual number changes of XI, XS and XR in unit time respectively by combining the emotion recurrence infection rule;
and determining a mean field equation about the triplets according to the individual number change of XI, XS and XR in unit time and combining a mean field theory, and establishing a virtual space emotion recurrent infection model.
The number of individuals in infected person XI per unit time becomes:
N[XI(t+Δt)-XI(t)]＝βXS(t)NXI(t)Δt-μNXI(t)Δt+P0XS(t)NΔt；
the number of individuals in the infected person XS per unit time becomes:
N[XS(t+Δt)-XS(t)]＝-βXS(t)NXI(t)Δt-P0XS(t)NΔt+δXR(t)NΔt；
the number of individual XRs per unit time of infected persons varies:
N[XR(t+Δt)-XR(t)]＝μNXI(t)Δt-δXR(t)NΔt；
wherein N represents the total number of individuals, XI(t) represents the individual proportion of XI at time t, XR(t) denotes the individual proportion of XR at time t, XS(t) represents the individual proportion of XS at the time t, P0Indicating probability of spontaneous emotion, XI(t + Δ t) represents the individual proportion of XI at time t + Δ t, XR(t + Δ t) denotes the individual proportion of XR at time t + Δ t, XS(t + Δ t) represents the individual proportion of XS at time t + Δ t.
The mean field equation for the triplet is determined as:
solving the virtual space emotion recurrence infection model by adopting a finite difference method comprises the following steps: using a finite difference method to carry out numerical solution on the virtual space emotion recurrence infection model, and obtaining the change of the numbers of susceptible persons, infected persons and temporary immune persons in the virtual space emotion recurrence infection model along with time to obtain the individual numbers of the susceptible persons, the infected persons and the temporary immune persons at any time; wherein the content of the first and second substances,
at time t, XIThe mean field equation for (t) is:
XI(t+Δt)＝[βXS(t)XI(t)-μXI(t)+P0XS(t)]Δt+XI(t)
at time t, XSThe mean field equation for (t) is:
XS(t+Δt)＝[-βXS(t)XI(t)-P0XS(t)+δXR(t)]Δt+XS(t)
at time t, XRThe mean field equation for (t) is:
XR(t+Δt)＝[μXI(t)-δXR(t)]Δt+XR(t)。
simulating a virtual space emotion recurrent infection model in combination with a WS small world network comprises: setting X according to the number of individuals of susceptible persons, infected persons and temporary immune persons as the number of nodes of the WS worlds network, wherein each node has k neighbors, the edge reconnection probability of the node is pSQuilt XIProbability of infection beta, XIQuilt XRProbability of cure μ and XRIs recovered to XSThe probability of (d).
Example 2
The embodiment 2 of the invention provides a crowd evacuation simulation system based on an emotional infection recurrence model SIRS, which comprises:
the infection rule module is used for establishing emotion recurrence infection rules of the virtual space individuals; wherein the types of the virtual space individuals comprise susceptible persons, infected persons and temporary immune persons;
the model construction module is used for establishing a virtual space emotion recurrence infection model according to the emotion recurrence infection rule of the virtual space individual and by combining the mean field theory;
and the simulation calculation module is used for solving the virtual space emotion recurrence infection model by adopting a finite difference method, simulating the virtual space emotion recurrence infection model by combining the WS small world network, calculating the state transition probability of each node in the WS small world network, and determining the state of the node at the next moment according to the state transition probability.
The crowd evacuation simulation method based on emotional relapse infection by utilizing the crowd evacuation simulation system based on the emotional relapse model SIRS comprises the following steps:
step (1): and constructing an individual emotion recurrence infection model. And (5) proposing emotional recurrent infection rules.
Step (2): and constructing an emotion recurrence infection model for analyzing the dynamic change of the emotion of the individual.
And (3): and a WS small-world network based on the emotional recurrent infection model is constructed, the state conversion of nodes in the small-world network is discussed, and the rationality of the emotional recurrent infection model is verified.
And (4): the emotional infection process is visualized, and the simulation effect is more truly and intuitively displayed.
The construction process of the individual emotion recurrence infection model in the step (1) is as follows:
in an individual emotional relapse infection model, an emotional relapse factor in a virtual space is considered. These factors will be divided into two parts: emotional relapse and infection space.
There is emotional recurrent infection in the virtual space. Therefore, in embodiment 2, the attribute of the individual i in the virtual space is represented by a triplet s (i) ═ State (i, t), μ, δ; where State (i, t) indicates the class of individual i at time t.
In this embodiment 2, State (i, t) is divided into three categories: susceptible, infected and temporarily immunized humans; in this example 2, State (i, t) ═ XS, XI, XR is defined, XS indicating a susceptible person, XI indicating an infected person, and XR indicating a temporary immunized person.
Emotional infection can occur in the virtual space, and the emotional relapse can also affect the emotional infection process of the crowd. Therefore, the rules of emotional recurrent infections are presented in this example to simulate emotional recurrent infections. The probability that a susceptible individual is infected with an infected individual is β, the probability that the infected individual is cured to a temporarily immunized individual is μ, and the probability that the temporarily immunized individual becomes a susceptible individual is δ, the emotional infection rule is:
(1) a susceptible person XS in virtual space can be infected with probability β to a virtual space infected person XI, becoming a virtual space infected person XI.
(2) The infected person XI in the virtual space can be cured with probability μ by the temporary immunized person XR, becoming the temporary immunized person XR.
(3) The temporary immunized XR has the potential to revert to the virtual space perceptron XS.
The construction process of the emotion recurrence infection model of the virtual space in the step (2) is as follows:
in this embodiment 2, an average field theory is used to deduce an evolution process of an emotional recurrent infection model of a virtual space, obtain an average field equation of the model, and then solve the equation by using a finite difference method. As shown in table one, the parameters of the mean field equation of the model of emotional recurrent infection in the virtual space are defined.
TABLE 1 values of parameters in the infection space
The mean field equation of the model of emotional recurrent infection obtained by mean field theory is:
then, the numerical solution can be obtained by a finite difference method as follows:
XI(t+Δt)＝[βXS(t)XI(t)-μXI(t)+P0XS(t)]Δt+XI(t)
XS(t+Δt)＝[-βXS(t)XI(t)-P0XS(t)+δXR(t)]Δt+XS(t)
XR(t+Δt)＝[μXI(t)-δXR(t)]Δt+XR(t)
given the initial conditions of individuals in different states in the population at time t-0, the number of individuals at time t + Δ t can be calculated from the above equation.
The WS small world network construction process of the emotion recurrence infection model based on the virtual space in the step (3) is as follows:
in this embodiment 2, the WS worldlet network is represented by G (V, E). Finally, to reflect emotional recurrence, a small probability P is added0I.e., other factors that may cause a susceptible to relapse into an infected person. The roulette method is used to explore the state transitions of nodes in a recurring WS small world network.
The state transition of any node in the WS loop small world network in time interval [ t, t +1] is analyzed.
Firstly, the state transition probability of each node is calculated, and then the state of the node at the next moment is determined according to the probability.
Example 3
As shown in fig. 2, this embodiment 3 provides a crowd evacuation simulation method based on SIRS, which mainly includes the following processes:
process 1: and constructing an individual emotion recurrence infection model and providing an emotion recurrence infection rule.
The first step is as follows: modeling of individual emotional recurrent infection.
The present disclosure represents the attributes of each individual i in virtual space with a triplet s (i), (t), μ, δ). Where s (i) ═ (State (i, t), μ, δ) represents the State of the individual i at any time t. Mu means the cure rate of infected persons. δ represents the recovery rate of the naive immunised.
As shown in fig. 3, the individual states are classified into the following three categories: susceptible, infected and temporarily immunized persons in virtual space. Define State (i, t) ═ XS,XI,XR) XS TableShow the susceptible population in virtual space, XI represents the infected person in physical space, XR represents the temporarily immunized person in virtual space.
The second step is that: and (5) proposing emotional recurrent infection rules.
In example 3, the rules of emotional recurrent infection are mainly proposed to simulate emotional recurrent infection. In the infection model, a susceptible individual in the virtual space may be infected by an infected person, becoming a member of the infected person. Infected individuals may be cured by the temporarily immunized person and become one of the cured persons. Temporary immunizers recover with probability to a susceptible individual over time.
And (2) a process: and constructing an emotion recurrence infection model in the virtual space.
The first step is as follows: modeling was done using the mean field equation.
The change in the number of individuals in infected person XI per unit time can be expressed as:
N[XI(t+Δt)-XI(t)]＝βXS(t)NXI(t)Δt-μNXI(t)Δt+P0XS(t)NΔt；
the individual number change of the infected person XS per unit time can be expressed as:
N[XS(t+Δt)-XS(t)]＝-βXS(t)NXI(t)Δt-P0XS(t)NΔt+δXR(t)NΔt；
the change in the individual number of XRs per unit time of an infected person can be expressed as:
N[XR(t+Δt)-XR(t)]＝μNXI(t)Δt-δXR(t)NΔt；
wherein N represents the total number of individuals, XI(t) represents the individual proportion of XI at time t, XR(t) denotes the individual proportion of XR at time t, XS(t) represents the individual proportion of XS at the time t, P0Indicates the probability of the susceptible population spontaneously becoming an infected person, XI(t + Δ t) represents the individual proportion of XI at time t + Δ t, XR(t + Δ t) denotes the individual proportion of XR at time t + Δ t, XS(t + Δ t) represents the individual proportion of XS at time t + Δ t.
Thus, the mean field equation for the model of emotional recurrent infection can be obtained as:
the second step is that: and solving by using a finite difference method.
To determine the number of susceptible, infected and provisionally immunized individuals in the model of emotional recurrent infection in virtual space over time, a numerical solution was performed using a finite difference method.
At time t, using a finite difference method, XIThe mean field equation of (t) can be expressed as:
XI(t+Δt)＝[βXS(t)XI(t)-μXI(t)+P0XS(t)]Δt+XI(t)；
at time t, using a finite difference method, XSThe mean field equation of (t) can be expressed as:
XS(t+Δt)＝[-βXS(t)XI(t)-P0XS(t)+δXR(t)]Δt+XS(t)；
at time t, using a finite difference method, XRThe mean field equation of (t) can be expressed as:
XR(t+Δt)＝[μXI(t)-δXR(t)]Δt+XR(t)。
by the three equations, the number of people in each state at the initial moment can be obtained, and the number of people in each state at any moment can be obtained.
And 3, process: a recurrent WS small world network was constructed.
The first step is as follows: a recurrent WS small world network was constructed.
The method comprises the steps of firstly giving 3 parameters of a small-world network model, wherein N is the number of points, k represents k/2 neighbors on the left side of each point, k/2 neighbors on the right side of each point and k neighbors in total, p represents the probability of reconnection of each edge, then drawing N nodes with a circle as a contour, giving an adjacent matrix A, putting the edges of an image in the adjacent matrix A, and reconnecting and modifying the edges with the probability p. The infection probability beta, the cure probability mu and the recovery rate delta are set.
The second step is that: the state transitions of nodes in the WS worlds network are explored.
The state transition of nodes in the WS small-world network is explored by using a roulette method, the state transition probability of each node is calculated, and then the state of the node at the next moment is determined according to the probability. The method comprises the following steps:
as long as we give the state of node i at time t, its state at the next time can be obtained by the following method. In a recurrent WS-worlds network, there are multiple types of neighbor nodes around the susceptible node. Therefore, in the neighbor nodes of the susceptible node, the number of nodes in XI is assumed to be P. Then, use
To represent the probability of state transition of a susceptible node in an information space by
To represent the state transition probability of an infected node in the information space, by qXI R,STo represent the state transition probability of the temporary immune node in the information space.
Thus, there are
S- > I transition probability:
i- > R transition probability:
r- > S transition probability:
and 4, process: the REC is simulated, and the simulated evacuation effect is more intuitively displayed.
Example 4
Embodiment 4 of the present invention provides a computer device, including a memory and a processor, the processor and the memory being in communication with each other, the memory storing program instructions executable by the processor, the processor calling the program instructions to execute the method for simulating people evacuation based on SIRS, the method including:
establishing emotional relapse infection rules of the individual in the virtual space; wherein the types of the virtual space individuals comprise susceptible persons, infected persons and temporary immune persons;
establishing a virtual space emotion recurrence infection model according to the emotion recurrence infection rule of the virtual space individual and by combining the mean field theory;
and solving the virtual space emotion recurrence infection model by adopting a finite difference method, simulating the virtual space emotion recurrence infection model by combining the WS small world network, calculating the state transition probability of each node in the WS small world network, and determining the state of the node at the next moment according to the state transition probability.
Example 5
Embodiment 5 of the present invention provides a computer-readable storage medium storing a computer program which, when executed by a processor, implements the method for simulating people evacuation based on SIRS, which is a model of emotional relapse.
As will be appreciated by one skilled in the art, embodiments of the present invention may be provided as a method, system, or computer program product. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
The above description is only a preferred embodiment of the present disclosure and is not intended to limit the present disclosure, and various modifications and changes may be made to the present disclosure by those skilled in the art. Any modification, equivalent replacement, improvement and the like made within the spirit and principle of the present disclosure should be included in the protection scope of the present disclosure.
Although the present disclosure has been described with reference to the specific embodiments shown in the drawings, it is not intended to limit the scope of the present disclosure, and it should be understood by those skilled in the art that various modifications and variations can be made without inventive faculty based on the technical solutions disclosed in the present disclosure.
Claims (10)
1. A crowd evacuation simulation method based on a mood infection recurrence model SIRS is characterized in that:
establishing emotional relapse infection rules of the individual in the virtual space; wherein the types of the virtual space individuals comprise susceptible persons, infected persons and temporary immune persons;
establishing a virtual space emotion recurrence infection model according to the emotion recurrence infection rule of the virtual space individual and by combining the mean field theory;
and solving the virtual space emotion recurrence infection model by adopting a finite difference method, simulating the virtual space emotion recurrence infection model by combining the WS small world network, calculating the state transition probability of each node in the WS small world network, and determining the state of the node at the next moment according to the state transition probability.
2. The method of claim 1, wherein establishing rules for emotional relapse infection of individuals in a virtual space comprises:
the attribute of an individual i in the virtual space is represented by a triplet s (i) ═ (State (i, t), μ, δ); where State (i, t) denotes the class of the individual i at the time t; state (i, t) ═ x, XI, XR, XS indicates a susceptible, XI indicates an infected, XR indicates a temporary immunized; then:
XS is infected with XI with probability β; XI cured by XR with probability μ; XR reverts to XS with probability δ.
3. The method of claim 2, wherein establishing a virtual space model of emotional relapse infection comprises:
determining individual number changes of XI, XS and XR in unit time respectively by combining the emotion recurrence infection rule;
and determining a mean field equation about the triplets according to the individual number change of XI, XS and XR in unit time and combining a mean field theory, and establishing a virtual space emotion recurrent infection model.
4. The method for simulating people evacuation based on SIRS (emotional relapse model) of claim 3, wherein the method comprises the following steps:
the number of individuals in infected person XI per unit time becomes:
the number of individuals in the infected person XS per unit time becomes:
the number of individual XRs per unit time of infected persons varies:
wherein N represents the total number of individuals, XI(t) represents the individual proportion of XI at time t, XR(t) denotes the individual proportion of XR at time t, XS(t) represents the individual proportion of XS at the time t, P0Denotes the probability that XS is spontaneously XI, XI(t + Δ t) represents the individual proportion of XI at time t + Δ t, XR(t + Δ t) denotes the individual proportion of XR at time t + Δ t, XS(t + Δ t) denotes XS at time tIndividual proportion at + Δ t.
5. The method for crowd evacuation simulation based on emotional infection relapse model SIRS according to claim 4, characterized by determining the mean field equation for the triplets as:
6. the method for simulating crowd evacuation based on SIRS (emotional recurrence model) according to claim 5, wherein solving the virtual space emotional recurrence infection model using finite difference method comprises: using a finite difference method to carry out numerical solution on the virtual space emotion recurrence infection model, and obtaining the change of the numbers of susceptible persons, infected persons and temporary immune persons in the virtual space emotion recurrence infection model along with time to obtain the individual numbers of the susceptible persons, the infected persons and the temporary immune persons at any time; wherein the content of the first and second substances,
at time t, XIThe mean field equation for (t) is:
at time t, XSThe mean field equation for (t) is:
at time t, XRThe mean field equation for (t) is:
7. the method of claim 6, wherein simulating a virtual space emotional relapse infection model in conjunction with a WS worlds network comprises: setting X according to the number of individuals of susceptible persons, infected persons and temporary immune persons as the number of nodes of the WS worlds network, wherein each node has k neighbors, the edge reconnection probability of the node is pSQuilt XIProbability of infection beta, XIQuilt XRProbability of cure μ and XRIs recovered to XSThe probability of (d).
8. A crowd evacuation simulation system based on an emotional infection recurrence model SIRS is characterized by comprising:
the infection rule module is used for establishing emotion recurrence infection rules of the virtual space individuals; wherein the types of the virtual space individuals comprise susceptible persons, infected persons and temporary immune persons;
the model construction module is used for establishing a virtual space emotion recurrence infection model according to the emotion recurrence infection rule of the virtual space individual and by combining the mean field theory;
and the simulation calculation module is used for solving the virtual space emotion recurrence infection model by adopting a finite difference method, simulating the virtual space emotion recurrence infection model by combining the WS small world network, calculating the state transition probability of each node in the WS small world network, and determining the state of the node at the next moment according to the state transition probability.
9. A computer device comprising a memory and a processor, the processor and the memory in communication with each other, characterized in that: the memory stores program instructions executable by the processor to perform the method of crowd evacuation simulation based on model SIRS of emotional infection relapse according to any of claims 1-7.
10. A computer-readable storage medium storing a computer program, characterized in that: the computer program when executed by a processor implements a method of crowd evacuation simulation based on model SIRS of emotional infection relapse according to any of claims 1-7.
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