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Time sequence network immunization method based on random walk

A random walk and time series network technology, applied in the field of social network and control of disease spread, can solve the problem of imbalance between immune cost and immune effect

Pending Publication Date: 2020-12-25
SHANGHAI UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0005] The purpose of the present invention is to provide a random walk immunization method based on a time series network to solve the problems of unbalanced immunization cost and immunization effect in controlling virus transmission in the prior art

Method used

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  • Time sequence network immunization method based on random walk
  • Time sequence network immunization method based on random walk
  • Time sequence network immunization method based on random walk

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0065] see figure 1 , a sequential network immune method based on random walk, applied to the sequential network, the operation steps are as follows:

[0066] Step S1: Given the immune ratio f, obtain the network structure and node neighbor information according to the original data in the network;

[0067] Step S2: Set random walk parameters according to the initial network structure and node neighbor information;

[0068] Step S3: Determine the immune time T according to the network structure and random walk parameters;

[0069] Step S4: According to the instantaneous network from the initial moment to the Tth moment, construct a time-series accumulation network, perform random walk, and determine the immune nodes until the immune nodes reach the proportion of f;

[0070] Step S5: Take the state of the immune node during the random walk as the initial state, and carry out the epidemic propagation process;

[0071] Step S6: Calculate the proportion of infected nodes in the...

Embodiment 2

[0074] This embodiment is basically the same as Embodiment 1, and the special features are as follows:

[0075] In the step S1, the method for obtaining network structure and node neighbor information includes:

[0076] Step S1.1: Assign an activity factor a∈(0,1) to all nodes in the network, and the activity follows a power-law distribution with a given power exponent γ: F(a)∝a -γ ;

[0077] Step S1.2: At each moment, all nodes in the instantaneous network are activated with their own activity factor a, which is called an active node; the activated node generates m edges to connect other nodes. Inactive nodes cannot actively send edges, but can receive connected edges; in the entire network construction, self-loops and repeated connections are not allowed;

[0078] Step S1.3: The duration of all connected edges in the network is Δt;

[0079] Step S1.4: After Δt time, delete all connected edges in the network;

[0080] In the step S2, the random walk parameters include: th...

Embodiment 3

[0106] This embodiment is basically the same as the above-mentioned embodiment, and the special features are as follows:

[0107] A sequential network immune method based on random walk, applied to the sequential network, the operation steps are as follows:

[0108] Step S1: This step is the same as the second embodiment;

[0109] Step S2: This step is the same as the second embodiment;

[0110] Step S3: This step is the same as the second embodiment;

[0111] Step S4: This step is the same as the second embodiment;

[0112] Step S5: Use the state of the immune node during the random walk as the initial state to simulate the epidemic spreading process, including:

[0113] Step S5.21: Select p 0 Proportional nodes are used as infected nodes;

[0114] Step S5.22: using the "susceptibility-infection-recovery" (SIR) transmission model to simulate the virus transmission process;

[0115] Step S5.23: At each moment, the instantaneous network evolves according to the rules of s...

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Abstract

The invention discloses a time sequence network immunization method based on random walk. The method comprises the following steps: firstly, acquiring an initial network structure and node neighbor information according to original data in a network; secondly, setting random walk parameters according to the initial network structure and node neighbor information; then determining immunization timeaccording to the network structure and the random walk parameters; constructing a time sequence accumulation network according to the immunization time; implementing a random walk process, and determining immune nodes until a certain proportion of nodes are immunized; taking the state of the immune node in the random walk process as an initial state, and carrying out epidemic propagation; and finally, counting the proportion of infected nodes in the network in a steady state. According to the immunization method, the immune cost can be effectively reduced, and a certain immune effect is achieved.

Description

technical field [0001] This application relates to the technical field of social network and control of disease spread, in particular to a time series network immunization method based on random walk. Background technique [0002] In the field of social networks and epidemic transmission, it is usually necessary to study immune methods to control the spread of epidemics. The immunization methods of the static network mainly include four kinds: random immunization, acquaintance immunization, random walk immunization and target immunization. With the development of data science, social networks are represented as more accurate time-series networks with time stamps, and the edges between nodes appear or disappear over time. In order to control the spread of the virus on the time series network, it is usually necessary to determine the immune nodes, that is, to immunize some nodes in the network so that they lose the ability to spread the virus, thereby reducing the spread of t...

Claims

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Application Information

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IPC IPC(8): G16H50/80G06F16/2458G06Q50/00
CPCG16H50/80G06F16/2474G06Q50/01Y02D30/70
Inventor 王冰曾红娟韩越兴
Owner SHANGHAI UNIV
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