Dual-objective optimization simulation evolution deduction method and system for network public opinion propagation

Abstract

The invention provides a dual-objective optimization simulation evolution deduction method and system for network public opinion propagation, relates to the field of network public opinion propagation analysis and regulation, solves the problem that bionic modeling, analysis and simulation of network public opinion propagation are difficult, and adopts the scheme that a dual-objective optimization model for network public opinion propagation is established; constructing a negative information propagation evaluation model of network public opinion propagation; constructing a negative information propagation variation regulation and control model of network public opinion propagation; the negative information level and the propagation level of network public opinion propagation are used as calculation objects of a variation regulation operator, and propagation of network public opinion negative information is inhibited; constructing a front guidance network public opinion generation crossover operator with a higher priority, and reducing the propagation space and speed of network public opinion negative information through the propagation of the front guidance network public opinion; performing iterative optimization operation on the operation object by using a dual-objective optimization evolutionary algorithm to obtain a parameter sequence with positive guidance maximization and negative information propagation minimization; and regulating and controlling model parameters of network public opinion propagation according to the optimal or suboptimal parameter sequence. According to the scheme of the invention, a simulation evolution deduction platform of network public opinion propagation can be constructed, the negative influence of network public opinion propagation is weakened and optimized by using a dual-objective evolution optimization algorithm, and the recognition capability, regulation and control capability and learning optimization capability of network public opinion propagation are improved.

Description

Technical Field

[0001] The present invention relates to the field of online public opinion dissemination analysis, and in particular to a dual-objective optimization simulation evolutionary deduction method and system for online public opinion dissemination. Background Art

[0002] This section is intended to provide background or context for the embodiments of the invention set forth in the claims. The descriptions herein may include concepts that may be explored, but not necessarily concepts that have been previously thought of or explored. Therefore, unless otherwise noted herein, the content described in this section is not prior art with respect to the specification and claims of this application, and is not admitted to be prior art by inclusion in this section.

[0003] Traditional methods for analyzing the spread of online public opinion are mainly based on mathematical models with strict conditions, which are far from the actual uncertain and complex environmental conditions. They lack the ability to adapt to various application scenarios and are often only able to simulate and calculate a single optimization goal. They lack sufficient computing power to support the actual dual-objective optimization. As a result, in the complex and changeable online public opinion dissemination environment, it is difficult to promptly suppress the rapid spread of negative information on the Internet. They ignore the auxiliary calculations of positive guidance and have a large room for improvement.

[0004] Therefore, real-world application needs urgently require a new method that simulates and deduces the evolutionary mechanism that can perform dual-objective optimization, and uses it for dual-objective optimization simulation evolutionary deduction of online public opinion dissemination. Summary of the invention

[0005] In order to solve the above technical problems, the purpose of the present invention is to provide a dual-objective optimization simulation evolutionary deduction method and system for network public opinion propagation.

[0006] To solve the above technical problems, in the first aspect, according to some embodiments, the present invention provides a dual-objective optimization simulation evolutionary deduction method for network public opinion propagation.

[0007] Establish a dual-objective optimization model for online public opinion dissemination;

[0008] Construct a negative information dissemination evaluation model for online public opinion dissemination;

[0009] Construct a variation regulation model of negative information dissemination in online public opinion dissemination;

[0010] The level of negative information and the level of dissemination of online public opinion are used as the calculation objects of the variation control operator to suppress the dissemination of negative information of online public opinion.

[0011] Construct a crossover operator with higher priority to generate positive guidance of online public opinion, and reduce the space and speed of negative information on online public opinion by positively guiding the spread of online public opinion;

[0012] The bi-objective optimization evolutionary algorithm is used to iteratively optimize the operation object, and the parameter sequence that maximizes positive guidance and minimizes negative information propagation is obtained;

[0013] The model parameters of online public opinion propagation are regulated according to the optimal or suboptimal parameter sequence.

[0014] In some embodiments, the model parameters of the online public opinion propagation include: constraint parameters for the goal of minimizing the propagation of negative information of online public opinion, constraint parameters for maximizing the goal of positively guiding online public opinion, negative information propagation evaluation parameters for the propagation of online public opinion, negative information propagation variation probability for the propagation of online public opinion, negative information level parameters for the propagation of online public opinion, propagation level parameters for online public opinion, propagable space parameters for online public opinion, propagation speed parameters for online public opinion, and at least any one of the crossover probability of a crossover operator generated by positively guiding online public opinion.

[0015] In some embodiments, the dual-objective optimization model of the dissemination of online public opinion satisfies the constraint parameter conditions of the goal of minimizing the dissemination of negative information in online public opinion and the constraint parameter conditions of the goal of maximizing the positive guidance of online public opinion. Through the dual-objective evolutionary optimization algorithm, iterative calculation is performed to achieve the basic goal of minimizing the dissemination of negative information in online public opinion and the auxiliary goal of maximizing the positive guidance of online public opinion. Maximizing the positive guidance of online public opinion is an auxiliary means to promote the minimization of the dissemination of negative information in online public opinion.

[0016] In some embodiments, the negative information propagation evaluation model for online public opinion dissemination is used to evaluate and calculate the fitness function value of negative information propagation for online public opinion dissemination to describe the negative information level, propagation level and propagation speed of online public opinion dissemination.

[0017] In some embodiments, the negative information propagation variation control model of network public opinion propagation uses a dual-objective evolutionary optimization algorithm to perform optimization operations on network public opinion propagation objects to obtain an optimal or suboptimal parameter sequence, specifically including:

[0018] Mutation control operator operation: The level of negative information and the level of propagation of online public opinion are used as the calculation objects of the mutation control operator to suppress the propagation of negative information of online public opinion;

[0019] Positive guidance of online public opinion generation crossover operator operation: used to generate positive guidance of online public opinion with higher priority;

[0020] Optimizing and selecting an operator operation according to the fitness function value;

[0021] The coordination operator operation between the goal of minimizing the spread of negative information on online public opinion and maximizing the goal of guiding positive online public opinion;

[0022] The operation of regulating the parameters of the network public opinion propagation model according to the optimal or suboptimal parameter sequence.

[0023] In a second aspect, an embodiment of the present invention further provides a dual-objective optimization simulation evolutionary deduction system for network public opinion propagation, characterized in that it includes:

[0024] The dual-objective optimization model construction module of online public opinion dissemination is used to establish a dual-objective optimization model of online public opinion dissemination, set the constraint parameters of the objective of minimizing the dissemination of negative information of online public opinion, and the constraint parameters of the objective of maximizing the positive guidance of online public opinion;

[0025] The module for constructing the evaluation model of negative information propagation of online public opinion is used to construct the evaluation model of negative information propagation of online public opinion, set the evaluation parameters of negative information propagation of online public opinion, the negative information level parameters of online public opinion, the propagation level parameters of online public opinion, the propagation space parameters of online public opinion, and the propagation speed parameters of online public opinion, evaluate and calculate the fitness function value of negative information propagation of online public opinion, so as to describe the negative information level, propagation level and propagation speed of online public opinion;

[0026] The module for constructing the variation control model of negative information propagation in online public opinion dissemination is used to construct the variation control model of negative information propagation in online public opinion dissemination, set the variation probability of negative information propagation in online public opinion dissemination, take the negative information level and propagation level of online public opinion dissemination as the calculation objects of the variation control operator, and suppress the spread of negative information in online public opinion dissemination;

[0027] A higher priority positive guidance network public opinion generation crossover operator module sets the crossover probability parameter of the positive guidance network public opinion generation crossover operator, which is used to reduce the propagation space and speed of negative information of network public opinion by positively guiding the propagation of network public opinion;

[0028] The optimal or suboptimal solution solving module of the dual-objective optimization evolutionary algorithm is used to use the dual-objective optimization evolutionary algorithm to perform iterative optimization operations on the operation object and obtain a parameter sequence that maximizes positive guidance and minimizes negative information propagation;

[0029] The network public opinion regulation module is used to regulate the model parameters of network public opinion dissemination according to the optimal or suboptimal parameter sequence, and gradually minimize the impact of negative information in network public opinion dissemination with the assistance of maximizing positive guidance.

[0030] In some embodiments, the dual-objective optimization model construction module for network public opinion propagation includes:

[0031] A constraint parameter setting unit for minimizing the propagation of negative information of online public opinion, used to set the constraint parameters for minimizing the propagation of negative information of online public opinion;

[0032] The constraint parameter setting unit for maximizing the goal of positively guiding online public opinion is used to set the constraint parameters for maximizing the goal of positively guiding online public opinion.

[0033] In some embodiments, the negative information dissemination evaluation model building module of the network public opinion dissemination includes:

[0034] A negative information dissemination evaluation parameter setting unit for network public opinion dissemination, used to set negative information dissemination evaluation parameters for network public opinion dissemination;

[0035] A negative information level parameter setting unit for network public opinion dissemination, used to set negative information level parameters for network public opinion dissemination;

[0036] A network public opinion propagation level parameter setting unit, used to set the network public opinion propagation level parameters;

[0037] A network public opinion propagation space parameter setting unit, used to set network public opinion propagation space parameters;

[0038] The network public opinion propagation speed parameter setting unit is used to set the network public opinion propagation speed parameter.

[0039] The above technical solution of the present invention has at least the following beneficial technical effects:

[0040] The technical scheme of the above-mentioned embodiment can establish a dual-objective optimization model for the propagation of online public opinion, construct a negative information propagation evaluation model for the propagation of online public opinion, and construct a variation and regulation model for the propagation of negative information for the propagation of online public opinion. The negative information level and propagation level of the propagation of online public opinion are used as the calculation objects of the variation and regulation operator to suppress the propagation of negative information of online public opinion, and construct a crossover operator with higher priority for positively guiding the generation of online public opinion. By positively guiding the propagation of online public opinion, the propagation space and speed of negative information of online public opinion are reduced. The dual-objective optimization evolutionary algorithm is used to iteratively optimize the operation object to find the parameter sequence that maximizes positive guidance and minimizes the propagation of negative information. The model parameters of the propagation of online public opinion are regulated according to the optimal or suboptimal parameter sequence, so that the complicated online public opinion propagation analysis and learning system can be quickly and effectively regulated, which greatly saves manpower and computing power loss, reduces the impact of negative information on online public opinion, and saves resource costs. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the conventional technology, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0042] Figure 1 It is a flow chart of a dual-objective optimization simulation evolution deduction method for network public opinion propagation according to the first embodiment of the present invention;

[0043] Figure 2 is a flow chart of a dual-objective optimization method for network public opinion dissemination according to a first embodiment of the present invention;

[0044] Figure 3 It is a structural schematic diagram of a dual-objective optimization simulation evolutionary deduction system for network public opinion dissemination according to an optional implementation mode of the present invention;

[0045] Figure 4 It is a flow chart of a dual-objective evolutionary optimization algorithm for the propagation, variation and regulation of negative information in the dissemination of online public opinion according to an optional implementation mode of the present invention. DETAILED DESCRIPTION

[0046] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0047] Furthermore, in the following description, descriptions of well-known structures and technologies are omitted to avoid unnecessarily obscuring the concepts of the present invention.

[0048] If there are descriptions involving "first", "second", etc. in the embodiments of the present application, the descriptions of "first", "second", etc. are only for descriptive purposes and cannot be understood as indicating or implying their relative importance or implicitly indicating the number of the indicated technical features. Therefore, the features defined as "first" or "second" may explicitly or implicitly include at least one of the features; the technical solutions between the various embodiments can be combined with each other, based on the ability of ordinary technicians in the field to implement.

[0049] In the embodiments of the present application, when A and / or B are mentioned, it means A, B, and A and B.

[0050] It should be noted that the sequence numbers mentioned in this application do not necessarily mean that the steps must be strictly followed in the actual implementation process. The sequence numbers are used to distinguish each step for ease of explanation and to avoid confusion.

[0051] The accompanying drawings show schematic diagrams of layer structures according to embodiments of the present invention. These figures are not drawn to scale, and some details are magnified and some details may be omitted for the purpose of clarity. The shapes of various regions and layers shown in the figures and the relative sizes and positional relationships therebetween are only exemplary, and may deviate in practice due to manufacturing tolerances or technical limitations, and those skilled in the art may additionally design regions / layers with different shapes, sizes, and relative positions according to actual needs.

[0052] In addition, the technical features involved in the different embodiments of the present invention described below can be combined with each other as long as they do not conflict with each other.

[0053] Traditional methods for analyzing the spread of online public opinion are mainly based on mathematical models with strict conditions, which are far from the actual uncertain and complex environmental conditions. They lack the ability to adapt to various application scenarios and are often only able to simulate and calculate a single optimization goal. They lack sufficient computing power to support the actual dual-objective optimization. As a result, in the complex and changeable online public opinion dissemination environment, it is difficult to promptly suppress the rapid spread of negative information on the Internet, and the auxiliary calculations for positive guidance are ignored.

[0054] In view of these shortcomings, the present invention designs a dual-objective optimization simulation evolutionary deduction model and algorithm for the propagation of online public opinion, establishes a dual-objective optimization model for the propagation of online public opinion, constructs a negative information propagation evaluation model for the propagation of online public opinion, constructs a negative information propagation variation regulation model for the propagation of online public opinion, takes the negative information level and propagation level of the propagation of online public opinion as the calculation objects of the variation regulation operator, suppresses the propagation of negative information of online public opinion, constructs a positive guidance online public opinion generation crossover operator with higher priority, reduces the propagation space and speed of negative information of online public opinion by positively guiding the propagation of online public opinion, uses a dual-objective optimization evolutionary algorithm to iteratively optimize the operation object, finds a parameter sequence that maximizes positive guidance and minimizes negative information propagation, regulates the model parameters of online public opinion propagation according to the optimal or suboptimal parameter sequence, enables the complicated online public opinion propagation analysis and learning system to be quickly and effectively regulated, greatly saves manpower and computing power loss, reduces the impact of negative information on online public opinion, and saves resource costs.

[0055] Based on the above technical concept, an embodiment of the present invention provides a dual-objective optimization simulation evolutionary deduction method for network public opinion propagation, including:

[0056] Establish a dual-objective optimization model for online public opinion dissemination;

[0057] Construct a negative information dissemination evaluation model for online public opinion dissemination;

[0058] Construct a variation regulation model of negative information dissemination in online public opinion dissemination;

[0059] The level of negative information and the level of dissemination of online public opinion are used as the calculation objects of the variation control operator to suppress the dissemination of negative information of online public opinion.

[0060] Construct a crossover operator with higher priority to generate positive guidance of online public opinion, and reduce the space and speed of negative information on online public opinion by positively guiding the spread of online public opinion;

[0061] The bi-objective optimization evolutionary algorithm is used to iteratively optimize the operation object, and the parameter sequence that maximizes positive guidance and minimizes negative information propagation is obtained;

[0062] The model parameters of online public opinion propagation are regulated according to the optimal or suboptimal parameter sequence.

[0063] The following is described by specific examples, see Figure 1 shown.

[0064] S101: Establish a dual-objective optimization model for online public opinion dissemination, such as Figure 2 As shown, a negative information dissemination evaluation model for online public opinion dissemination is constructed;

[0065] S102: Construct a variation control model for the propagation of negative information in the propagation of online public opinion, take the level of negative information and the propagation level of online public opinion as the calculation objects of the variation control operator, and suppress the propagation of negative information in online public opinion;

[0066] S103: construct a crossover operator with a higher priority for positively guiding online public opinion generation, and reduce the space and speed at which negative information on online public opinion can be spread by positively guiding the spread of online public opinion;

[0067] S104: using a dual-objective optimization evolutionary algorithm to perform iterative optimization operations on the operation object, and obtaining a parameter sequence that maximizes positive guidance and minimizes negative information propagation;

[0068] S105: Regulate the model parameters of online public opinion propagation according to the optimal or suboptimal parameter sequence.

[0069] The above-mentioned embodiments can establish a dual-objective optimization model for the propagation of online public opinion, construct a negative information propagation evaluation model for the propagation of online public opinion, and construct a variation and regulation model for the propagation of negative information for the propagation of online public opinion. The negative information level and propagation level of the propagation of online public opinion are used as calculation objects of the variation and regulation operator to suppress the propagation of negative information of online public opinion, and construct a crossover operator with higher priority for positively guiding the generation of online public opinion. By positively guiding the propagation of online public opinion, the propagation space and speed of negative information of online public opinion are reduced. The dual-objective optimization evolutionary algorithm is used to iteratively optimize the operation object to find the parameter sequence that maximizes positive guidance and minimizes the propagation of negative information. The model parameters of the propagation of online public opinion are regulated according to the optimal or suboptimal parameter sequence, so that the complicated online public opinion propagation analysis and learning system can be quickly and effectively regulated, which greatly saves manpower and computing power loss and reduces the impact of negative information on online public opinion.

[0070] Optionally, the model parameters of the online public opinion propagation include: constraint parameters for the goal of minimizing the propagation of negative information of online public opinion, constraint parameters for maximizing the goal of positively guiding online public opinion, evaluation parameters for the propagation of negative information of online public opinion, variation probability of the propagation of negative information of online public opinion, negative information level parameters for the propagation of online public opinion, propagation level parameters of online public opinion, propagable space parameters of online public opinion, propagation speed parameters of online public opinion, and crossover probability of generating crossover operator by positively guiding online public opinion.

[0071] Optionally, the dual-objective optimization model for the dissemination of online public opinion satisfies the constraint parameter conditions of the goal of minimizing the dissemination of negative information in online public opinion and the constraint parameter conditions of the goal of maximizing the positive guidance of online public opinion. Through the dual-objective evolutionary optimization algorithm, iterative calculation is performed to achieve the basic goal of minimizing the dissemination of negative information in online public opinion and the auxiliary goal of maximizing the positive guidance of online public opinion. Maximizing the positive guidance of online public opinion is an auxiliary means to promote the minimization of the dissemination of negative information in online public opinion.

[0072] Optionally, the negative information propagation evaluation model for online public opinion dissemination is used to evaluate and calculate the negative information propagation fitness function value of online public opinion dissemination to describe the negative information level, propagation level and propagation speed of online public opinion dissemination.

[0073] Optionally, the variation regulation model for the propagation of negative information in the online public opinion dissemination utilizes a dual-objective evolutionary optimization algorithm to perform optimization operations on the object of online public opinion dissemination to obtain an optimal or suboptimal parameter sequence, specifically including: a variation regulation operator operation, which takes the negative information level and propagation level of online public opinion dissemination as the calculation objects of the variation regulation operator to suppress the propagation of negative information in online public opinion; a crossover operator operation for positively guiding online public opinion to generate positively guided online public opinion with a higher priority; an operator operation for optimizing the selection according to the fitness function value; a coordination operator operation between the goal of minimizing the propagation of negative information in online public opinion and the goal of maximizing the positive guidance of online public opinion; and an operation for regulating the parameters of the online public opinion dissemination model according to an optimal or suboptimal parameter sequence.

[0074] In another aspect of the embodiments of the present invention, a dual-objective optimization simulation evolution deduction system for network public opinion propagation is provided, such as Figure 3 As shown, it includes: a dual-objective optimization model construction module for network public opinion dissemination, which is used to establish a dual-objective optimization model for network public opinion dissemination, set the constraint parameters of the network public opinion negative information dissemination minimization target, and the constraint parameters of the network public opinion positive guidance maximization target; a negative information dissemination evaluation model construction module for network public opinion dissemination, which is used to construct a negative information dissemination evaluation model for network public opinion dissemination, set the negative information dissemination evaluation parameters of network public opinion dissemination, the negative information level parameters of network public opinion dissemination, the dissemination level parameters of network public opinion, the propagation space parameters of network public opinion, and the propagation speed parameters of network public opinion, evaluate and calculate the fitness function value of the negative information dissemination of network public opinion dissemination, so as to describe the negative information level, dissemination level and dissemination speed of network public opinion dissemination; a negative information dissemination variation regulation model construction module for network public opinion dissemination, which is used to construct a negative information dissemination variation regulation model for network public opinion dissemination The control model sets the mutation probability of negative information propagation in the online public opinion dissemination, takes the negative information level and propagation level of the online public opinion dissemination as the calculation objects of the mutation control operator, and suppresses the propagation of negative information in the online public opinion; the higher priority positive guidance online public opinion generation crossover operator module sets the crossover probability parameters of the positive guidance online public opinion generation crossover operator, which is used to reduce the propagation space and speed of negative information in the online public opinion by positively guiding the propagation of the online public opinion; the optimal or suboptimal solution solving module of the dual-objective optimization evolutionary algorithm is used to use the dual-objective optimization evolutionary algorithm to iteratively optimize the operation object, and obtain the parameter sequence that maximizes positive guidance and minimizes the propagation of negative information; the online public opinion control module is used to control the model parameters of the online public opinion dissemination according to the optimal or suboptimal parameter sequence, and gradually minimize the impact of negative information in the online public opinion dissemination with the assistance of maximizing positive guidance.

[0075] Optionally, the dual-objective optimization model construction module for the dissemination of online public opinion includes: a constraint parameter setting unit for the goal of minimizing the dissemination of negative information in online public opinion, which is used to set the constraint parameters of the goal of minimizing the dissemination of negative information in online public opinion; and a constraint parameter setting unit for the goal of maximizing the positive guidance of online public opinion, which is used to set the constraint parameters of the goal of maximizing the positive guidance of online public opinion.

[0076] Optionally, the negative information propagation evaluation model construction module for the dissemination of online public opinion includes: a negative information propagation evaluation parameter setting unit for the dissemination of online public opinion, which is used to set the negative information propagation evaluation parameters for the dissemination of online public opinion; a negative information level parameter setting unit for the dissemination of online public opinion, which is used to set the negative information level parameters for the dissemination of online public opinion; a propagation level parameter setting unit for online public opinion, which is used to set the propagation level parameters for online public opinion; a propagation space parameter setting unit for online public opinion, which is used to set the propagation space parameters for online public opinion; and a propagation speed parameter setting unit for online public opinion, which is used to set the propagation speed parameters for online public opinion.

[0077] In an optional embodiment, a dual-objective optimization simulation evolutionary deduction system for the dissemination of online public opinion is provided. This embodiment constructs a dual-objective optimization simulation evolutionary deduction system for the dissemination of online public opinion, the variation regulation of negative information dissemination, and the dissemination of online public opinion based on a dual-objective evolutionary optimization algorithm according to the following steps.

[0078] 1. Design a dual-objective evolutionary optimization algorithm for regulating the spread of negative information on the Internet public opinion

[0079] The dual-objective evolutionary optimization algorithm for the variation regulation of negative information dissemination in online public opinion dissemination has certain bionic multi-objective optimization solving, intelligent search, and evolutionary learning capabilities, such as Figure 4 shown.

[0080] The negative information level IL(F) and the propagation level PL(F) of online public opinion are used as the calculation objects of the mutation control operator M(F) to suppress the spread of negative information of online public opinion.

[0081] M(F)=OP1(IL(F), PL(F)) (1)

[0082] Among them, F represents the negative information feature vector of online public opinion dissemination, IL represents the information level function, IL(F) represents the information level of negative information dissemination of online public opinion, PL represents the dissemination level function, PL(F) represents the dissemination level of negative information dissemination of online public opinion, and OP1 represents the mutation operation function.

[0083] Positive guidance of online public opinion generates a crossover operator C(F,T) operation to generate a higher priority positive guidance of online public opinion O F,T .

[0084] O F,T =C(F,T) (2)

[0085] Among them, F represents the negative information feature vector of online public opinion dissemination, T represents the feature vector of positively guiding online public opinion, and the crossover operator C(F,T) for positively guiding online public opinion generates the feature vector T of positively guiding online public opinion according to the opposing information of the negative information feature vector of online public opinion dissemination, and then generates the positively guiding online public opinion O with higher priority for suppressing the dissemination of negative information of online public opinion. F,T .

[0086] Calculate the fitness function value of the negative information feature vector F of the network public opinion propagation, and select the optimal negative information feature vector of the network public opinion propagation; on the other hand, calculate the positive guidance network public opinion O F,T The fitness function value is used to select the optimal positive way to guide online public opinion.

[0087] Min(f1(F))(3)

[0088] Max(f2(O F,T ))(4) Where, f1(F) represents the fitness function value of the negative information feature vector F of the network public opinion propagation, f2( F,T ) indicates that the positive guidance of online public opinion has a higher priority. F,T The fitness function value of , Min() represents the minimization optimization function, and Max() represents the maximization optimization function.

[0089] The goal of minimizing the spread of negative information in online public opinion and the goal of maximizing the positive guidance of online public opinion are achieved simultaneously. Through the coordination of operator operations and regulation, the goal of minimizing the spread of negative information in online public opinion is the main goal, and the goal of maximizing the positive guidance of online public opinion is the auxiliary goal.

[0090] 2. Construct a Web platform for dual-objective optimization, simulation and evolutionary deduction of online public opinion dissemination

[0091] The Web platform of dual-objective optimization simulation evolutionary deduction of online public opinion propagation can be used to set online the constraint parameters of the objective of minimizing the propagation of negative information of online public opinion and the constraint parameters of the objective of maximizing the objective of positive guidance of online public opinion, and configure the dual-objective optimization model of online public opinion propagation. It can be used to set online the evaluation parameters of negative information propagation of online public opinion propagation, the negative information level parameters of online public opinion propagation, the propagation level parameters of online public opinion, the propagation space parameters of online public opinion, and the propagation speed parameters of online public opinion propagation, configure the evaluation model of negative information propagation of online public opinion propagation, and online evaluate and calculate the fitness function value of negative information propagation of online public opinion propagation. It can be used to set online the variation probability of negative information propagation of online public opinion propagation, configure the variation regulation model of negative information propagation of online public opinion propagation, take the negative information level and propagation level of online public opinion propagation as the calculation objects of the variation regulation operator, and suppress the propagation of negative information of online public opinion. It can be used to set online the crossover probability parameters of the crossover operator of positive guidance of online public opinion generation, configure the crossover operator of positive guidance of online public opinion generation with higher priority, and reduce the propagation space and speed of negative information of online public opinion by positively guiding the propagation of online public opinion. Online optimization calculates the optimal solution or suboptimal solution, which is used to perform iterative optimization operations on the operation object using a dual-objective optimization evolutionary algorithm, and obtain a parameter sequence that maximizes positive guidance and minimizes the spread of negative information. This is then used to regulate the model parameters of the spread of online public opinion, and with the assistance of maximizing positive guidance, gradually minimize the impact of negative information on the spread of online public opinion.

[0092] Obviously, the described embodiments are only some embodiments of the present invention, but not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0093] It should be understood that the above specific embodiments of the present invention are only used to illustrate or explain the principles of the present invention, and do not constitute a limitation of the present invention. Therefore, any modifications, equivalent substitutions, improvements, etc. made without departing from the spirit and scope of the present invention should be included in the protection scope of the present invention. In addition, the appended claims of the present invention are intended to cover all changes and modifications that fall within the scope and boundaries of the appended claims, or the equivalent forms of such scope and boundaries.

Claims

1. A dual-objective optimization simulation evolutionary deduction method for network public opinion propagation, characterized in that: include: Establish a dual-objective optimization model for online public opinion dissemination; Construct a negative information dissemination evaluation model for online public opinion dissemination; Construct a variation regulation model of negative information dissemination in online public opinion dissemination; The level of negative information and the level of dissemination of online public opinion are used as the calculation objects of the variation control operator to suppress the dissemination of negative information of online public opinion. Construct a crossover operator with higher priority to generate positive guidance of online public opinion, and reduce the space and speed of negative information on online public opinion by positively guiding the spread of online public opinion; The bi-objective optimization evolutionary algorithm is used to iteratively optimize the operation object, and the parameter sequence that maximizes positive guidance and minimizes negative information propagation is obtained; The model parameters of online public opinion propagation are regulated according to the optimal or suboptimal parameter sequence.

2. The method according to claim 1, characterized in that The model parameters of the network public opinion propagation include: constraint parameters for minimizing the goal of propagating negative information of network public opinion, constraint parameters for maximizing the goal of positively guiding network public opinion, negative information propagation evaluation parameters for network public opinion propagation, negative information propagation variation probability for network public opinion propagation, negative information level parameters for network public opinion propagation, propagation level parameters for network public opinion, propagable space parameters for network public opinion, propagation speed parameters for network public opinion, and at least any one of the crossover probability of a crossover operator generated by positively guiding network public opinion.

3. The method according to claim 1, characterized in that The dual-objective optimization model for the dissemination of online public opinion meets the constraint parameter conditions of the goal of minimizing the dissemination of negative information in online public opinion and the constraint parameter conditions of the goal of maximizing the positive guidance of online public opinion. Through the dual-objective evolutionary optimization algorithm, iterative calculation is performed to achieve the basic goal of minimizing the dissemination of negative information in online public opinion and the auxiliary goal of maximizing the positive guidance of online public opinion. Maximizing the positive guidance of online public opinion is an auxiliary means to promote the minimization of the dissemination of negative information in online public opinion.

4. The method according to claim 1, characterized in that: The negative information propagation evaluation model for network public opinion propagation is used to evaluate and calculate the negative information propagation fitness function value of network public opinion propagation to describe the negative information level, propagation level and propagation speed of network public opinion propagation.

5. The method according to claim 1, characterized in that The negative information propagation variation control model of network public opinion propagation uses a dual-objective evolutionary optimization algorithm to optimize the network public opinion propagation object and obtain the optimal or suboptimal parameter sequence, which specifically includes: Mutation control operator operation: The level of negative information and the level of propagation of online public opinion are used as the calculation objects of the mutation control operator to suppress the propagation of negative information of online public opinion; Positive guidance of online public opinion generation crossover operator operation: used to generate positive guidance of online public opinion with higher priority; Optimizing and selecting an operator operation according to the fitness function value; The coordination operator operation between the goal of minimizing the spread of negative information on online public opinion and maximizing the goal of guiding positive online public opinion; The operation of regulating the parameters of the network public opinion propagation model according to the optimal or suboptimal parameter sequence.

6. A dual-objective optimization simulation evolutionary deduction system for network public opinion dissemination, characterized in that: include: The dual-objective optimization model construction module of online public opinion dissemination is used to establish a dual-objective optimization model of online public opinion dissemination, set the constraint parameters of the objective of minimizing the dissemination of negative information of online public opinion, and the constraint parameters of the objective of maximizing the positive guidance of online public opinion; The module for constructing the evaluation model of negative information propagation of online public opinion is used to construct the evaluation model of negative information propagation of online public opinion, set the evaluation parameters of negative information propagation of online public opinion, the negative information level parameters of online public opinion, the propagation level parameters of online public opinion, the propagation space parameters of online public opinion, and the propagation speed parameters of online public opinion, evaluate and calculate the fitness function value of negative information propagation of online public opinion, so as to describe the negative information level, propagation level and propagation speed of online public opinion; The module for constructing the variation control model of negative information propagation in online public opinion dissemination is used to construct the variation control model of negative information propagation in online public opinion dissemination, set the variation probability of negative information propagation in online public opinion dissemination, take the negative information level and propagation level of online public opinion dissemination as the calculation objects of the variation control operator, and suppress the spread of negative information in online public opinion dissemination; A higher priority positive guidance network public opinion generation crossover operator module sets the crossover probability parameter of the positive guidance network public opinion generation crossover operator, which is used to reduce the propagation space and speed of negative information of network public opinion by positively guiding the propagation of network public opinion; The optimal or suboptimal solution solving module of the dual-objective optimization evolutionary algorithm is used to use the dual-objective optimization evolutionary algorithm to perform iterative optimization operations on the operation object and obtain a parameter sequence that maximizes positive guidance and minimizes negative information propagation; The network public opinion regulation module is used to regulate the model parameters of network public opinion dissemination according to the optimal or suboptimal parameter sequence, and gradually minimize the impact of negative information in network public opinion dissemination with the assistance of maximizing positive guidance.

7. The system according to claim 6, characterized in that The dual-objective optimization model construction module for network public opinion propagation includes: A constraint parameter setting unit for minimizing the propagation of negative information of online public opinion, used to set the constraint parameters for minimizing the propagation of negative information of online public opinion; The constraint parameter setting unit for maximizing the goal of positively guiding online public opinion is used to set the constraint parameters for maximizing the goal of positively guiding online public opinion.

8. The system according to claim 6, characterized in that The negative information dissemination evaluation model building module of the network public opinion dissemination includes: A negative information dissemination evaluation parameter setting unit for network public opinion dissemination, used to set negative information dissemination evaluation parameters for network public opinion dissemination; A negative information level parameter setting unit for network public opinion dissemination, used to set negative information level parameters for network public opinion dissemination; A network public opinion propagation level parameter setting unit, used to set the network public opinion propagation level parameters; A network public opinion propagation space parameter setting unit, used to set network public opinion propagation space parameters; The network public opinion propagation speed parameter setting unit is used to set the network public opinion propagation speed parameter.

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