CN110808851A - Game theory-based ubiquitous power Internet of things reform behavior selection method - Google Patents
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Abstract
The invention provides a game theory-based ubiquitous power Internet of things reformation behavior selection method, which is used for selecting a ubiquitous power Internet of things reformation behavior and comprises the following steps: constructing a revolutionary behavior model of the ubiquitous power Internet of things, wherein the revolutionary behavior model comprises a first expected model and a second expected model; obtaining a corresponding first replication dynamic equation and a corresponding second replication dynamic equation according to the first expected model and the second expected model; obtaining equilibrium points of the first expected model and the second expected model according to the first replication dynamic equation and the second replication dynamic equation; carrying out stability analysis on the equilibrium points to obtain stable points and stable conditions corresponding to the stable points; according to the method, whether the ubiquitous power internet of things is currently reformed and the best time for reforming can be guided according to the current reforming conditions, so that the reforming failure is avoided, and external benefits of enterprises, governments and the like are prevented from being influenced.
Description
Technical Field
The invention belongs to the field of energy Internet, and relates to a ubiquitous power Internet of things reformation behavior selection method, in particular to a ubiquitous power Internet of things reformation behavior selection method based on a game theory.
Background
The ubiquitous power internet of things refers to an intelligent service system which surrounds all links of a power system, fully applies modern information technologies such as mobile interconnection and artificial intelligence and advanced communication technologies, realizes the internet of everything and man-machine interaction in all the links of the power system, and has the characteristics of comprehensive state sensing, efficient information processing and convenient and flexible application.
The construction content of the ubiquitous power internet of things comprises internal services, external services, data sharing, basic support, technical attack and security protection and the like, along with the integration of an energy revolution and a digital revolution, the construction content of the ubiquitous power internet of things is continuously updated, the number of expanded services is continuously increased, and correspondingly, in order to adapt to the continuously increased construction content, the ubiquitous power internet of things is reformed into a necessary trend.
However, as a new enterprise, the development of the ubiquitous power internet of things is still in an exploration phase, and external support of governments and the like is required at any time, so that the time for reforming the ubiquitous power internet of things is very important, and is directly related to the development of the enterprise and external benefits of governments and the like, and the existing ubiquitous power internet of things enterprise cannot determine whether to reform or not and the specific time for reforming according to the current reforming conditions.
Disclosure of Invention
In order to solve the problems, the invention provides a game theory-based ubiquitous power internet of things reformation behavior selection method which can determine whether power internet of things enterprises reform according to current reformation conditions, and adopts the following technical scheme:
the invention provides a game theory-based ubiquitous power Internet of things reformation behavior selection method, which is used for selecting a ubiquitous power Internet of things reformation behavior and is characterized by comprising the following steps of:
step S1, constructing a reform behavior model of the ubiquitous power Internet of things according to preset model parameters, wherein the reform behavior model comprises a first expected model used for reflecting whether a first party supports reform behaviors and a second expected model used for reflecting whether a second party carries out reform behaviors;
step S2, obtaining a corresponding first replication dynamic equation and a corresponding second replication dynamic equation according to the first expected model and the second expected model;
step S3, obtaining the equilibrium points of the first expected model and the second expected model according to the first replication dynamic equation and the second replication dynamic equation;
step S4, performing stability analysis on the equilibrium points to obtain stable points and stable conditions corresponding to the stable points;
and step S5, determining the reform behavior of the ubiquitous power Internet of things according to the model parameters and the stable conditions.
The game theory-based ubiquitous power internet of things reform behavior selection method provided by the invention can further have the technical characteristics that in the step S1, the first expected model comprises a first supporting expected benefit equation and a first non-supporting expected benefit equation, the second expected model comprises a second supporting expected benefit equation and a second non-supporting expected benefit equation,
the first support expected benefit equation is:
Y1＝y(R+A+B-C)+(1-y)(R-C-D)＝y(A+B+D)+R-C-D，
the first does not support the expected benefit equation:
Y2＝y(R+A+B-D)+(1-y)(R-D)＝y(A+B)+R-D，
Y1expected revenue to support innovation for the first party, Y2The expected benefit for the first party not supporting the reform, y is the ratio of the second party to the reform, R is the current benefit of the first party, A is the direct benefit for the first party to support the reform, B is the indirect benefit for the first party to support the reform, C is the cost for the first party to support the reform, and D is the negative effect for the first party to give up the reform;
the second support expected benefit equation is:
Z1＝x(S+E+F-G)+(1-x)(S+E-G)＝xF+S+E-G，
the second does not support the expected benefit equation:
Z2＝x(S-H)+(1-x)(S-H)＝S-H，
Z1expected yield of innovation for the second party, Z2Expected revenue for the second party not to reform, x is the proportion of the first party that supports the reformS is the current benefit of the second party, E is the positive effect brought by the reform of the second party, F is the support of the first party for the reform of the second party, G is the cost of the reform of the second party, and H is the negative effect of the non-reform of the second party.
The game theory-based ubiquitous power internet of things reform behavior selection method provided by the invention can also have the technical characteristics that in the step S2, the method specifically comprises the following steps:
step S2-1, obtaining the average expectation of the first party and the average expectation of the second party according to the first expectation model and the second expectation model respectively,
the average expectation of the first party is:
Y＝xY1+(1-x)Y2，
the average expectation of the second party is:
Z＝yZ1+(1-y)Z2；
step S2-2, obtaining a first duplicate dynamic equation G (x) and a second duplicate dynamic equation G (y) according to the average expectation of the first party and the average expectation of the second party respectively,
the first replication dynamic equation is:
the second replication dynamic equation is:
t is the reform time.
The game theory-based ubiquitous power internet of things reform behavior selection method provided by the invention can also have the technical characteristics that in the step S3, the method specifically comprises the following steps of;
step S3-1, according to the first replication dynamic equation, it is obtained:
when x is 0, x is 1 or
The probability that the first party supports the reform act is stable,
from the second replication dynamical equation:
when y is 0, y is 1 or
The probability of the second party performing the reform act is stable;
step S3-2, obtaining an equilibrium point from g (x) 0 and g (y) 0, where the equilibrium point is specifically O (0, 0), a (1, 0), B (1, 1), C (0, 1), and D (x, y) satisfies the requirement 
The game theory-based ubiquitous power internet of things reform behavior selection method provided by the invention can also have the technical characteristics that in the step S4, the method specifically comprises the following steps:
step S4-1, differentiating the first replication dynamic equation and the second replication dynamic equation respectively to obtain a Jacobian matrix of the reformed behavior model:
step S4-2, obtaining determinant values Det (J) and traces Tr (J) according to the Jacobian matrix,
the determinant values are:
the traces are:
step S4-3, calculating determinant values Det (J) and traces Tr (J) corresponding to all the equilibrium points;
step S4-4, according to the relationship between the model parameters, judging the sign of the determinant value det (J) and the trace Tr (J) corresponding to each equilibrium point, if the sign of the determinant value det (J) corresponding to the equilibrium point is positive and the sign of the trace Tr (J) is negative, the equilibrium point is stable;
and step S4-5, determining all stable points and stable conditions corresponding to the stable points.
The game theory-based ubiquitous power internet of things reform behavior selection method provided by the invention can also have the technical characteristics that in the step S4-5, the stable points are (0, 0) and (1, 1), the stable condition corresponding to the stable point (0, 0) is S + E + F-G < S-H, and the stable condition corresponding to the stable point (1, 1) is S + E + F-G > S-H and C < D.
The game theory-based ubiquitous power internet of things reform behavior selection method provided by the invention can also have the technical characteristics that in the step S5, the method specifically comprises the following steps: calculating the model parameters, and judging whether the model parameters meet the stable conditions; if not, changing the model parameters to change the value of D (x, y) to achieve a stable condition; if yes, determining which stable condition is met, and determining the corresponding stable point.
The game theory-based ubiquitous power internet of things reformation behavior selection method provided by the invention can also have the technical characteristics that the strategy selection corresponding to the stable point (0, 0) is that the first party does not support the reformation behavior, the second party does not perform the reformation behavior, the strategy selection corresponding to the stable point (1, 1) is that the first party supports the reformation behavior, and the second party performs the reformation behavior.
Action and Effect of the invention
According to the game theory-based ubiquitous power internet of things reform behavior selection method provided by the invention, the first expected model and the second expected model are constructed according to the preset model parameters; obtaining a corresponding first replication dynamic equation and a corresponding second replication dynamic equation according to the first expected model and the second expected model; obtaining equilibrium points of the first expected model and the second expected model according to the first replication dynamic equation and the second replication dynamic equation; carry out stability analysis to the equilibrium point, obtain the stable condition that stable point and stable point correspond, each stable point all corresponds a reform action, consequently, can judge whether current accord with stable condition according to the current model parameter under the current reform condition to and which stable condition accords with, thereby confirm the reform action that corresponds, and then guide the current best opportunity whether to reform and reform at electric power thing networking enterprise, avoid reforming failure, influence external income such as enterprise and government.
Drawings
Fig. 1 is an overall flow chart of a ubiquitous power internet of things reform behavior selection method based on a game theory according to an embodiment of the invention;
fig. 2 is a dynamic evolution diagram of a reformation behavior of the ubiquitous power internet of things reformation behavior selection method based on the game theory in the embodiment of the invention.
Detailed Description
The conception, the specific structure and the technical effects of the present invention will be further described with reference to the accompanying drawings to fully understand the objects, the features and the effects of the present invention.
Fig. 1 is an overall flowchart of a ubiquitous power internet of things reform behavior selection method based on a game theory in the embodiment of the invention.
As shown in fig. 1, an embodiment of the present invention provides a game theory-based method for selecting a behavior of modifying a ubiquitous power internet of things, which is used for selecting a behavior of modifying a ubiquitous power internet of things, and includes the following steps:
step S1, establishing a reform behavior model of the ubiquitous power Internet of things according to preset model parameters, wherein the reform behavior model comprises a first expected model used for reflecting whether a first party supports reform behaviors and a second expected model used for reflecting whether a second party performs reform behaviors.
In this embodiment, the first party is the external world that provides guidance and help to the ubiquitous power thing networking reform, such as government etc., and the second party is the enterprise that carries out the ubiquitous power thing networking reform, and first party and second party are the game both sides in the ubiquitous power thing networking reform promptly.
The model parameters of the first desired model are the expected yield Y of the first party supporting the reform1The first party does not support the expected profit Y of the reform2The ratio y of the second party to reform, the current profit R of the first party, the direct profit A brought by the first party to support the reformation, the indirect profit B brought by the first party to support the reformation, the cost C of the first party to support the reformation, and the negative effect D brought by the first party to give up the reformation
Model parameters of the second desired model are the expected yield Z of the second party's reform1Expected profit Z of the second party without innovation2The ratio x of the first party supporting the reform, the current profit S of the second party, the positive effect E brought by the second party carrying out the reform, the second party carrying out the reform to obtain the support F of the first party, the cost G of the second party carrying out the reform and the negative effect H of the second party not carrying out the reform are disclosed.
According to the ratio x that the first party supports the reformation and the ratio y that the second party carries out the reformation, the ratio that the first party does not support the reformation is 1-x, and the ratio that the second party does not carry out the reformation is 1-y, so that the income matrix of the two parties of the game is obtained, and is shown in table 1.
TABLE 1
In step S1, the first desired model includes a first supported desired benefit equation and a first unsupported desired benefit equation, and the second desired model includes a second supported desired benefit equation and a second unsupported desired benefit equation.
The first support expected benefit equation is:
Y1＝y(R+A+B-C)+(1-y)(R-C-D)＝y(A+B+D)+R-C-D，
the first does not support the expected benefit equation:
Y2＝y(R+A+B-D)+(1-y)(R-D)＝y(A+B)+R-D，
the second support expected benefit equation is:
Z1＝x(S+E+F-G)+(1-x)(S+E-G)＝xF+S+E-G，
the second does not support the expected benefit equation:
Z2＝x(S-H)+(1-x)(S-H)＝S-H。
and step S2, obtaining a corresponding first replication dynamic equation and a corresponding second replication dynamic equation according to the first expected model and the second expected model.
In step S2, the method specifically includes:
step S2-1, obtaining the average expectation of the first party and the average expectation of the second party according to the first expectation model and the second expectation model respectively,
the average expectation of the first party is:
Y＝xY1+(1-x)Y2，
the average expectation of the second party is:
Z＝yZ1+(1-y)Z2；
step S2-2, obtaining a first duplicate dynamic equation G (x) and a second duplicate dynamic equation G (y) according to the average expectation of the first party and the average expectation of the second party respectively,
the first replication dynamic equation is:
the second replication dynamic equation is:
t is the reform time.
In step S3, equilibrium points (equilibrium points) of the first desired model and the second desired model are obtained according to the first replication dynamic equation and the second replication dynamic equation.
In step S3, the method specifically includes:
step S3-1, according to the first replication dynamic equation, it is obtained: when x is 0, x is 1 or
The probability that the first party supports the reform behaviour is stable.
From the second replication dynamical equation: when y is 0, y is 1 or
The probability of the second party performing the reform act is stable.
In step S3-2, an equilibrium point is obtained from g (x) 0 and g (y) 0.
The balance points are O (0, 0), A (1, 0), B (1, 1), C (0, 1) and D (x, y), and D (x, y) satisfies the following conditions
Step S4, performing stability analysis on the equilibrium points to obtain stable points and stable conditions corresponding to the stable points.
In step S4, the method specifically includes:
step S4-1, differentiating the first replication dynamic equation and the second replication dynamic equation respectively to obtain a Jacobian matrix of the reformed behavior model:
step S4-2, obtaining determinant values Det (J) and traces Tr (J) according to the Jacobian matrix,
the determinant value det (j) is:
trace Tr (J) is:
step S4-3, calculating determinant values det (j) and traces tr (j) corresponding to the equalization points, and the calculation results are shown in table 2.
TABLE 2
And step S4-4, judging the signs of the determinant values det (J) and the traces Tr (J) corresponding to the equalization points according to the relationship among the model parameters, and if the signs of the determinant values det (J) corresponding to the equalization points are positive and the signs of the traces Tr (J) are negative, stabilizing the equalization points.
In this embodiment, the relationship between the model parameters is divided into four cases:
in the first case: and when S + E + F-G is less than S-H and C is less than D, the expected benefit of adopting the reforming action by the power grid enterprise is less than the expected benefit of adopting the non-reforming action, and the cost of adopting the reforming action supported by the government is less than the negative effect of adopting the reforming action not supported.
In the second case: and when S + E + F-G is greater than S-H and C is greater than D, the expected benefit of adopting the reforming action by the power grid enterprise is greater than the expected benefit of adopting the non-reforming action, and the cost of adopting the reforming action supported by the government is greater than the negative effect of adopting the reforming action not supported.
In the second case: and when S + E + F-G is less than S-H and C is more than D, the expected benefit of adopting the reforming action by the power grid enterprise is less than the expected benefit of adopting the non-reforming action, and the cost of adopting the reforming action by the government is more than the negative effect of adopting the non-reforming action.
Table 3 shows the stable state of each equalization point for the above three cases.
TABLE 3
In a fourth case: and when S + E + F-G is greater than S-H and C is less than D, the expected benefit of adopting the reforming action by the power grid enterprise is greater than the expected benefit of adopting the non-reforming action, and the cost of adopting the reforming action supported by the government is less than the negative effect of adopting the reforming action not supported.
Table 4 shows the stable state of each equalization point corresponding to the fourth case.
| Balance point | Det(J) | Tr(J) | Results |
| (0,0) | Indefinite article | _ | Instability of the film |
| (0,1) | Indefinite article | Indefinite article | Saddle point |
| (1,0) | + | + | Instability of the film |
| (1,1) | + | _ | Stabilization |
| (x*,y*) | Indefinite article | 0 | Saddle point |
TABLE 4
Step S4-5, determine all stable points and stable conditions corresponding to the stable points, as shown in table 5.
TABLE 5
As can be seen from tables 3 to 5, the stable points are (0, 0) and (1, 1), and the stable conditions for the stable point (0, 0) are S + E + F-G < S-H, and the stable conditions for the stable point (1, 1) are S + E + F-G > S-H and C < D.
Fig. 2 is a dynamic evolution diagram of a reformation behavior of the ubiquitous power internet of things reformation behavior selection method based on the game theory in the embodiment of the invention.
As shown in fig. 2, the dynamic evolution game of the first and second parties has the possibility of reaching (1, 1) equilibrium state, but can converge to (1, 1) or not, depending on which region of the graph OABC the initial state of the system falls, the critical line of the different regions is determined by the connection line of the unstable points a, C and the saddle point D.
And step S5, determining the reform behavior of the ubiquitous power Internet of things according to the model parameters and the stable conditions.
In step S5, the method specifically includes: calculating the model parameters, and judging whether the model parameters meet the stable conditions; if so, determining which stable condition is met, and determining a corresponding stable point; if not, the stable condition can be achieved by changing the model parameters such that the value of D (x, y) changes.
When the initial state falls into the ABCD area on the upper right of the critical line, the evolution system converges on the equilibrium point (1, 1), the strategy corresponding to the stable point (1, 1) is selected as that the first party supports the reform behavior, the second party carries out the reform behavior, and at the moment, the first party and the second party can reach the win-win state.
When the initial state falls into the OADC region at the lower left of the critical line, the system converges to (0, 0), the strategy corresponding to the stable point (0, 0) is selected to be that the first party does not support the reforming action and the second party does not carry out the reforming action, at the moment, if the first party and the second party want to realize the win-win, the value of the saddle point D (x, y) needs to be reduced, even if the initial state falls into the critical lineThe probability of the right upper ABCD region increases since D (x, y) satisfiesThe method can be realized by reducing the cost C for supporting the reform of the first party, the negative effect D brought by the abandonment of the reform of the first party, increasing the support F of the first party obtained by the reform of the second party, or increasing the positive effect E brought by the reform of the second party, the negative effect H not brought by the reform of the second party, and reducing the cost G for the reform of the second party.
Examples effects and effects
According to the game theory-based ubiquitous power internet of things reform behavior selection method provided by the invention, the first expected model and the second expected model are constructed according to the preset model parameters; obtaining a corresponding first replication dynamic equation and a corresponding second replication dynamic equation according to the first expected model and the second expected model; obtaining equilibrium points of the first expected model and the second expected model according to the first replication dynamic equation and the second replication dynamic equation; carry out stability analysis to the equilibrium point, obtain the stable condition that stable point and stable point correspond, each stable point all corresponds a reform action, consequently, can judge whether current accord with stable condition according to the current model parameter under the current reform condition to and which stable condition accords with, thereby confirm the reform action that corresponds, and then guide the current best opportunity whether to reform and reform at electric power thing networking enterprise, avoid reforming failure, influence external income such as enterprise and government.
In this embodiment, since the first expected model includes the first support expected benefit equation and the first non-support expected benefit equation, and the second expected model includes the second support expected benefit equation and the second non-support expected benefit equation, it is possible to determine each model parameter that affects the reformation and the relationship between each model parameter, thereby determining the pros and cons of the reformation on the first party and the second party under the current reformation condition.
In the embodiment, since the average expectation of the first party and the average expectation of the second party are obtained according to the first expectation model and the second expectation model respectively; respectively obtaining a corresponding first replication dynamic equation and a corresponding second replication dynamic equation according to the average expectation of the first party and the average expectation of the second party; according to the first replication dynamic equation and the second replication dynamic equation, the balance points of the first expected model and the second expected model are obtained, so that the dynamic evolution process of the ubiquitous power internet of things reformation can be determined according to the obtained balance points, and the reformation behavior can be determined.
In this embodiment, since the first and second replica dynamic equations are differentiated respectively, a jacobian matrix of the reformed behavior model is obtained: obtaining determinant values and traces according to the Jacobian matrix; calculating determinant values and traces corresponding to the equalizing points; and judging the determinant value and the sign of the trace corresponding to each equilibrium point according to the relationship among the model parameters, wherein if the sign of the determinant value corresponding to the equilibrium point is positive and the sign of the trace is negative, the equilibrium point is stable, so that which equilibrium points are stable points in each equilibrium point can be judged, thereby being convenient for determining the convergence direction and being beneficial to determining the reformation behavior corresponding to the current reformation condition.
In this embodiment, since the model parameters are calculated, whether the stability condition is met is judged; if so, determining which stable condition is met, and determining a corresponding stable point; if not, the model parameters are changed, so that the value of D (x, y) is changed to achieve a stable condition, and therefore, the current reform conditions provided for enterprises and governments can be guided and modified, so that a balanced state is achieved, and win-win of the enterprises and governments is facilitated.
The foregoing detailed description of the preferred embodiments of the invention has been presented. It should be understood that numerous modifications and variations could be devised by those skilled in the art in light of the present teachings without departing from the inventive concepts. Therefore, the technical solutions available to those skilled in the art through logic analysis, reasoning and limited experiments based on the prior art according to the concept of the present invention should be within the scope of protection defined by the claims.
Claims (8)
1. A game theory-based ubiquitous power Internet of things reformation behavior selection method is used for selecting ubiquitous power Internet of things reformation behaviors, and is characterized by comprising the following steps:
step S1, constructing a reform behavior model of the ubiquitous power Internet of things according to preset model parameters, wherein the reform behavior model comprises a first expected model used for reflecting whether a first party supports the reform behavior and a second expected model used for reflecting whether a second party performs the reform behavior;
step S2, obtaining a corresponding first replication dynamic equation and a corresponding second replication dynamic equation according to the first expected model and the second expected model;
step S3, obtaining the equilibrium point of the first expected model and the second expected model according to the first replication dynamic equation and the second replication dynamic equation;
step S4, performing stability analysis on the equilibrium points to obtain stable points and stable conditions corresponding to the stable points;
and S5, determining the reform behavior of the ubiquitous power Internet of things according to the model parameters and the stable conditions.
2. The game theory-based ubiquitous power internet of things reform behavior selection method according to claim 1, wherein:
wherein, in step S1, the first desired model includes a first supported desired benefit equation and a first unsupported desired benefit equation,
the second desired model includes a second supported desired benefit equation and a second unsupported desired benefit equation,
the first support expected benefit equation is:
Y1＝y(R+A+B-C)+(1-y)(R-C-D)＝y(A+B+D)+R-C-D，
the first unsupported expected benefit equation:
Y2＝y(R+A+B-D)+(1-y)(R-D)＝y(A+B)+R-D，
Y1desired revenue, Y, for supporting innovation for the first party2Not supporting change for the first partyThe expected yield of the reform, y is the ratio of the reform performed by the second party, R is the current yield of the first party, A is the direct yield brought by the support of the reform by the first party, B is the indirect yield brought by the support of the reform by the first party, C is the cost of the support of the reform by the first party, and D is the negative effect brought by the abandonment of the reform by the first party;
the second support expected benefit equation is:
Z1＝x(S+E+F-G)+(1-x)(S+E-G)＝xF+S+E-G，
the second does not support the expected benefit equation:
Z2＝x(S-H)+(1-x)(S-H)＝S-H，
Z1expected yield of reform for said second party, Z2For the expected profit that the second party does not reform, x is the proportion that the first party supports the reformation, S is the current profit of the second party, E is the positive effect that the second party carries out the reformation and brings, F is the second party carries out the reformation and obtains the support of the first party, G is the cost that the second party carries out the reformation, H is the negative effect that the second party does not carry out the reformation.
3. The game theory-based ubiquitous power internet of things reform behavior selection method according to claim 2, wherein:
in step S2, the method specifically includes:
step S2-1, obtaining the average expectation of the first party and the average expectation of the second party according to the first expectation model and the second expectation model respectively,
the average expectation of the first party is:
Y＝xY1+(1-x)Y2，
the average expectation of the second party is:
Z＝yZ1+(1-y)Z2；
step S2-2, obtaining the corresponding first replication dynamic equation G (x) and the second replication dynamic equation G (y) according to the average expectation of the first party and the average expectation of the second party respectively,
the first replication dynamic equation is:
the second replication dynamic equation is:
t is the reform time.
4. The game theory-based ubiquitous power internet of things reform behavior selection method according to claim 3, wherein:
specifically, step S3 includes;
step S3-1, obtaining from the first replication dynamic equation:
when x is 0, x is 1 or
The probability that the first party supports the reform behaviour is stable,
obtaining from the second replication dynamic equation:
when y is 0, y is 1 orThe probability of the second party performing the reform act is stable;
a step S3-2 of obtaining the equilibrium point from g (x) 0 and g (y) 0,
said equilibrium points are in particular O (0, 0), A (1, 0), B (1, 1), C (0, 1) and D (x, y),
d (x, y) satisfies
5. The game theory-based ubiquitous power internet of things reform behavior selection method according to claim 4, wherein:
in step S4, the method specifically includes:
step S4-1, differentiating the first replication dynamic equation and the second replication dynamic equation respectively to obtain a jacobian matrix of the reformed behavior model:
step S4-2, obtaining determinant values Det (J) and traces Tr (J) according to the Jacobian matrix,
the determinant values are:
the traces are:
step S4-3, calculating the determinant value Det (J) and the trace Tr (J) corresponding to each equilibrium point;
step S4-4, according to the relationship between the model parameters, judging the symbols of the determinant value Det (J) and the trace Tr (J) corresponding to each equilibrium point,
if the sign of the determinant value det (j) corresponding to the equilibrium point is positive and the sign of the trace tr (j) is negative, the equilibrium point is stable;
and step S4-5, determining all the stable points and the stable conditions corresponding to the stable points.
6. The game theory-based ubiquitous power internet of things reform behavior selection method according to claim 5, wherein:
wherein, in step S4-5, the stable points are (0, 0) and (1, 1),
the stabilization condition for the stabilization point (0, 0) is S + E + F-G < S-H,
the stabilization conditions for the stabilization points (1, 1) are S + E + F-G > S-H and C < D.
7. The game theory-based ubiquitous power internet of things reform behavior selection method according to claim 6, wherein:
in step S5, the method specifically includes:
calculating the model parameters and judging whether the model parameters meet the stable conditions or not;
if not, the stable condition is achieved by changing the model parameters, thereby changing the value of D (x, y);
if yes, determining which stable condition is met, and determining the corresponding stable point.
8. The game theory-based ubiquitous power internet of things reform behavior selection method according to claim 6, wherein:
wherein the strategy corresponding to the stable point (0, 0) is selected such that the first party does not support the reform act and the second party does not perform the reform act,
and the strategy corresponding to the stable point (1, 1) is selected to be that the first party supports the reform action and the second party carries out the reform action.
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113204792A (en) * | 2021-06-03 | 2021-08-03 | 绍兴文理学院 | Internet of things privacy security protection method and system based on evolutionary game |
| CN113344627A (en) * | 2021-06-04 | 2021-09-03 | 哈尔滨商业大学 | Method and device for generating user high-quality content, electronic equipment and storage medium |
Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105120468A (en) * | 2015-07-13 | 2015-12-02 | 华中科技大学 | Dynamic wireless network selection method based on evolutionary game theory |
| CN106844463A (en) * | 2016-12-21 | 2017-06-13 | 湖北大学 | A kind of lsa cache algorithm of pervasive game equilibrium |
| CN108734621A (en) * | 2018-03-23 | 2018-11-02 | 江苏科技大学 | A kind of political affairs production, teaching & research collaborative innovation tripartite's evolutionary Game Analysis method |
| CN108985631A (en) * | 2018-07-18 | 2018-12-11 | 淮阴工学院 | A kind of private car share-car action selection method based on game theory |
| CN109903183A (en) * | 2019-03-06 | 2019-06-18 | 广东电网有限责任公司 | A kind of power distribution network decision-making technique, device and equipment based on tripartite's evolutionary Game |
| CN110111605A (en) * | 2019-06-12 | 2019-08-09 | 吉林大学 | Automatic driving vehicle entrance ring road based on dynamic game travels decision-making technique |
-
2019
- 2019-10-16 CN CN201910983242.XA patent/CN110808851A/en active Pending
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105120468A (en) * | 2015-07-13 | 2015-12-02 | 华中科技大学 | Dynamic wireless network selection method based on evolutionary game theory |
| CN106844463A (en) * | 2016-12-21 | 2017-06-13 | 湖北大学 | A kind of lsa cache algorithm of pervasive game equilibrium |
| CN108734621A (en) * | 2018-03-23 | 2018-11-02 | 江苏科技大学 | A kind of political affairs production, teaching & research collaborative innovation tripartite's evolutionary Game Analysis method |
| CN108985631A (en) * | 2018-07-18 | 2018-12-11 | 淮阴工学院 | A kind of private car share-car action selection method based on game theory |
| CN109903183A (en) * | 2019-03-06 | 2019-06-18 | 广东电网有限责任公司 | A kind of power distribution network decision-making technique, device and equipment based on tripartite's evolutionary Game |
| CN110111605A (en) * | 2019-06-12 | 2019-08-09 | 吉林大学 | Automatic driving vehicle entrance ring road based on dynamic game travels decision-making technique |
Non-Patent Citations (4)
| Title |
|---|
| 吴慧欣等: "网络组织信息共享的演化博弈研究", 《计算机工程与应用》 * |
| 周晶等: "考虑汽车共享的出行方式选择的演化博弈分析", 《营销与服务》 * |
| 张强等: "自然保护区立法中部门合作的演化博弈分析", 《系统工程》 * |
| 王晓天等: "可再生能源发电并网利益协调演化博弈分析", 《系统工程》 * |
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113204792A (en) * | 2021-06-03 | 2021-08-03 | 绍兴文理学院 | Internet of things privacy security protection method and system based on evolutionary game |
| CN113204792B (en) * | 2021-06-03 | 2022-06-10 | 绍兴文理学院 | Internet of things privacy security protection method and system based on evolutionary game |
| CN113344627A (en) * | 2021-06-04 | 2021-09-03 | 哈尔滨商业大学 | Method and device for generating user high-quality content, electronic equipment and storage medium |
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