CN112541623B - Method for acquiring scientific and technological achievement conversion value of double-creation park of power internet of things - Google Patents

Method for acquiring scientific and technological achievement conversion value of double-creation park of power internet of things Download PDF

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CN112541623B
CN112541623B CN202011413521.1A CN202011413521A CN112541623B CN 112541623 B CN112541623 B CN 112541623B CN 202011413521 A CN202011413521 A CN 202011413521A CN 112541623 B CN112541623 B CN 112541623B
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周冬旭
皮一晨
许洪华
张玮亚
刘少君
胡年超
宁艺飞
李存斌
贾雪枫
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Nanjing Power Supply Co of State Grid Jiangsu Electric Power Co Ltd
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Abstract

The invention relates to a method for acquiring a scientific and technological achievement conversion value of a double-wound park of an electric power internet of things, and belongs to the technical field of data processing methods suitable for management prediction. The method comprises the steps of firstly selecting a conversion mode of scientific and technological achievements and constructing indexes, quantifying factors influencing index grading and weighting the indexes, constructing a judgment matrix for pairwise comparison of the indexes, calculating the weight of each index, constructing a grading matrix of the indexes, selecting the conversion mode of the scientific and technological achievements through calculation, respectively modeling a conversion value of the scientific and technological achievements according to different conversion modes, and finally solving to obtain the conversion value of the scientific and technological achievements. According to the method, data of the park cloud management platform are fully utilized, the data utilization rate of an information system is improved, and the maximum scientific and technological achievement conversion value of the double-creation park of the power internet of things can be obtained; and further, research and development work of scientific and technological innovation enterprises can be stimulated, and successful transformation of scientific research achievements is promoted.

Description

Method for acquiring scientific and technological achievement conversion value of double-creation park of power internet of things
Technical Field
The invention relates to a method for acquiring a scientific and technological achievement conversion value of a double-wound park of an electric power internet of things, and belongs to the technical field of data processing methods suitable for management prediction.
Background
The electric power Internet of things double-creation park is a new industrial park which is driven by a collaborative innovation mechanism to carry out industrial complementation and enterprise union to realize high-quality new technology research and development, result conversion and benefit acquisition. The operation of the collaborative innovation double-creation park with the power internet of things as a technical carrier is a brand new business model. The power grid enterprises not only need to be used as innovation subjects to carry out research and development work, but also can play a government role in the traditional industrial park to carry out management support work. The power grid enterprise should serve as a leader to build a park management team of a cross-organization, plan resources of the double-creater in a comprehensive mode, guide and develop research, development, conversion and benefit acquisition of the leading-edge common technology, and reduce information asymmetry and uncertainty in a complex knowledge flow process between the double-creater. However, the collaborative innovation mechanism is still in the starting stage, and there are many problems in the aspects of resource obtaining mechanism, support incentive mode, benefit obtaining mode and the like.
The acquisition of proper scientific and technological achievement conversion benefits can support the research and development work of stimulating scientific and technological innovation enterprises and promote the successful conversion of scientific and technological achievements. Traditional labor-based acquisition or resource-based acquisition cannot objectively evaluate the effort degree of research and development participants, so that the gain is lopsided, enterprise research and development are hindered, and the intelligent upgrading progress of the power industry is slowed down. Therefore, how to objectively quantify benefit influence factors such as the effort degree, innovative resource investment, risk sharing and bargaining capability of research and development participants, how to comprehensively consider multiple factors to perform reasonable conversion of scientific and technological achievements into benefit values, and the like are still problems to be solved urgently.
Disclosure of Invention
The technical problem to be solved by the invention is as follows: the scientific and technological achievement transformation value of the double-creation park of the power internet of things can be clearly and definitely obtained.
The technical scheme provided by the invention for solving the technical problems is as follows: a method for acquiring a scientific and technological achievement conversion value of a double-creation park of an electric power Internet of things comprises the following steps:
step 1: constructing index judgment matrix and calculating index weight
Step 1.1: dividing scientific and technological achievements of the double-creation park of the power internet of things into a first conversion mode dominated by research and development members and a second conversion mode dominated by demand enterprises, wherein the first conversion mode is divided into three conversion modes, and the second conversion mode is divided into two conversion modes; carrying out index quantification on the conversion mode to obtain 4 first-level indexes and 8 second-level indexes;
step 1.2: structural judgment matrix
Constructing a pairwise comparison judgment matrix for 8 secondary indexes as shown in formula (1)
Figure RE-GDA0002949865020000011
Wherein i, j ═ 1,2, …,8, denotes the serial number of the secondary index;
step 1.3: performing consistency check on the judgment matrix, wherein an index CR of the consistency check is obtained by calculating according to formula (2), and if CR is less than 0.1, the consistency check is met;
CR＝[(λ max -m)/(m-1)]/RI (2)，
wherein: lambda [ alpha ] max The maximum eigenvalue of the judgment matrix is obtained, m is the order of the judgment matrix, m is 8, RI represents the average random consistency index of the judgment matrix, and a corresponding numerical value is selected according to the order m of the judgment matrix according to the inherent numerical value in the analytic hierarchy process;
step 1.4: calculating the weight of 8 secondary indexes
The weight w of each index is obtained according to the formula (3) j ，
Figure RE-GDA0002949865020000021
Step 2: constructing a scoring matrix
Step 2.1: designing a grading standard of the secondary indexes, wherein grading standard values of the qualitative indexes are formed by grading by experts, and data of the quantitative indexes are called through a cloud management platform;
step 2.2: calling data of the quantitative index
Setting a scoring matrix system, logically isolating the cloud platform and an internal network and an external network where the scoring matrix system is located by using a gateway, receiving an HTTP request from the scoring matrix system in real time, and configuring a data exchange channel of the cloud platform and the scoring matrix system by means of an HTTP protocol; according to the standard scoring value, related data are called from the cloud management platform and returned to the scoring matrix system, and the returned data are packaged and encrypted; transmitting the data after being packaged and encrypted to an external network from a cloud platform in the form of an xml file by means of a webservice interface, and then performing unpacking and decryption processing on the data and transmitting the data to a scoring matrix system;
step 2.3: data verification
Checking the xml file security in the step 2.2, comprising:
1) checking whether an interface of the xml file contains an sql injection attack code, if so, ending, and if not, performing the next step;
2) checking whether an interface of the xml file contains an xml injection attack code, if so, ending, and if not, continuing the next step;
3) checking whether the interface of the xml file contains the DOS attack or not, if so, ending the operation, and if not, continuing the next step;
4) checking whether an interface of the xml file contains an illegal data field, if so, finishing the data verification, and if not, finishing the data verification;
step 2.4: the qualitative index in the secondary indexes is scored by experts
Step 2.5: constructing a scoring matrix as shown in formula (4) by using the data of the quantitative indexes in the secondary indexes and the numerical values of the qualitative indexes in the secondary indexes obtained by calling in the steps,
Figure RE-GDA0002949865020000022
the element in the scoring matrix of formula (4) is x kj Wherein k represents the kth transformation mode, and j represents the jth index;
and step 3: selection of transformation mode
Step 3.1: calculating the pair x according to equation (5) kj Normalized score z kj
Figure RE-GDA0002949865020000031
Step 3.2: definition of
Figure RE-GDA0002949865020000032
And with
Figure RE-GDA0002949865020000033
Is Z kj The maximum and minimum of the column, i.e.
Figure RE-GDA0002949865020000034
Redefining
Figure RE-GDA0002949865020000035
And
Figure RE-GDA0002949865020000036
in the kth transformation mode and
Figure RE-GDA0002949865020000037
and
Figure RE-GDA0002949865020000038
distance, calculated according to equations (6) and (7), respectively
Figure RE-GDA0002949865020000039
And
Figure RE-GDA00029498650200000310
Figure RE-GDA00029498650200000311
Figure RE-GDA00029498650200000312
step 3.3: the score S of the kth conversion mode is calculated according to the formula (8) k ∈[0,1]，
Figure RE-GDA00029498650200000313
According to S k Selecting the first transformation mode or the second transformation mode in descending order;
and 4, step 4: modeling the scientific and technological achievement conversion value
If the first conversion mode is selected, turning to step 4.1; if the second conversion mode is selected, turning to the step 4.2;
step 4.1: constructing a first benefit obtaining model as formulas (9) and (10)
Figure RE-GDA00029498650200000314
Figure RE-GDA00029498650200000315
Wherein x is n N is 1,2. N represents the number of enterprises related to the first benefit acquisition model, J represents the overall HJB equation of the double-wound park of the power internet of things, and J represents the overall HJB equation of the double-wound park of the power internet of things n Representing an HJB equation of an enterprise of the electric power Internet of things double-zone; e.g. of the type -pt The influence of positive presentation rate is expressed, and the format of the HJB equation is satisfied; ρ represents a positive discount rate e -ρt A relation with the current presentation rate R, ρ ═ ln (1+ R); eta is the income influence coefficient of the conversion progress of the scientific and technological achievements, and eta is greater than 0; theta n Is the marginal gain factor of participating in the transformation enterprise; a is n Cost factor, a, representing the degree of effort n Is greater than 0; pi (K) is the sum of the conversion values of the scientific and technological achievements in the first conversion mode, and pi' (K) is the derivative of pi (K);
step 4.2: constructing a second benefit-obtaining model as in equations (11) - (13)
Figure RE-GDA00029498650200000316
Figure RE-GDA00029498650200000317
Figure RE-GDA0002949865020000041
Where equation (11) is the objective function, p n Is to represent the amount of revenue of the enterprise; wi (r) n Representing the importance degree of the enterprise as a preset constant; p' n Representing a proxy bargaining capability of the enterprise; p represents the total amount of the scientific and technological achievement conversion value in the second conversion mode;
and 5: if the step 4.1 is executed, executing a step 5.1; if the step 4.2 is executed, executing a step 5.2;
step 5.1: calculating according to the formula (22) to obtain the total scientific and technological achievement conversion value of the double-wound parks of the power internet of things, calculating according to the formula (23) to obtain the enterprise scientific and technological achievement conversion value of the double-wound parks of the power internet of things,
Figure RE-GDA0002949865020000042
Figure RE-GDA0002949865020000043
step 5.2: calculating according to the formula (27) to obtain the scientific and technological achievement conversion value of the external enterprises in the double-creation park of the power internet of things,
Figure RE-GDA0002949865020000044
further, the three conversion modes of the first conversion mode are a self-investment implementation conversion mode, a conversion mode which is implemented by taking the scientific and technological achievement as a cooperation condition together with other people and an investment conversion mode which is priced by the scientific and technological achievement, and the two conversion modes of the second conversion mode are a conversion mode which is assigned to other people and a conversion mode which permits other people to use the scientific and technological achievement respectively; the first-level indexes are policy factors, economic factors, social factors and technical factors respectively, and the second-level indexes are government subsidies, fund investment, expected income, risk sharing, participation of research and development members, subsequent achievement affiliation, technical distance and intellectual property affiliation respectively.
Further, in the step 4, the method for solving the HJB equation should adopt a first-order optimality condition of the HJB to solve, and if the first-order optimality condition is not met, the objective function of the method should be adjusted to adapt to the form of the HJB.
Further, the process for obtaining the formulas (22) and (23) in the step 5.1 is as follows,
solving for the right part of equation (10), equation (10) for x n The first order partial derivative is calculated and made equal to zero to obtain equation (14),
Figure RE-GDA0002949865020000045
the formula (14) is reduced to the formula (15),
Figure RE-GDA0002949865020000046
let pi (K) ═ a in equation (15) 1 K(16) (16)，
In formula (15)
Figure RE-GDA0002949865020000047
Wherein a is 1 And a 0 Is a temporary variable, formula (18) is obtained by bringing formula (16) and formula (17) into formula (15),
Figure RE-GDA0002949865020000051
comparison a was determined according to the comparison of formula (18) with formula (16) and formula (17), respectively 1 And a 0 As shown in formula (19) and formula (20),
Figure RE-GDA0002949865020000052
Figure RE-GDA0002949865020000053
bringing formula (19) into formula (14) to obtain formula (21),
Figure RE-GDA0002949865020000054
a is to 1 And a 0 The expressions (22) and (23) can be obtained by bringing the expressions (16) and (17) into consideration, respectively.
Further, the process for obtaining formula (27) in step 5.1 is as follows,
the lagrange function is constructed as equation (24),
Figure RE-GDA0002949865020000055
wherein L represents a Lagrangian function, μ represents a Lagrangian multiplier, w i Representing the degree of importance of the enterprise, p n Representing the amount of revenue, p' n Representing a proxy bargaining capability of the enterprise;
equations (25) and (26) can be derived from the optimality conditions for convex optimization,
Figure RE-GDA0002949865020000056
Figure RE-GDA0002949865020000057
reduction of formula (23) to give p n Equation with μ taken together with equation (25) to give μ and p' n And then mu is compared with p' n Equation substitution of formula (26) to obtain p n And p' n The equation (2) yields equation (27).
The invention has the beneficial effects that: the method can make full use of the data of the cloud management platform of the park, so that the data utilization rate of the information system can be improved; according to the method, the weight of the influence factors of the achievement transformation mode is quantified by adopting a characteristic value method, the appropriate achievement transformation mode is selected by adopting a TOPSIS method, the benefit distribution process in a certain time domain is simulated by means of an HJB equation according to different achievement transformation modes, and the optimal benefit distribution ratio is solved by means of optimality conditions, so that the maximum scientific and technological achievement transformation value of the double-creation park of the power internet of things can be obtained. The result of the method can play a role in supporting the research and development work of scientific and technological innovation enterprises and promoting the successful transformation of scientific research achievements.
Detailed Description
Example 1
The method for obtaining the scientific and technological achievement conversion value of the double-creation park of the power internet of things in the embodiment takes 3 enterprises in the double-creation park of the power internet of things as an example, and comprises the following steps:
step 1: constructing index judgment matrix and calculating index weight
Step 1.1: dividing the scientific and technological achievements of the double-creation park of the power internet of things into a first conversion mode dominated by research and development members and a second conversion mode dominated by demand enterprises, wherein the first conversion mode and the second conversion mode are shown in the following table 1:
TABLE 1 classification of scientific and technological achievements transformation modes
Figure RE-GDA0002949865020000061
The first transformation mode is divided into three transformation modes, and the first transformation mode is divided into two transformation modes; index quantization is performed on the two transformation modes to obtain 4 primary indexes and 8 secondary indexes as shown in the following table 2:
TABLE 2 index Classification of scientific and technological achievement transformation modes
Figure RE-GDA0002949865020000062
Step 1.2: structural judgment matrix
Constructing a pairwise comparison judgment matrix for 8 secondary indexes by experts in combination with a 5-level scaling method as shown in the following formula (1),
Figure RE-GDA0002949865020000063
the formula (1) is specifically
Figure RE-GDA0002949865020000064
The 5-step scale is shown in table 3.
TABLE 3 judge matrix Scale and its implications
Figure RE-GDA0002949865020000065
Figure RE-GDA0002949865020000071
Step 1.3: performing consistency check on the judgment matrix, wherein an index CR of the consistency check is obtained by calculating according to formula (2), and if CR is less than 0.1, the consistency check is met;
CR＝[(λ max -m)/(m-1)]/RI (3)，
wherein: lambda [ alpha ] max Is the maximum characteristic of the decision matrix; m is the order of the judgment matrix, and in this embodiment, m is 8; RI represents an average random consistency index of the determination matrix, and selects a corresponding numerical value according to the order m of the determination matrix according to an inherent numerical value in the analytic hierarchy process, as shown in table 4.
TABLE 4 average random consistency index
Figure RE-GDA0002949865020000072
Maximum eigenvalue lambda of the calculated decision matrix max When RI is 1.41 and CR is 0 <0.1, it is determined that RI is 8The matrix satisfies the consistency check.
Step 1.4: calculating the weight of 8 secondary indexes, and obtaining the weight w of each index according to the formula (3) j ，
Figure RE-GDA0002949865020000073
As can be seen from equation (3), the denominator of the weight is the sum of all elements of the decision matrix, and therefore, all elements of the decision matrix are added, i.e.
Figure RE-GDA0002949865020000074
Meanwhile, the numerator of the formula (3) is the sum of all elements in a certain row of the judgment matrix, that is
Figure RE-GDA0002949865020000075
Figure RE-GDA0002949865020000076
Figure RE-GDA0002949865020000077
Calculating the weight of each index, e.g.
Figure RE-GDA0002949865020000078
Therefore, the weight calculation results for the 8 secondary indicators are as follows:
(w 1 ,w 2 ,w 3 ,w 4 ,w 5 ,w 6 ,w 7 ,w 8 )＝(0.22,0.12,0.11,0.11,0.11,0.11,0.11,0.11)
step 2: constructing a scoring matrix
Step 2.1: designing a scoring standard of the secondary indexes, wherein scoring standard values of the qualitative indexes are formed by scoring by experts, and the quantitative indexes are called through a cloud management platform, as shown in table 5:
standard score values for the indices of Table 5
Figure RE-GDA0002949865020000081
Step 2.2: calling data of the quantitative index
Setting a scoring matrix system, logically isolating the cloud platform and an internal network and an external network where the scoring matrix system is located by using a gateway, receiving an HTTP request from the scoring matrix system in real time, and configuring a data exchange channel of the cloud platform and the scoring matrix system by means of an HTTP protocol; according to the standard scoring values in the table 5, relevant data are called from the cloud management platform and returned to the scoring matrix system, and the returned data are packaged and encrypted; transmitting the data after being packaged and encrypted to an external network from a cloud platform in the form of an xml file by means of a webservice interface, and then performing unpacking and decryption processing on the data and transmitting the data to a scoring matrix system;
step 2.3: data verification
Checking the xml file security in step 2.2, comprising:
1) checking whether an interface of the xml file contains an sql injection attack code, if so, ending, and if not, performing the next step;
2) checking whether an interface of the xml file contains an xml injection attack code, if so, ending, otherwise, continuing the next step;
3) checking whether the interface of the xml file contains the DOS attack or not, if so, ending the operation, and if not, continuing the next step;
4) checking whether an interface of the xml file contains an illegal data field, if so, finishing the data verification, and if not, finishing the data verification;
step 2.4: the qualitative index in the secondary indexes is scored by experts
Step 2.5: constructing a scoring matrix of the quantitative index data in the secondary indexes and the scoring numerical value of the qualitative index in the secondary indexes, which are obtained in the step (4),
Figure RE-GDA0002949865020000091
the formula (4) is specifically
Figure RE-GDA0002949865020000092
And step 3: selecting the first transformation mode or the second transformation mode
Step 3.1: calculating the pair x according to equation (5) kj Normalized score z kj
Figure RE-GDA0002949865020000093
In z 11 The example calculation process is: first, the denominator is calculated
Figure RE-GDA0002949865020000094
B is to be 1 The squares of all elements in a column are summed and squared to give 244, after which z is calculated using the elements in row 1, column 1 as numerator 11 Value of (2) 4.054 × 10 -2 Calculating all z in turn kj The results are as follows.
Figure RE-GDA0002949865020000095
Step 3.2: definition of
Figure RE-GDA0002949865020000096
And
Figure RE-GDA0002949865020000097
is z kj The maximum and minimum of the column, i.e.
Figure RE-GDA0002949865020000098
Redefining
Figure RE-GDA0002949865020000099
And with
Figure RE-GDA00029498650200000910
In the kth transformation mode and
Figure RE-GDA00029498650200000911
and
Figure RE-GDA00029498650200000912
distance, calculated according to equations (6) and (7), respectively
Figure RE-GDA00029498650200000913
And
Figure RE-GDA00029498650200000914
Figure RE-GDA00029498650200000915
Figure RE-GDA00029498650200000916
first, z is selected j + And z j - ，z j + Is the maximum value, z, of each column of the matrix of formula (6) j - Is the minimum value of each column of the matrix of equation (6), and the results are as follows.
Figure RE-GDA00029498650200000917
Then calculate
Figure RE-GDA00029498650200000918
And
Figure RE-GDA00029498650200000919
and
Figure RE-GDA00029498650200000920
means that each index is scored to
Figure RE-GDA00029498650200000921
And
Figure RE-GDA00029498650200000922
weighted euclidean distance of. Take k as 1 for example
Figure RE-GDA00029498650200000923
And
Figure RE-GDA00029498650200000924
the following were used:
Figure RE-GDA0002949865020000101
Figure RE-GDA0002949865020000102
can calculate all
Figure RE-GDA0002949865020000103
And
Figure RE-GDA0002949865020000104
the calculation results are as follows.
Figure RE-GDA0002949865020000105
Figure RE-GDA0002949865020000106
Step 3.3: the score S of the kth transformation method is calculated according to the formula (8) k ∈[0,1]，
Figure RE-GDA0002949865020000107
With S 1 The calculation procedure for example is as follows
Figure RE-GDA0002949865020000108
All S can be calculated by the same method k The results are as follows
S k ＝(0.8617,0.9746,0.6272,0.4181,0.6272)，
According to S k In descending order, K should be 1, i.e., the first conversion method is selected.
And 4, step 4: modeling scientific achievement conversion value
Step 4.1: constructing a first benefit obtaining model as formulas (9) and (10)
Figure RE-GDA0002949865020000109
Figure RE-GDA00029498650200001010
From the result of step 3, it is known that a first conversion scheme with K equal to 1, N equal to 3, model parameters ρ equal to 0.2, δ equal to 0.2, η equal to 0.3, and K (0) equal to K, should be selected 0 ＝2,α＝(0.3,0.4,0.5),λ＝(0.2,0.3,0.4),θ＝(0.5,0.6,0.7)。
And 5: solving the conversion value of scientific and technological achievements
Step 5.1: solving for the right part of equation (10), equation (10) for x n The first order partial derivative is calculated, and the partial derivative result is equal to zero, and the formula (14) is obtained by simplification,
Figure RE-GDA0002949865020000111
the formula (14) is reduced to the formula (15),
Figure RE-GDA0002949865020000112
let pi (K) ═ a in equation (15) 1 K(16) (16)，
In equation (15)
Figure RE-GDA0002949865020000113
Wherein a is 1 And a 0 Is a temporary variable, formula (18) is obtained by bringing formula (16) and formula (17) into formula (15),
Figure RE-GDA0002949865020000114
comparison a was determined according to the comparison of formula (18) with formula (16) and formula (17), respectively 1 And a 0 As shown in formula (19) and formula (20),
Figure RE-GDA0002949865020000115
Figure RE-GDA0002949865020000116
bringing formula (19) into formula (14) to obtain formula (21),
Figure RE-GDA0002949865020000117
a is to 1 And a 0 The formula (22) and the formula (23) can be obtained by bringing the formula (16) and the formula (17) into consideration,
Figure RE-GDA0002949865020000118
Figure RE-GDA0002949865020000121
calculating according to the formula (22) to obtain a total scientific and technological achievement conversion value of 19.7 (unit: ten thousand yuan) of the double-creation park of the power internet of things,
the process of calculating the conversion values of the scientific and technological achievements of 3 enterprises in the double-creation park of the power internet of things according to the formula (23) is as follows:
first, ρ is 0.2, δ is 0.2, η is 0.3, and K (0) is K 0 When α is 2, α is (0.3,0.4,0.5), λ is (0.2,0.3,0.4), θ is (0.5,0.6,0.7), wn is (0.25,0.35,0.4), and t is 30, the method is applicable
Figure RE-GDA0002949865020000122
Figure RE-GDA0002949865020000123
Meanwhile, according to the specification of the HJB equation, the method can be known
Figure RE-GDA0002949865020000124
Bringing the above calculated values available:
Figure RE-GDA0002949865020000125
the conversion value (unit: ten thousand yuan) of the scientific and technological achievements of the 3 enterprises participating in the conversion is calculated as follows:
Figure RE-GDA0002949865020000126
Figure RE-GDA0002949865020000127
Figure RE-GDA0002949865020000131
therefore, the conversion values of scientific and technological achievements of 3 enterprises are 4.926 ten thousand yuan, 6.896 ten thousand yuan and 7.881 ten thousand yuan respectively.
Example 2: this example is a modification of example 1, except that the same as example 1:
step 2.5: the scoring matrix is specifically
Figure RE-GDA0002949865020000132
And step 3: selecting the first transformation mode or the second transformation mode
Step 3.1: calculating the pair x according to equation (5) kj Normalized score z kj In z is 11 For example, B 1 The squares of all elements in a column are summed and squared to 121.655, after which z is calculated using the element in row 1, column 1 as the numerator 11 Is 1.351 × 10 -2 Calculating all z in turn kj The results are as follows.
Figure RE-GDA0002949865020000133
Step 3.2: calculated according to equations (6) and (7)
Figure RE-GDA0002949865020000134
And
Figure RE-GDA0002949865020000135
first, z is selected j + And z j - The results are as follows,
Figure RE-GDA0002949865020000136
then calculate
Figure RE-GDA0002949865020000137
And
Figure RE-GDA0002949865020000138
take k as 1 for example
Figure RE-GDA0002949865020000139
And
Figure RE-GDA00029498650200001310
the following were used:
Figure RE-GDA0002949865020000141
Figure RE-GDA0002949865020000142
therefore all of
Figure RE-GDA0002949865020000143
And
Figure RE-GDA0002949865020000144
has the following values
Figure RE-GDA0002949865020000145
Figure RE-GDA0002949865020000146
Step 3.3: calculating S according to equation (8) k With S 1 The calculation is as follows for the sake of example,
Figure RE-GDA0002949865020000147
thus all S are calculated k The following were used:
S k ＝(0.3615,0.5186,0.703,0.6392,0.8951)，
according to S k The descending order of (a) indicates that K ═ 2 should be selected, i.e., the second transformation mode should be selected.
And 4, step 4: modeling scientific achievement conversion value
Step 4.2: constructing a second benefit-obtaining model as in equations (11) - (13)
Figure RE-GDA0002949865020000148
Figure RE-GDA0002949865020000149
Figure RE-GDA00029498650200001410
Where equation (11) is the objective function, p n Is to represent the amount of revenue of the enterprise; wi represents the importance degree of the enterprise and is a preset constant; p' n Representing a proxy bargaining capability of the enterprise; p represents the total amount of the scientific and technological achievement conversion value in the second conversion mode;
wi＝(0.25,0.35,0.4),p′＝(5,7,8,P＝22。
and 5: solving the conversion value of scientific and technological achievements
Step 5.2: the lagrange function is constructed as equation (24),
Figure RE-GDA0002949865020000151
wherein L represents the Lagrangian function, μ represents the Lagrangian multiplier, w i Representing the degree of importance of the enterprise, p n Denotes the amount of revenue, p' n Representing a proxy bargaining capability of the enterprise;
equations (23) and (24) can be derived from the optimality conditions for convex optimization,
Figure RE-GDA0002949865020000152
Figure RE-GDA0002949865020000153
reduction of formula (24) to give p i Equation p with μ n ＝p′ n +wi n Mu, with formula (25) to give mu and p' i Is that
Figure RE-GDA0002949865020000154
By substituting formula (26) with p i And p' i Is given by the equation (27),
Figure RE-GDA0002949865020000155
the conversion value (unit: ten thousand yuan) of scientific and technological achievements of 3 enterprises is calculated according to the formula (27) as follows:
Figure RE-GDA0002949865020000156
therefore, the conversion values of the scientific and technological achievements of 3 enterprises are 5.5 ten thousand yuan, 7.7 ten thousand yuan and 8.8 ten thousand yuan respectively.
The above description is only for the preferred embodiment of the present invention, but the present invention is not limited thereto, for example: 1) the number of the participating enterprises in the scientific and technological achievement conversion is not only 3, but also 2, 4, 5 or other numbers; 2) the scientific and technological achievement transformation mode can be other modes besides the two transformation modes given in the above embodiments. All equivalents and modifications of the inventive concept and its technical solutions are intended to be included within the scope of the present invention.

Claims (4)

1. A method for obtaining a scientific and technological achievement conversion value of a double-creation park of an electric power Internet of things is characterized by comprising the following steps:
step 1: constructing index judgment matrix and calculating index weight
Step 1.1: dividing scientific and technological achievements of the double-creation park of the power internet of things into a first conversion mode dominated by research and development members and a second conversion mode dominated by demand enterprises, wherein the first conversion mode is divided into three conversion modes, and the second conversion mode is divided into two conversion modes; carrying out index quantification on the conversion mode to obtain 4 first-level indexes and 8 second-level indexes; the three conversion modes of the first conversion mode are a self-investment implementation conversion mode, a conversion mode which is implemented by taking the scientific and technological achievement as a cooperation condition together with other people and an investment conversion mode which is priced by the scientific and technological achievement, and the two conversion modes of the second conversion mode are a conversion mode which transfers the scientific and technological achievement to other people and a conversion mode which permits other people to use the scientific and technological achievement respectively; the first-level indexes are policy factors, economic factors, social factors and technical factors respectively, and the second-level indexes are government subsidies, fund investment, expected income, risk sharing, participation of research and development members, subsequent achievement affiliation, technical distance and intellectual property affiliation respectively;
step 1.2: structural judgment matrix
Constructing a pairwise comparison judgment matrix for 8 secondary indexes as shown in formula (1)
Figure FDA0003643492380000011
Wherein i, j ═ 1,2, …,8, denotes the serial number of the secondary index;
step 1.3: performing consistency check on the judgment matrix, wherein an index CR of the consistency check is obtained by calculating according to formula (2), and if CR is less than 0.1, the consistency check is met;
CR＝[(λ max -m)/(m-1)]/RI (2)，
wherein: lambda [ alpha ] max The maximum eigenvalue of the judgment matrix is obtained, m is the order of the judgment matrix, m is 8, RI represents the average random consistency index of the judgment matrix, and a corresponding numerical value is selected according to the order m of the judgment matrix according to the inherent numerical value in the analytic hierarchy process;
step 1.4: calculating the weight of 8 secondary indexes
The weight w of each index is obtained according to the formula (3) j ，
Figure FDA0003643492380000012
Step 2: constructing a scoring matrix
Step 2.1: designing a grading standard of the secondary indexes, wherein grading standard values of the qualitative indexes are formed by grading by experts, and data of the quantitative indexes are called through a cloud management platform;
step 2.2: calling data of the quantitative index
Setting a scoring matrix system, logically isolating the cloud platform and an internal network and an external network where the scoring matrix system is located by using a gateway, receiving an HTTP request from the scoring matrix system in real time, and configuring a data exchange channel of the cloud platform and the scoring matrix system by means of an HTTP protocol; according to the standard scoring value, related data are called from the cloud management platform and returned to the scoring matrix system, and the returned data are packaged and encrypted; transmitting the data after being packaged and encrypted to an external network from a cloud platform in the form of an xml file by means of a webservice interface, and then performing unpacking and decryption processing on the data and transmitting the data to a scoring matrix system;
step 2.3: data verification
Checking the xml file security in the step 2.2, comprising:
1) checking whether an interface of the xml file contains an sql injection attack code, if so, ending, and if not, performing the next step;
2) checking whether an interface of the xml file contains an xml injection attack code, if so, ending, otherwise, continuing the next step;
3) checking whether the interface of the xml file contains the DOS attack or not, if so, ending the operation, and if not, continuing the next step;
4) checking whether an interface of the xml file contains an illegal data field, if so, finishing the data verification, and if not, finishing the data verification;
step 2.4: the qualitative index in the secondary indexes is scored by experts
Step 2.5: constructing a scoring matrix as shown in formula (4) by using the data of the quantitative indexes in the secondary indexes and the numerical values of the qualitative indexes in the secondary indexes obtained by calling in the steps,
Figure FDA0003643492380000021
the element in the scoring matrix of formula (4) is x kj Wherein k represents the kth transformation mode, and j represents the jth index;
and step 3: selection of transformation means
Step 3.1: calculating the pair x according to equation (5) kj Normalized score z kj
Figure FDA0003643492380000022
Step 3.2: definition of z j + And z j - Is z kj The maximum and minimum of the column of (1), i.e. z j + ＝max k {z kj }，z j - ＝min k {z kj Is redefined
Figure FDA0003643492380000023
And
Figure FDA0003643492380000024
is the kth transformation mode with z j + And z j - Distance, calculated according to equations (6) and (7), respectively
Figure FDA0003643492380000025
And
Figure FDA0003643492380000026
Figure FDA0003643492380000027
Figure FDA0003643492380000031
step 3.3: the score S of the kth transformation method is calculated according to the formula (8) k ∈[0,1]，
Figure FDA0003643492380000032
According to S k Selecting the first transformation mode or the second transformation mode in descending order;
and 4, step 4: modeling the scientific and technological achievement conversion value
If the first conversion mode is selected, turning to step 4.1; if the second conversion mode is selected, turning to the step 4.2;
step 4.1: constructing a first benefit obtaining model as formulas (9) and (10)
Figure FDA0003643492380000033
Figure FDA0003643492380000034
Wherein x is n N is 1,2. N represents the number of enterprises related to the first benefit acquisition model, J represents the overall HJB equation of the double-wound park of the power internet of things, and J represents the overall HJB equation of the double-wound park of the power internet of things n The HJB equation of the enterprises in the double-zone garden of the power Internet of things is expressed; e.g. of the type -pt The influence of positive presentation rate is expressed, and the format of the HJB equation is satisfied; ρ represents a positive discount rate e -ρt A relation with the current presentation rate R, ρ ═ ln (1+ R); eta is the income influence coefficient of the conversion progress of the scientific and technological achievements, and eta is greater than 0; theta n Is the marginal profit coefficient of the participating transformation enterprises; a is n Cost factor, a, representing the degree of effort n Is greater than 0; pi (K) is the sum of the conversion values of the scientific and technological achievements in the first conversion mode, and pi' (K) is the derivative of pi (K);
step 4.2: constructing a second benefit-obtaining model as in equations (11) - (13)
Figure FDA0003643492380000035
Figure FDA0003643492380000036
Figure FDA0003643492380000037
Where equation (11) is the objective function, p n Is to represent the amount of revenue of the enterprise; wi (r) n Representing the importance degree of the enterprise as a preset constant; p' n Representing a proxy bargaining capability of the enterprise; p represents the total amount of the scientific and technological achievement conversion value in the second conversion mode;
and 5: if the step 4.1 is executed, executing a step 5.1; if the step 4.2 is executed, executing a step 5.2;
step 5.1: calculating according to the formula (22) to obtain the total scientific and technological achievement conversion value of the double-wound parks of the power internet of things, calculating according to the formula (23) to obtain the enterprise scientific and technological achievement conversion value of the double-wound parks of the power internet of things,
Figure FDA0003643492380000041
Figure FDA0003643492380000042
step 5.2: calculating according to the formula (27) to obtain the scientific and technological achievement conversion value of the external enterprises in the double-creation park of the power internet of things,
Figure FDA0003643492380000043
2. the method for acquiring the scientific and technological achievement conversion value of the power internet of things double-wound park according to claim 1, is characterized in that: in the step 4, the method for solving the HJB equation is to solve by adopting a first-order optimality condition of the HJB, and if the first-order optimality condition is not met, the objective function of the method is adjusted to adapt to the form of the HJB.
3. The method for acquiring the scientific and technological achievement conversion value of the power internet of things double-wound park according to claim 1, is characterized in that: the process for obtaining formulae (22) and (23) in said step 5.1 is as follows,
solving for the right part of equation (10), equation (10) for x n The first order partial derivative is calculated and made equal to zero to obtain the formula (14),
Figure FDA0003643492380000044
the formula (14) is reduced to the formula (15),
Figure FDA0003643492380000045
let pi (K) ═ a in equation (15) 1 K(16) (16)，
In equation (15)
Figure FDA0003643492380000046
Wherein a is 1 And a 0 Is a temporary variable, formula (18) is obtained by bringing formula (16) and formula (17) into formula (15),
Figure FDA0003643492380000047
comparison of formula (18) with formula (16) and formula (17) to determine a comparison a 1 And a 0 As shown in formulas (19) andthe compound of the formula (20),
Figure FDA0003643492380000048
Figure FDA0003643492380000051
bringing formula (19) into formula (14) to obtain formula (21),
Figure FDA0003643492380000052
a is to 1 And a 0 The expressions (22) and (23) can be obtained by bringing the expressions (16) and (17) into consideration, respectively.
4. The method for acquiring the scientific and technological achievement conversion value of the power internet of things double-wound park according to claim 1, is characterized in that: the procedure for obtaining formula (27) in said step 5.1 is as follows,
the lagrange function is constructed as equation (24),
Figure FDA0003643492380000053
wherein L represents the Lagrangian function, μ represents the Lagrangian multiplier, w i Representing the degree of importance of the enterprise, p n Representing the amount of revenue, p' n Representing a proxy bargaining capability of the enterprise;
equations (25) and (26) can be derived from the optimality conditions for convex optimization,
Figure FDA0003643492380000054
Figure FDA0003643492380000055
reduction of formula (23) to give p n Equation with μ taken together with equation (25) to give μ and p' n And then mu is compared with p' n Equation substitution of formula (26) to obtain p n And p' n The equation (2) yields equation (27).
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