Development project cost evaluation method and device based on improved grey correlation analysis

Abstract

The invention provides a development project cost evaluation method and device based on improved grey correlation analysis, and belongs to the technical field of data processing. The method comprises the following steps: determining pricing indexes and pricing index weights corresponding to science and technology projects by using an expert evaluation method and an analytic hierarchy process; an important pricing index corresponding to the development project cost is screened by using a grey correlation analysis method and each pricing index weight; and performing project cost calculation according to the important pricing indexes. In the process, factors with relatively low contribution degree are eliminated, so that the benefit of model calculation is increased, and the accuracy of cost calculation is improved. And in combination with expert evaluation and an analytic hierarchy process, the importance of pricing indexes is reasonably embodied. According to the method, a grey correlation analysis method and pricing index weights are utilized to screen out important indexes having significant influence on the project cost, and accurate cost calculation is carried out according to the important indexes, so that the evaluation efficiency and accuracy are improved.

Description

Technical Field

[0001] The invention relates to the technical field of data processing, in particular to the technical field of electric power, and in particular to a method and a device for evaluating development project costs based on improved grey correlation analysis. Background Art

[0002] The emphasis on technological innovation has prompted enterprises to increase their investment in scientific research. The key lies in determining the reasonable cost of scientific and technological projects. State Grid Corporation of China has conducted in-depth research on the pricing methods of scientific and technological projects, which not only improves project and financial management, but also aligns with the development direction of scientific and technological innovation and supports the development of high-quality scientific and technological innovation projects. These efforts reflect the decision of enterprises to pursue high-quality development under the new economic situation, and play a key role in the transformation of energy structure, digitalization process, improvement of international competitiveness and scientific and technological innovation.

[0003] At present, enterprises still face many challenges in the evaluation of scientific research project costs: first, there is a lack of mature quota application methods and cost evaluation indicators for scientific and technological projects, and the recognition standards and cost levels of project costs and output results still need further research; second, in the process of project cost evaluation, the identification and cognition of the innovative point of using gray correlation analysis to evaluate development project costs is not in-depth, resulting in a deviation between the evaluation results and the actual R&D cost efficiency; in addition, the process and mechanism of project cost evaluation are not perfect, and there is a lack of effective monitoring and adjustment mechanisms, which makes it difficult to control costs during project execution. Therefore, in terms of enterprise science and technology project cost evaluation, it is necessary to provide an optimized evaluation model to solve the problem that the existing evaluation model performs poorly in evaluating benefit efficiency and the economic rationality of scientific research funds. Summary of the invention

[0004] The embodiment of the present invention provides a development project cost evaluation method and device based on improved grey correlation analysis to solve the problem that the existing evaluation model performs poorly in evaluating benefit efficiency and economic rationality of scientific research funds.

[0005] In a first aspect, an embodiment of the present invention provides a development project cost assessment method based on improved grey correlation analysis, comprising:

[0006] Use expert evaluation method and analytic hierarchy process to determine the pricing indicators and weights of the corresponding scientific and technological projects;

[0007] Use grey correlation analysis and the weights of various pricing indicators to screen important pricing indicators corresponding to development project costs;

[0008] Calculate project costs based on the important pricing indicators mentioned above.

[0009] In a possible implementation, the method of using the expert evaluation method and the analytic hierarchy process to determine the pricing indicators and the weights of the pricing indicators corresponding to the scientific and technological projects includes:

[0010] Design a pricing index evaluation system corresponding to each type of scientific and technological project based on the expert evaluation method; wherein the types of scientific and technological projects include: theoretical method scientific research projects, platform software scientific research projects, and hardware R&D scientific research projects; the pricing index evaluation system includes multiple layers of pricing indexes corresponding to the types of scientific and technological projects;

[0011] The weight of each pricing indicator in the pricing indicator evaluation system is determined through the hierarchical analysis method.

[0012] In a possible implementation, determining the weight of each pricing indicator in the pricing indicator evaluation system by using the hierarchical analysis method includes:

[0013] Use the analytic hierarchy process to establish a judgment matrix;

[0014] Verify the consistency of the judgment matrix;

[0015] When the judgment matrix passes the consistency test, the square root method is used to solve the weight of each indicator to determine the weight of each indicator;

[0016] Otherwise, the matrix data is corrected or the matrix order is reduced, and the steps of establishing the judgment matrix using the hierarchical analysis method are repeated.

[0017] In a possible implementation, the use of the analytic hierarchy process to establish a judgment matrix includes:

[0018] According to the relative importance of the current layer pricing indicator to a certain pricing indicator of the previous layer, the initial weight of the current layer pricing indicator is determined; the higher the relative importance, the greater the corresponding weight;

[0019] A judgment matrix is ​​constructed based on the initial weights of each pricing indicator.

[0020] In a possible implementation, when checking the consistency of the judgment matrix, the calculation formula is:

[0021]

[0022] Where CI is the consistency of the judgment matrix; the larger the CI value, the worse the consistency of the judgment matrix; n is the order; λ max is the maximum eigenvalue of the judgment matrix; B i is the i-th row vector of the judgment matrix; w and w i They are the weight of the pricing indicator and the absolute weight of the pricing indicator in the current layer respectively.

[0023] In one possible implementation, corresponding to different types of scientific and technological projects, the pricing indicator evaluation system includes three layers;

[0024] The method of using the square root method to solve the weight of each indicator to determine the weight of each indicator includes:

[0025] Calculate the nth root of the product of the importance of each indicator in each row of the judgment matrix in, a ij is the element in the judgment matrix, n is the order of the judgment matrix, is the nth root of the product of the elements in the i-th row of the judgment matrix;

[0026] Pair Vector Normalize to w=(w1,w2,....w n );in,

[0027] After calculation, the weight of each indicator in the second-level judgment matrix is ​​w B =(w B1 ,w B2 ,w B3 ,w B4 );

[0028] The weight of each indicator in the third layer judgment matrix is ​​w C =(w C1 ,w C2 ,w C3 ,w C4 .....,w C15 ).

[0029] In a possible implementation, the gray correlation analysis method and the weights of various pricing indicators are used to screen important pricing indicators corresponding to the development project costs, including:

[0030] Set up a reference sequence and a comparison index sequence; among them, the total cost of the project is set as the reference sequence; the index factors affecting the cost are set as the comparison index sequence;

[0031] Calculate the correlation between the reference sequence and each indicator;

[0032] By comparing the correlation, the indicators with greater contribution are selected as important pricing indicators, and the indicators with smaller contribution are eliminated.

[0033] In a possible implementation, the calculating of project costs according to the important pricing indicators includes:

[0034] Substitute the sample values ​​of the selected important pricing indicators into the calculation model for calculation;

[0035] When the error does not reach the ideal value, the genetic algorithm is used to continuously optimize the measurement model parameters;

[0036] When the error reaches the ideal value, the measurement model parameters are determined and the actual project cost is estimated.

[0037] In a possible implementation, the calculation model is:

[0038] y=β0+β1x1+.....+β k x k

[0039] Among them, Y = Xβ + ε is the matrix expression of the measurement model; ε is the error term; and it satisfies E(ε) = 0; COV(ε,ε) = σ 2 I n ;I n is an n-order unit matrix; k represents the total number of important pricing indicators;

[0040] Each indicator that affects project cost has n sample values.

[0041] In a second aspect, an embodiment of the present invention provides a development project cost assessment device based on improved grey correlation analysis, comprising:

[0042] The determination module is used to determine the pricing indicators and pricing indicator weights corresponding to the scientific and technological projects by using the expert evaluation method and the hierarchical analysis method;

[0043] The screening module is used to screen the important pricing indicators corresponding to the development project costs by using the grey correlation analysis method and the weights of each pricing indicator;

[0044] The calculation module is used to calculate the project cost according to the important pricing indicators.

[0045] The present invention proposes a method and device for evaluating the cost of development projects based on improved grey correlation analysis. It adopts a combination of expert evaluation method and hierarchical analysis method to identify and determine various pricing indicators in scientific and technological projects, and further determines the weights of these pricing indicators to ensure that the importance of each pricing indicator in the evaluation process is reasonably reflected. Subsequently, through the grey correlation analysis method, combined with the previously determined pricing indicator weights, the important pricing indicators that have a significant impact on the cost of the development project are screened out, and those factors that have a low contribution to the project cost are excluded, reducing the interference of these indicators on the cost evaluation. Based on the important pricing indicators screened out, the project cost is accurately calculated, thereby improving the efficiency and accuracy of the evaluation. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings required for use in the embodiments or the description of the prior art 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 paying creative work.

[0047] Figure 1 It is a flow chart of a development project cost evaluation method based on improved grey correlation analysis provided by one embodiment of the present invention;

[0048] Figure 2 It is a flowchart for implementing the method of determining the pricing indicators and the weights of the pricing indicators corresponding to the scientific and technological projects by using the expert evaluation method and the analytic hierarchy process according to one embodiment of the present invention;

[0049] Figure 3 This is a flowchart for implementing the method of screening important pricing indicators for project cost estimation provided by an embodiment of the present invention;

[0050] Figure 4 It is a structural schematic diagram of a development project cost assessment device based on improved grey correlation analysis provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0051] In the following description, specific details such as specific system structures, technologies, etc. are provided for the purpose of illustration rather than limitation, so as to provide a thorough understanding of the embodiments of the present invention. However, it should be clear to those skilled in the art that the present invention may be implemented in other embodiments without these specific details. In other cases, detailed descriptions of well-known systems, devices, circuits, and methods are omitted to prevent unnecessary details from obstructing the description of the present invention.

[0052] By establishing a systematic scientific research project cost evaluation system, we can accurately predict and control the cost of scientific research projects, improve the efficiency and effectiveness of scientific research project process management, promote the reasonable calculation of scientific research project funds and the improvement of corporate scientific and technological innovation and scientific research capabilities, and provide guarantees for the improvement of the efficiency of the use of innovation funds. Therefore, it is of great practical significance and value to carry out research on cost measurement indicators and evaluation methods for scientific and technological research and development projects.

[0053] In the current context, the direct benefit of the research and practice of the cost evaluation method of scientific and technological projects is that it can more accurately predict and control the cost of scientific research projects, thereby significantly improving the efficiency of the use of scientific research funds and the return on investment of scientific research projects. In addition, this method helps to reduce the financial risks caused by inaccurate cost forecasting and ensure the rational allocation of funds. The indirect benefit is reflected in the improvement of the overall management ability of the enterprise, which is specifically manifested in strengthening the systematic management and monitoring of scientific and technological innovation activities and promoting the development of corporate culture in the direction of innovation and efficiency priority. More importantly, scientific cost evaluation methods provide a solid foundation for the decision-making and execution of scientific and technological innovation projects of enterprises, enabling enterprises to maintain their competitive advantages in the fierce market competition, and play a positive role in promoting scientific and technological progress and economic development. These efforts have not only enhanced the competitiveness and market position of enterprises, but also contributed to scientific and technological innovation and industrial upgrading. Therefore, conducting research on scientific research project cost measurement indicators and evaluation systems has important practical significance and far-reaching value for enterprises and even the entire society.

[0054] This application aims to deeply optimize and improve the existing cost assessment model by introducing the grey correlation analysis method.

[0055] In order to make the purpose, technical solutions and advantages of the present invention more clear, specific embodiments will be described below in conjunction with the accompanying drawings.

[0056] Figure 1 The flowchart of the development project cost evaluation method based on improved grey correlation analysis provided by the embodiment of the present invention is as follows. Figure 1 As shown, the following steps are included:

[0057] S101, using expert evaluation method and analytic hierarchy process to determine the pricing indicators and pricing indicator weights corresponding to the scientific and technological projects.

[0058] In a possible implementation method, expert evaluation method and analytic hierarchy process are used to determine the pricing indicators and pricing indicator weights corresponding to the scientific and technological projects, including:

[0059] According to the expert evaluation method, a pricing index evaluation system corresponding to each type of scientific and technological project is designed; among them, the types of scientific and technological projects include: theoretical method research projects, platform software research projects, and hardware R&D research projects; the pricing index evaluation system includes multi-layer pricing indicators corresponding to the types of scientific and technological projects;

[0060] The weight of each pricing indicator in the pricing indicator evaluation system is determined through the hierarchical analysis method.

[0061] In a possible implementation, the pricing indicator system for theoretical method research projects, platform software research projects, and hardware R&D research projects is as follows:

[0062] (1) Pricing indicator system for theoretical and methodological research projects

[0063] Table 1 Pricing index system for theoretical and methodological scientific research projects

[0064]

[0065] (2) Pricing indicator system for platform software research projects

[0066] Table 2 Pricing index system for platform software research projects

[0067]

[0068]

[0069] (3) Pricing index system for hardware R&D research projects

[0070] Table 3 Pricing index system for hardware R&D scientific research projects

[0071]

[0072]

[0073]

[0074] The pricing index evaluation system corresponding to each type of scientific and technological project shown above is theoretically presented. During the specific implementation process, the pricing index evaluation system can be designed according to specific project information.

[0075] S102, using the grey correlation analysis method and the weights of various pricing indicators, screen the important pricing indicators corresponding to the development project costs.

[0076] In this process, factors with small contributions will be eliminated, thereby increasing the benefits of model calculations and improving the accuracy of cost calculations. This process does not require human intervention and can automatically optimize the calculation process. By improving the gray correlation analysis model, the system can more accurately identify and quantify the correlation between project costs and key influencing factors, thereby improving the accuracy of the evaluation and providing a more scientific basis for project budget formulation.

[0077] S103, calculate project costs based on important pricing indicators.

[0078] In this embodiment, the expert evaluation method and the hierarchical analysis method are combined to identify and determine the various pricing indicators in the scientific and technological projects, and the weights of these pricing indicators are further determined to ensure that the importance of each pricing indicator in the evaluation process is reasonably reflected. Subsequently, the gray correlation analysis method is used to screen out the important pricing indicators that have a significant impact on the development project costs, and those factors that have a low contribution to the project costs are excluded to reduce the interference of these indicators on the cost assessment. Based on the selected important pricing indicators, the project costs are accurately calculated, thereby improving the efficiency and accuracy of the evaluation.

[0079] In a possible implementation, the weight of each pricing indicator in the pricing indicator evaluation system is determined by the hierarchical analysis method, including:

[0080] Use the analytic hierarchy process to establish a judgment matrix;

[0081] Verify the consistency of the judgment matrix;

[0082] When the judgment matrix passes the consistency test, the square root method is used to solve the weight of each indicator to determine the weight of each indicator;

[0083] Otherwise, the matrix data is corrected or the matrix order is reduced, and the steps of establishing the judgment matrix using the hierarchical analysis method are repeated.

[0084] Among them, the indicator weights are determined through the hierarchical analysis method. Taking the first type of "theoretical method research" projects as an example, the established hierarchical structure contains three levels: the first level is the goal of scientific research project pricing; the second level includes four evaluation factors such as research foundation, degree of innovation, technical route, and expected results; the third level includes 15 evaluation indicators such as the applicant's research experience.

[0085] Table 4 Pricing indicators for scientific research projects

[0086]

[0087] In a possible implementation, a judgment matrix is ​​established using the analytic hierarchy process, including:

[0088] According to the relative importance of the current layer pricing indicator to a certain pricing indicator of the previous layer, the initial weight of the current layer pricing indicator is determined; the higher the relative importance, the greater the corresponding weight;

[0089] A judgment matrix is ​​constructed based on the initial weights of each pricing indicator.

[0090] The judgment matrix represents the comparison of the relative importance of all factors in this layer to a factor in the previous layer. Generally, 1 to 9 and their reciprocals are used to represent the relative importance of indicators. The scale of each indicator is obtained by expert scoring.

[0091] Table 5 Ratio scale table

[0092]

[0093] Among them, 1 means that the two indicators are equally important, and 9 means that one indicator is more important than the other.

[0094] In a possible implementation, when checking the consistency of the judgment matrix, the calculation formula is:

[0095]

[0096] Where CI is the consistency of the judgment matrix; the larger the CI value, the worse the consistency of the judgment matrix; n is the order; λ max is the maximum eigenvalue of the judgment matrix; B i is the i-th row vector of the judgment matrix; w and w i They are the weight of the pricing indicator and the absolute weight of the pricing indicator in the current layer respectively.

[0097] The order of the judgment matrix is ​​determined by the number of indicators at each level. When the order is greater than 2, the consistency index CI value of the judgment matrix is ​​equal to the average random consistency index R of the same order. I The ratio of the values ​​is called the random consistency ratio CR, where R I The values ​​are given in Table 6, and CI n It represents the consistency index of the nth randomly generated judgment matrix. When CR<0.1, the judgment matrix is ​​considered to have satisfactory consistency. Since there are subjective factors in the judgment of the relative importance of each indicator, when the judgment matrix cannot pass the consistency test, the importance of each indicator needs to be re-assigned, that is, the experts need to re-score the relative importance of each indicator in the matrix.

[0098] Figure 2 FIG. 1 is a flowchart of an embodiment of the present invention for determining the pricing indicators and pricing indicator weights (i.e., step S01) corresponding to a scientific and technological project by using the expert evaluation method and the analytic hierarchy process. Figure 2 As shown, the following steps are included:

[0099] Design a pricing index system based on expert evaluation;

[0100] Establish a hierarchy;

[0101] Use the analytic hierarchy process to establish a judgment matrix;

[0102] Verify the consistency of the judgment matrix;

[0103] When the judgment matrix passes the consistency test, the square root method is used to solve the weight of each indicator to determine the weight of each indicator;

[0104] Otherwise, the matrix data is corrected or the matrix order is reduced, and the steps of establishing the judgment matrix using the hierarchical analysis method are repeated.

[0105] In one possible implementation, corresponding to different types of scientific and technological projects, the pricing indicator evaluation system includes three layers;

[0106] The square root method is used to solve the weight of each indicator and determine the weight of each indicator, including:

[0107] Calculate the nth root of the product of the importance of each indicator in each row of the judgment matrix in, a ij is the element in the judgment matrix, n is the order of the judgment matrix, is the nth root of the product of the elements in the i-th row of the judgment matrix;

[0108] Pair Vector Normalize to w=(w1,w2,....w n );in,

[0109] After calculation, the weight of each indicator in the second-level judgment matrix is ​​w B =(w B1 ,w B2 ,w B3 ,w B4 );

[0110] The weight of each indicator in the third layer judgment matrix is ​​w C =(w C1 ,w C2 ,w C3 ,w C4 .....,w C15 ).

[0111] Table 6n and R I Relationship table

[0112]

[0113] Table 7 Second level judgment matrix

[0114]

[0115] Table 8 The third level judgment matrix

[0116]

[0117] Table 9 The third level judgment matrix

[0118]

[0119] Table 10 The third level judgment matrix

[0120]

[0121] Table 11 The third level judgment matrix

[0122]

[0123] According to the weights of each indicator in the second-layer judgment matrix and the third-layer judgment matrix, the absolute weight of each indicator in the third layer in the entire hierarchy is calculated, that is, W Ci =w Bj × Ci , where i=1,2,....,11, j=1,2,3,4, and when i≤4, j=1; when 5≤i≤7, j=2; when 8≤i≤10, j=3; and when 11≤i≤15, j=4. Absolute weight W Ci Used to calculate the correlation between each indicator in the system behavior sequence in step 2 and the reference sequence.

[0124] Table 12 Pricing index system for scientific research projects

[0125]

[0126] In a possible implementation method, the grey correlation analysis method and the weights of various pricing indicators are used to screen the important pricing indicators corresponding to the development project costs, including:

[0127] Set up a reference sequence and a comparison index sequence; among them, the total cost of the project is set as the reference sequence; the index factors affecting the cost are set as the comparison index sequence;

[0128] Calculate the correlation between the reference sequence and each indicator;

[0129] By comparing the correlation, the indicators with greater contribution are selected as important pricing indicators, and the indicators with smaller contribution are eliminated.

[0130] First, let the total project cost X0 = {X0(1), X0(2), ....., X0(n)} as the reference sequence, and let the factors affecting the cost include the applicant's research experience, the applicant's academic level, the project research situation, and 15 other factors X0 = 1. i ={X i (1),X i (2),....,X i (n)}, i = 1, 2, 3..., 15. is the system behavior sequence, that is, the comparison index sequence, and the data sequence that affects the system behavior is recorded as X. Among them, n is the total number of samples.

[0131] but

[0132] Since different factors have different dimensions and data ranges, they need to be preprocessed to remove the dimensions and unify them into an approximate range. First, the mean of each indicator is calculated, and then the elements in the indicator are divided by their mean. The processed X0 and X i They are and

[0133]

[0134] Then calculate the correlation coefficient between each indicator in the system behavior sequence and the reference sequence, assuming and is the minimum and maximum difference between the two poles.

[0135] Construct correlation coefficient calculation formula: where ξ i (k) represents the correlation coefficient between the reference sequence and the influencing factor in the i-th row of X, ρ∈[0,1] is the resolution coefficient, and ρ=0.5 is generally taken. However, in order to make the correlation calculation more accurate, the model is improved here to find a more appropriate ρ value. The improvement method is as follows:

[0136] set up

[0137] but

[0138] set up Here m=15.

[0139] set up

[0140] If μ(k)≥0.5, the resolution coefficient is kept as ρ(k)∈(0.5,1) as much as possible; if μ(k)<0.5, the resolution coefficient is kept as ρ(k)∈(0,0.5) as much as possible.

[0141] After determining the range of ρ(k), ρ(k) needs to be within its corresponding range and the optimal value is found using the following objective function. In both cases, the range of values ​​of ρ and ρ(k) in the following formula is consistent:

[0142]

[0143] The improved correlation coefficient calculation formula is:

[0144]

[0145] Then calculate the correlation between each indicator in the system behavior sequence and the reference sequence. The calculation formula is:

[0146]

[0147] Among them, r i represents the correlation between the reference sequence and the influencing factor in the i-th row in X, W Ci is the absolute weight of the influencing factor in the i-th row of X obtained in step 1. Compare the correlation between the indicators affecting the cost and the total project cost, select the indicators with more obvious contribution, and eliminate the indicator factors with smaller contribution. The samples of the eliminated factors will not participate in the subsequent calculation, and the samples of the retained factors will be used as independent variable samples for the next step of project cost calculation.

[0148] In one possible implementation, project cost estimation is performed based on important pricing indicators, including:

[0149] Substitute the sample values ​​of the selected important pricing indicators into the calculation model for calculation;

[0150] When the error does not reach the ideal value, the genetic algorithm is used to continuously optimize the measurement model parameters;

[0151] When the error reaches the ideal value, the measurement model parameters are determined and the actual project cost is estimated.

[0152] In a possible implementation, the calculation model is:

[0153] y=β0+β1x1+.....+β k x k

[0154] Among them, Y = Xβ + ε is the matrix expression of the measurement model; ε is the error term; and it satisfies E(ε) = 0; COV(ε,ε) = σ 2 I n ;I n is an n-order unit matrix; k represents the total number of important pricing indicators;

[0155] Each indicator that affects project cost has n sample values.

[0156] Figure 3 FIG. 1 is a flowchart of an implementation of selecting important pricing indicators for project cost estimation (ie, steps S102 and S103) provided by an embodiment of the present invention. Figure 3 The steps shown include:

[0157] Set up a reference sequence and a comparison index sequence; among them, the total cost of the project is set as the reference sequence; the index factors affecting the cost are set as the comparison index sequence;

[0158] Calculate the correlation between the reference sequence and each indicator;

[0159] Compare the correlations and select the indicators with greater contribution, and eliminate the indicators with less contribution;

[0160] Substitute the selected indicator sample values ​​into the measurement model for measurement;

[0161] When the error does not reach the ideal value, the genetic algorithm is used to continuously optimize the measurement model parameters;

[0162] When the error reaches the ideal value, the measurement model parameters are determined and the actual project cost is estimated.

[0163] In the calculation process, the project cost is taken as the independent variable, and the selected important pricing indicators are substituted as the dependent variables into the software SPSSPRO for multiple linear regression analysis. Then, the genetic algorithm function provided in the software is used to solve the regression model with the minimum sum of squared deviations. The quantitative data of each dependent variable of the project that needs cost forecasting is then substituted into the model formula optimized by the genetic algorithm. What is substituted here is the quantitative data of the selected important pricing indicators, and finally the final total project cost is calculated.

[0164] This application scheme can more accurately identify and quantify the correlation between various factors, making the evaluation results more scientific, reasonable and valuable. Through this improvement, it is expected to provide a more comprehensive and accurate tool for the cost evaluation of power grid technology projects, thereby helping relevant decision makers to better manage projects and allocate funds, ensure the economic rationality of scientific research funds, and improve the overall efficiency of projects.

[0165] It should be understood that the order of execution of the steps in the above embodiment does not necessarily mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiment of the present invention.

[0166] The following is an embodiment of the device of the present invention. For details not described in detail therein, reference may be made to the corresponding method embodiment described above.

[0167] Figure 4 The schematic diagram of the structure of the development project cost evaluation device based on improved grey correlation analysis provided by the embodiment of the present invention is shown. For the convenience of explanation, only the part related to the embodiment of the present invention is shown, which is described in detail as follows:

[0168] like Figure 4 As shown, the development project cost assessment device 4 based on improved grey relational analysis includes:

[0169] Determination module 401, used to determine the pricing indicators and pricing indicator weights corresponding to the scientific and technological project by using expert evaluation method and hierarchical analysis method;

[0170] A screening module 402 is used to screen important pricing indicators corresponding to the development project costs by using a grey correlation analysis method and the weights of various pricing indicators;

[0171] The calculation module 403 is used to calculate the project cost according to important pricing indicators.

[0172] In a possible implementation, the determination module 401 is specifically configured to:

[0173] According to the expert evaluation method, a pricing index evaluation system corresponding to each type of scientific and technological project is designed; among them, the types of scientific and technological projects include: theoretical method research projects, platform software research projects, and hardware R&D research projects; the pricing index evaluation system includes multi-layer pricing indicators corresponding to the types of scientific and technological projects;

[0174] The weight of each pricing indicator in the pricing indicator evaluation system is determined through the hierarchical analysis method.

[0175] In a possible implementation, the determination module 401 is specifically configured to:

[0176] Use the analytic hierarchy process to establish a judgment matrix;

[0177] Verify the consistency of the judgment matrix;

[0178] When the judgment matrix passes the consistency test, the square root method is used to solve the weight of each indicator to determine the weight of each indicator;

[0179] Otherwise, the matrix data is corrected or the matrix order is reduced, and the steps of establishing the judgment matrix using the hierarchical analysis method are repeated.

[0180] In a possible implementation, the determination module 401 is specifically configured to:

[0181] According to the relative importance of the current layer pricing indicator to a certain pricing indicator of the previous layer, the initial weight of the current layer pricing indicator is determined; the higher the relative importance, the greater the corresponding weight;

[0182] A judgment matrix is ​​constructed based on the initial weights of each pricing indicator.

[0183] In a possible implementation, when checking the consistency of the judgment matrix, the calculation formula is:

[0184]

[0185] Where CI is the consistency of the judgment matrix; the larger the CI value, the worse the consistency of the judgment matrix; n is the order; λ max is the maximum eigenvalue of the judgment matrix; B i is the i-th row vector of the judgment matrix; w and wi They are respectively the weight of the pricing indicator and the absolute weight of the pricing indicator in the current layer.

[0186] In one possible implementation, corresponding to different types of scientific and technological projects, the pricing indicator evaluation system includes three layers;

[0187] The determination module 401 is specifically used for:

[0188] Calculate the nth root of the product of the importance of each indicator in each row of the judgment matrix in, a ij is the element in the judgment matrix, n is the order of the judgment matrix, is the nth root of the product of the elements in the i-th row of the judgment matrix;

[0189] Pair Vector Normalize to w=(w1,w2,....w n );in,

[0190] After calculation, the weight of each indicator in the second-level judgment matrix is ​​w B =(w B1 ,w B2 ,w B3 ,w B4 );

[0191] The weight of each indicator in the third layer judgment matrix is ​​w C =(w C1 ,w C2 ,w C3 ,w C4 .....,w C15 ).

[0192] In a possible implementation, the screening module 402 is specifically configured to:

[0193] Set up a reference sequence and a comparison index sequence; among them, the total cost of the project is set as the reference sequence; the index factors affecting the cost are set as the comparison index sequence;

[0194] Calculate the correlation between the reference sequence and each indicator;

[0195] By comparing the correlation, the indicators with greater contribution are selected as important pricing indicators, and the indicators with smaller contribution are eliminated.

[0196] In a possible implementation, the calculation module 403 is specifically configured to:

[0197] Substitute the sample values ​​of the selected important pricing indicators into the calculation model for calculation;

[0198] When the error does not reach the ideal value, the genetic algorithm is used to continuously optimize the measurement model parameters;

[0199] When the error reaches the ideal value, the measurement model parameters are determined and the actual project cost is estimated.

[0200] In this embodiment, the expert evaluation method and the hierarchical analysis method are combined to identify and determine the various pricing indicators in the scientific and technological projects, and the weights of these pricing indicators are further determined to ensure that the importance of each pricing indicator in the evaluation process is reasonably reflected. Subsequently, the gray correlation analysis method is used to screen out the important pricing indicators that have a significant impact on the development project costs, and those factors that have a low contribution to the project costs are excluded to reduce the interference of these indicators on the cost assessment. Based on the selected important pricing indicators, the project costs are accurately calculated, thereby improving the efficiency and accuracy of the evaluation.

[0201] In the above embodiments, the description of each embodiment has its own emphasis. For parts that are not described or recorded in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0202] Those of ordinary skill in the art will appreciate that the templates, units, and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of the present invention.

[0203] If the module / unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the present invention implements all or part of the processes in the above-mentioned embodiment method, and can also be completed by instructing the relevant hardware through a computer program. The computer program can be stored in a computer-readable storage medium. When the computer program is executed by the processor, it can implement the steps of the above-mentioned embodiments of the development project cost assessment method based on improved grey correlation analysis. Among them, the computer program includes computer program code, and the computer program code can be in source code form, object code form, executable file or some intermediate form. The computer-readable medium may include: any entity or device that can carry the computer program code, recording medium, U disk, mobile hard disk, disk, optical disk, computer memory, read-only memory, random access memory, electric carrier signal, telecommunication signal and software distribution medium.

[0204] The embodiments described above are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features may be replaced by equivalents. Such modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention, and should all be included in the protection scope of the present invention.

Claims

1. A development project cost evaluation method based on improved grey correlation analysis, characterized in that: include: Use expert evaluation method and analytic hierarchy process to determine the pricing indicators and weights of the corresponding scientific and technological projects; Use grey correlation analysis and the weights of various pricing indicators to screen important pricing indicators corresponding to development project costs; Calculate project costs based on the important pricing indicators mentioned above.

2. The development project cost evaluation method based on improved grey correlation analysis according to claim 1, characterized in that: The expert evaluation method and the analytic hierarchy process are used to determine the pricing indicators and pricing indicator weights corresponding to the scientific and technological projects, including: Design a pricing index evaluation system corresponding to each type of scientific and technological project based on the expert evaluation method; wherein the types of scientific and technological projects include: theoretical method scientific research projects, platform software scientific research projects, and hardware R&D scientific research projects; the pricing index evaluation system includes multiple layers of pricing indexes corresponding to the types of scientific and technological projects; The weight of each pricing indicator in the pricing indicator evaluation system is determined through the hierarchical analysis method.

3. The development project cost evaluation method based on improved grey correlation analysis as claimed in claim 2, characterized in that: The weight of each pricing indicator in the pricing indicator evaluation system is determined by the hierarchical analysis method, including: Use the analytic hierarchy process to establish a judgment matrix; Verify the consistency of the judgment matrix; When the judgment matrix passes the consistency test, the square root method is used to solve the weight of each indicator to determine the weight of each indicator; Otherwise, the matrix data is corrected or the matrix order is reduced, and the steps of establishing the judgment matrix using the hierarchical analysis method are repeated.

4. The development project cost evaluation method based on improved grey correlation analysis as claimed in claim 3, characterized in that: The method of establishing a judgment matrix by using the analytic hierarchy process comprises: According to the relative importance of the current layer pricing indicator to a certain pricing indicator of the previous layer, the initial weight of the current layer pricing indicator is determined; the higher the relative importance, the greater the corresponding weight; A judgment matrix is ​​constructed based on the initial weights of each pricing indicator.

5. The development project cost evaluation method based on improved grey correlation analysis as claimed in claim 3, characterized in that: When checking the consistency of the judgment matrix, the calculation formula is: Where CI is the consistency of the judgment matrix; the larger the CI value, the worse the consistency of the judgment matrix; n is the order; λ max is the maximum eigenvalue of the judgment matrix; B i is the i-th row vector of the judgment matrix; w and w i They are respectively the weight of the pricing indicator and the absolute weight of the pricing indicator in the current layer.

6. The method for evaluating development project costs based on improved grey correlation analysis as claimed in claim 3, characterized in that: Corresponding to different types of scientific and technological projects, the pricing index evaluation system includes three levels; The method of using the square root method to solve the weight of each indicator to determine the weight of each indicator includes: Calculate the nth root of the product of the importance of each indicator in each row of the judgment matrix in, a ij is the element in the judgment matrix, n is the order of the judgment matrix, is the nth root of the product of the elements in the i-th row of the judgment matrix; Pair Vector Normalize to w=(w1,w2,....w n );in, After calculation, the weight of each indicator in the second-level judgment matrix is ​​w B =(w B1 ,w B2 ,w B3 ,w B4 ); The weight of each indicator in the third layer judgment matrix is ​​w C =(w C1 ,w C2 ,w C3 ,w C4 .....,w C15 ).

7. The method for evaluating development project costs based on improved grey correlation analysis according to claim 1, characterized in that: The gray correlation analysis method and the weights of various pricing indicators are used to screen important pricing indicators corresponding to the development project costs, including: Set up a reference sequence and a comparison index sequence; among them, the total cost of the project is set as the reference sequence; the index factors affecting the cost are set as the comparison index sequence; Calculate the correlation between the reference sequence and each indicator; By comparing the correlation, the indicators with greater contribution are selected as important pricing indicators, and the indicators with smaller contribution are eliminated.

8. The method for evaluating development project costs based on improved grey relational analysis according to claim 7, characterized in that: The project cost estimation based on the important pricing indicators includes: Substitute the sample values ​​of the selected important pricing indicators into the calculation model for calculation; When the error does not reach the ideal value, the genetic algorithm is used to continuously optimize the measurement model parameters; When the error reaches the ideal value, the measurement model parameters are determined and the actual project cost is estimated.

9. The method for evaluating development project costs based on improved grey correlation analysis according to claim 8, characterized in that: The calculation model is: y=β0+β1x1+.....+β k x k Among them, Y = Xβ + ε is the matrix expression of the measurement model; ε is the error term; and it satisfies E(ε) = 0; COV(ε,ε) = σ 2 I n ;I n is an n-order unit matrix; k represents the total number of important pricing indicators; Each indicator that affects project cost has n sample values.

10. A development project cost assessment device based on improved grey correlation analysis, characterized in that: include: The determination module is used to determine the pricing indicators and pricing indicator weights corresponding to the scientific and technological projects by using the expert evaluation method and the hierarchical analysis method; The screening module is used to screen the important pricing indicators corresponding to the development project costs by using the grey correlation analysis method and the weights of each pricing indicator; The calculation module is used to calculate the project cost according to the important pricing indicators.

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