IT R&D energy efficiency evaluation method and system based on comprehensive data analysis

Abstract

The present invention discloses an IT R&D energy efficiency evaluation method and system based on comprehensive data analysis, and relates to the IT R&D technical field. The method includes establishing an IT R&D energy efficiency scoring model related to the early completion benefits, labor costs and time costs of IT R&D projects based on the project development duration of each IT R&D project, the project deadline duration corresponding to each IT R&D project and the total amount of IT R&D human resources that can be allocated by the enterprise; taking the maximum IT R&D energy efficiency score as the goal, solving the global optimal solution through the particle swarm optimization algorithm under the premise that the sum of the R&D human resources of each IT R&D project in the enterprise's IT R&D project list is less than or equal to the total amount of IT R&D human resources, and obtaining the IT R&D human resources allocation amount of each IT R&D project; and allocating IT R&D human resources to each IT R&D project. The method and system disclosed in the present invention can reduce the development cost of IT R&D projects and realize more refined project resource allocation.

Description

Technical Field

[0001] The present invention belongs to the field of IT R&D technology, and specifically relates to an IT R&D energy efficiency evaluation method and system based on comprehensive data analysis. Background Art

[0002] In the process of IT project development, how to achieve more refined project human resource allocation and reduce the development cost of IT R&D projects is an important task of project management.

[0003] In the prior art, human resource allocation for some IT R&D projects is based on the project deadline. On the premise of meeting the project deadline, human resources are allocated to each IT R&D project. However, in actual situations, the development cost of an IT R&D project is not a single time cost. Adopting such a human resource allocation method often leads to an increase in the development cost of IT R&D projects.

[0004] Therefore, how to provide an effective solution to reduce the development cost of IT R&D projects as much as possible has become an urgent problem to be solved in the prior art. Summary of the invention

[0005] The purpose of the present invention is to provide an IT R&D energy efficiency evaluation method and system based on comprehensive data analysis to solve the above-mentioned problems existing in the prior art.

[0006] In order to achieve the above object, the present invention adopts the following technical solutions:

[0007] In a first aspect, the present invention provides an IT R&D energy efficiency evaluation method based on comprehensive data analysis, characterized in that it includes:

[0008] Based on the project development time of each IT R&D project in the enterprise's IT R&D project list, the project deadline of each IT R&D project, and the total amount of IT R&D human resources that can be allocated by the enterprise, an IT R&D energy efficiency scoring model related to the early completion benefits, human cost, and time cost of IT R&D projects is established;

[0009] Taking the maximum IT R&D energy efficiency score as the goal, the particle swarm optimization algorithm is used to solve the global optimal solution under the premise that the sum of the R&D human resources of each IT R&D project in the enterprise IT R&D project list is less than or equal to the total amount of IT R&D human resources, and the IT R&D human resources allocation amount of each IT R&D project in the enterprise IT R&D project list is obtained;

[0010] Allocate IT R&D human resources to each IT R&D project based on the IT R&D human resources allocation amount of each IT R&D project in the enterprise's IT R&D project list.

[0011] Based on the above disclosed content, the present invention establishes an IT R&D energy efficiency scoring model related to the early completion benefits, labor costs and time costs of IT R&D projects based on the project development duration of each IT R&D project in the enterprise's IT R&D project list, the project deadline duration corresponding to each IT R&D project and the total amount of IT R&D human resources that can be allocated by the enterprise; with the maximum IT R&D energy efficiency score as the goal, the particle swarm optimization algorithm is used to solve the global optimal solution under the premise that the sum of the R&D human resources of each IT R&D project in the enterprise's IT R&D project list is less than or equal to the total amount of IT R&D human resources, and the IT R&D human resource allocation amount of each IT R&D project in the enterprise's IT R&D project list is obtained; based on the IT R&D human resource allocation amount of each IT R&D project in the enterprise's IT R&D project list, IT R&D human resources are allocated to each IT R&D project. In this way, multiple IT R&D projects can be comprehensively considered from multiple angles, such as the benefits of early completion of IT R&D projects, the human costs of IT R&D projects, and the time costs of IT R&D projects, to determine the IT R&D human resource allocation for each IT R&D project when the IT R&D energy efficiency score is the highest, that is, the comprehensive cost of the IT R&D project is the lowest. IT R&D human resources can be allocated to each IT R&D project, thereby reducing the development cost of IT R&D projects, achieving more refined project resource allocation, providing data support and guidance for project teams and decision-makers, and enhancing the company's IT R&D capabilities.

[0012] In one possible design, the method further includes:

[0013] If the global optimal solution is not found, the project duration corresponding to the target IT R&D project in the enterprise IT R&D project list is incremented by 1 and the global optimal solution is found again. The target IT R&D project is the IT R&D project with the lowest priority in the enterprise IT R&D project list.

[0014] If the global optimal solution is still not found after adding N to the project deadline of the target IT R&D project, the target IT R&D project is removed from the enterprise IT R&D project list to update the enterprise IT R&D project list, where N is a positive integer greater than 1;

[0015] Taking the maximum IT R&D energy efficiency score as the goal, the particle swarm optimization algorithm is used to solve the global optimal solution under the premise that the sum of the R&D human resources of each IT R&D project in the updated enterprise IT R&D project list is less than or equal to the total amount of IT R&D human resources, and the IT R&D human resource allocation of each IT R&D project in the updated enterprise IT R&D project list is obtained.

[0016] In a possible design, the IT R&D energy efficiency scoring model is: , where P represents the sum of IT R&D energy efficiency scores of all IT R&D projects, n represents the total number of IT R&D projects in the enterprise IT R&D project list, represents the energy efficiency score of the i-th IT R&D project, The duration of the project corresponding to the i IT R&D projects represented by represents the project development duration of the i-th IT R&D project, represents the IT R&D human resources allocation for the i-th IT R&D project, a, b and c are all known proportional coefficients, It indicates the total amount of IT R&D human resources that can be allocated by the enterprise.

[0017] In one possible design, the method further includes:

[0018] Based on multiple historical IT R&D project lists that have not been overdue, the project development duration of historical IT R&D projects in each historical IT R&D project list, the project deadline duration corresponding to the historical IT R&D projects, and the total amount of IT R&D human resources that can be allocated by the enterprise corresponding to each historical IT R&D project list during the same period, the values ​​of the proportional coefficients a, b, and c in the IT R&D energy efficiency scoring model are solved when the IT R&D energy efficiency score is the maximum, and multiple arrays corresponding to multiple historical IT R&D project lists are obtained;

[0019] The values ​​of the proportional coefficients a, b and c are solved based on the multiple arrays.

[0020] In a possible design, solving the values ​​of the proportional coefficients a, b and c based on the multiple arrays includes:

[0021] Performing bottom-up hierarchical clustering on the plurality of arrays;

[0022] When there are two clusters left, the cluster with the most corresponding arrays is selected as the target cluster;

[0023] The cluster center of the target cluster is calculated, and the values ​​of the proportional coefficients a, b and c are determined based on the values ​​corresponding to the cluster center.

[0024] In a possible design, with the maximum IT R&D energy efficiency score as the goal, the particle swarm optimization algorithm is used to solve the global optimal solution under the premise that the sum of the R&D human resources of each IT R&D project in the enterprise IT R&D project list is less than or equal to the total amount of IT R&D human resources, including:

[0025] Initializing a particle population, wherein the particle population includes IT R&D human resource allocations of each IT R&D project;

[0026] Based on the IT R&D energy efficiency scoring model, the fitness function of the population example algorithm is determined. Based on the fitness function, the fitness value of each particle in the particle population is calculated, and the fitness value of each particle is used as the local optimal solution position. The position corresponding to the particle with the largest fitness value among all particles is used as the global optimal solution position.

[0027] Update the particles in the particle population;

[0028] Calculate the fitness value of each particle in the updated particle population, and update the local optimal solution position and the global optimal solution position of each particle based on the fitness value of each particle in the particle population;

[0029] If the fitness value corresponding to the current global optimal solution position does not reach the preset threshold, the particles of the particle population are updated again to re-update the local optimal solution position and the global optimal solution position of each particle;

[0030] If the fitness value corresponding to the latest global optimal solution position reaches a preset threshold or the number of iterations reaches a preset number, the update is stopped.

[0031] In one possible design, the amount of IT R&D human resources allocated to each IT R&D project is a positive integer.

[0032] In a second aspect, the present invention provides an IT R&D energy efficiency evaluation system based on comprehensive data analysis, comprising:

[0033] Establish a unit for establishing an IT R&D efficiency scoring model related to the benefits of early completion, human cost, and time cost of IT R&D projects based on the project development time of each IT R&D project in the enterprise's IT R&D project list, the project deadline of each IT R&D project, and the total amount of IT R&D human resources that can be allocated by the enterprise;

[0034] A calculation unit is used to solve the global optimal solution by using a particle swarm optimization algorithm with the maximum IT R&D energy efficiency score as the goal, under the premise that the sum of the R&D human resources of each IT R&D project in the enterprise IT R&D project list is less than or equal to the total amount of IT R&D human resources, and obtain the IT R&D human resources allocation amount of each IT R&D project in the enterprise IT R&D project list;

[0035] The allocation unit is used to allocate IT R&D human resources to each IT R&D project based on the IT R&D human resources allocation amount of each IT R&D project in the enterprise IT R&D project list.

[0036] In a third aspect, the present invention provides an electronic device comprising a memory, a processor and a transceiver which are communicatively connected in sequence, wherein the memory is used to store a computer program, the transceiver is used to send and receive messages, and the processor is used to read the computer program to execute the IT R&D energy efficiency evaluation method based on comprehensive data analysis as described in the first aspect or any possible design of the first aspect.

[0037] In a fourth aspect, the present invention provides a computer-readable storage medium having instructions stored thereon, which, when executed on a computer, executes the IT R&D energy efficiency evaluation method based on comprehensive data analysis as described in the first aspect or any possible design of the first aspect.

[0038] In a fifth aspect, the present invention provides a computer program product comprising instructions, which, when executed on a computer, causes the computer to execute the IT R&D energy efficiency assessment method based on comprehensive data analysis as described in the first aspect or any possible design of the first aspect.

[0039] Beneficial effects:

[0040] The IT R&D energy efficiency evaluation method and system based on comprehensive data analysis provided by the present invention can comprehensively consider multiple IT R&D projects from multiple angles such as the benefits of early completion of IT R&D projects, the human cost of IT R&D projects, and the time cost of IT R&D projects, and determine the IT R&D human resource allocation amount for each IT R&D project when the IT R&D energy efficiency score is the largest, that is, the comprehensive cost of the IT R&D project is the lowest, and allocate IT R&D human resources to each IT R&D project, thereby reducing the development cost of IT R&D projects, achieving more refined project resource allocation, providing data support and guidance for project teams and decision-makers, improving the IT R&D capabilities of enterprises, and facilitating practical application and promotion. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] Figure 1 A flowchart of an IT R&D energy efficiency evaluation method based on comprehensive data analysis provided in an embodiment of the present application;

[0042] Figure 2 A schematic diagram of a block diagram of an IT R&D energy efficiency evaluation system based on comprehensive data analysis provided in an embodiment of the present application;

[0043] Figure 3 A schematic block diagram of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0044] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the present invention will be briefly introduced below in combination with the drawings and the description of the embodiments or the prior art. Obviously, the following description of the structure of the drawings is only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work. It should be noted that the description of these embodiments is used to help understand the present invention, but does not constitute a limitation of the present invention.

[0045] It should be understood that although the terms first, second, etc. may be used herein to describe various units, these units should not be limited by these terms. These terms are only used to distinguish one unit from another unit. For example, a first unit can be referred to as a second unit, and similarly, a second unit can be referred to as a first unit without departing from the scope of the exemplary embodiments of the present invention.

[0046] It should be understood that the term "and / or" that may appear in this article is merely a description of the association relationship between associated objects, indicating that three relationships may exist. For example, A and / or B can represent three situations: A exists alone, B exists alone, and A and B exist at the same time. The term " / and" that may appear in this article describes another type of association object relationship, indicating that two relationships may exist. For example, A / and B can represent two situations: A exists alone, and A and B exist alone. In addition, the character " / " that may appear in this article generally indicates that the previous and next associated objects are in an "or" relationship.

[0047] In order to reduce the development cost of IT R&D projects as much as possible, the embodiment of the present application provides an IT R&D energy efficiency evaluation method and system based on comprehensive data analysis. The IT R&D energy efficiency evaluation method and system based on comprehensive data analysis can reduce the development cost of IT R&D projects and achieve more refined project resource allocation.

[0048] The IT R&D energy efficiency evaluation method based on comprehensive data analysis provided in the embodiment of the present application can be applied to a server or a user terminal. It can be understood that the execution subject does not constitute a limitation on the embodiment of the present application.

[0049] The IT R&D energy efficiency evaluation method based on comprehensive data analysis provided in an embodiment of the present application will be described in detail below.

[0050] like Figure 1 As shown, it is a flowchart of the IT R&D energy efficiency evaluation method based on comprehensive data analysis provided in the first aspect of the embodiment of the present application. The IT R&D energy efficiency evaluation method based on comprehensive data analysis may include but is not limited to the following steps S101-S103.

[0051] Step S101. Based on the project development duration of each IT R&D project in the enterprise's IT R&D project list, the project deadline corresponding to each IT R&D project, and the total amount of IT R&D human resources that can be allocated by the enterprise, establish an IT R&D energy efficiency scoring model related to the early completion benefits, labor costs, and time costs of IT R&D projects.

[0052] The IT R&D projects in the IT R&D project list may refer to multiple IT R&D projects in the same batch. The total amount of IT R&D human resources that can be allocated by the enterprise may refer to the number of IT R&D personnel that can be allocated by the enterprise.

[0053] If an IT R&D project is completed ahead of schedule, it will bring certain benefits during the period of early completion. Therefore, in the embodiment of the present application, the IT R&D energy efficiency scoring model is set to be positively correlated with the benefits of early completion of the IT R&D project, and negatively correlated with labor costs and time costs. That is, the earlier the IT R&D project is completed, the higher the benefits brought by early completion, and the higher the IT R&D energy efficiency score. The more labor costs and time costs, the more costs paid, and the lower the IT R&D energy efficiency score.

[0054] In the embodiment of the present application, the IT R&D energy efficiency scoring model can be expressed as: , where P represents the sum of IT R&D energy efficiency scores of all IT R&D projects (in the IT R&D project list), n represents the total number of IT R&D projects in the enterprise IT R&D project list, represents the energy efficiency score of the i-th IT R&D project, The duration of the project corresponding to the i IT R&D projects represented by represents the project development duration of the i-th IT R&D project, represents the IT R&D human resources allocation for the i-th IT R&D project, a, b and c are all known predetermined proportional coefficients. It indicates the total amount of IT R&D human resources that can be allocated by the enterprise.

[0055] a, b and c are all known proportional coefficients. a, b and c are used to represent the weights of early completion benefits, labor costs and time costs in the IT R&D energy efficiency scoring process, that is, the importance of early completion benefits, labor costs and time costs in the process of evaluating IT R&D energy efficiency scoring.

[0056] In an embodiment of the present application, the degree to which the enterprise values ​​early completion benefits, labor costs, and time costs when evaluating the development costs of IT R&D projects, that is, the weights of early completion benefits, labor costs, and time costs, can be determined based on the human resource allocation of each IT R&D project in the historical IT R&D project list.

[0057] Specifically, the values ​​of the proportional coefficients a, b and c in the IT R&D energy efficiency scoring model when the IT R&D energy efficiency score is the maximum can be solved based on the project development time of the historical IT R&D projects in each historical IT R&D project list, the project deadline corresponding to the historical IT R&D projects, and the total amount of IT R&D human resources that can be allocated by the enterprise in the corresponding period of each historical IT R&D project list in multiple historical IT R&D project lists that have not been overdue, and multiple arrays corresponding to multiple historical IT R&D project lists are obtained. That is, the project development time of the historical IT R&D projects in each historical IT R&D project list, the project deadline corresponding to the historical IT R&D projects, and the total amount of IT R&D human resources that can be allocated by the enterprise in the corresponding period of each historical IT R&D project list are substituted into the IT R&D energy efficiency scoring model to solve the values ​​of a, b and c when the IT R&D energy efficiency score is the maximum. Then, the values ​​of the proportional coefficients a, b and c are solved based on the multiple arrays.

[0058] In one or more embodiments, solving the values ​​of the proportional coefficients a, b, and c based on multiple arrays may include, but is not limited to, the following steps S201-S203.

[0059] Step S201: Perform bottom-up hierarchical clustering on multiple groups of arrays.

[0060] In the embodiment of the present application, multiple groups of arrays can be converted into vectors to obtain multiple groups of vectors that correspond one to one with the multiple groups of arrays. Then, the multiple groups of vectors are clustered by bottom-up hierarchical clustering.

[0061] Step S202: When there are two clusters remaining, the cluster with the largest number of corresponding arrays is selected as the target cluster.

[0062] Specifically, when there are two cluster classes remaining, the cluster containing the most vectors (that is, the most corresponding arrays) can be selected as the target cluster.

[0063] Step S203: Calculate the cluster center of the target cluster, and determine the values ​​of the proportional coefficients a, b and c based on the values ​​corresponding to the cluster center.

[0064] It is understandable that in some other embodiments, the values ​​of a, b and c may be solved by other methods. For example, the corresponding values ​​in multiple arrays may be directly averaged to obtain the values ​​of a, b and c.

[0065] Step S102. Taking the maximum IT R&D energy efficiency score as the goal, the particle swarm optimization algorithm is used to solve the global optimal solution under the premise that the sum of the R&D human resources of each IT R&D project in the enterprise IT R&D project list is less than or equal to the total amount of IT R&D human resources, and the IT R&D human resource allocation of each IT R&D project in the enterprise IT R&D project list is obtained.

[0066] Among them, the IT R&D human resources allocation amount for each IT R&D project is a positive integer.

[0067] In one or more embodiments, with the maximum IT R&D energy efficiency score as the goal, a global optimal solution is solved by a particle swarm optimization algorithm under the premise that the sum of the R&D human resources of each IT R&D project in the enterprise IT R&D project list is less than or equal to the total amount of IT R&D human resources, and the IT R&D human resource allocation amount of each IT R&D project in the enterprise IT R&D project list is obtained, which may include but is not limited to the following steps S1021-S1026.

[0068] Step S1021: Initialize a particle population, wherein the particle population includes IT R&D human resource allocations for each IT R&D project.

[0069] Step S1022. Determine the fitness function of the population example algorithm based on the IT R&D energy efficiency scoring model, calculate the fitness value of each particle in the particle population based on the fitness function, and use the fitness value of each particle as the local optimal solution position, and use the position corresponding to the particle with the largest fitness value among all particles as the global optimal solution position.

[0070] Step S1023: Update the particles in the particle population.

[0071] Step S1024: Calculate the fitness value of each particle in the updated particle population, and update the local optimal solution position and the global optimal solution position of each particle based on the fitness value of each particle in the particle population.

[0072] Step S1025: If the fitness value corresponding to the current global optimal solution position does not reach a preset threshold, the particles of the particle population are updated again to re-update the local optimal solution position and the global optimal solution position of each particle.

[0073] Step S1026: If the fitness value corresponding to the latest global optimal solution position reaches a preset threshold or the number of iterations reaches a preset number, stop updating.

[0074] Step S103: Allocate IT R&D human resources to each IT R&D project based on the IT R&D human resources allocation amount of each IT R&D project in the enterprise IT R&D project list.

[0075] In one or more embodiments, when solving the global optimal solution through the particle swarm optimization algorithm, the global optimal solution may not be solved due to the insufficient total amount of IT R&D human resources that can be allocated by the enterprise. If the global optimal solution is not solved, the project deadlines corresponding to some low-priority IT R&D projects can be increased or some low-priority IT R&D projects can be removed. In this way, when it is impossible to ensure that all IT R&D projects can be completed smoothly on schedule, it is possible to ensure that high-priority IT R&D projects can be completed on schedule. It can include but is not limited to the following steps S301-S303.

[0076] Step S301. If the global optimal solution is not found, the project deadline corresponding to the target IT R&D project in the enterprise IT R&D project list is incremented by 1 and the global optimal solution is found again. The target IT R&D project is the IT R&D project with the lowest priority in the enterprise IT R&D project list.

[0077] Among them, the priority of IT R&D projects can be set in advance according to actual conditions.

[0078] Step S302. If the global optimal solution is not obtained after adding N to the project deadline of the target IT R&D project, the target IT R&D project is removed from the enterprise IT R&D project list to update the enterprise IT R&D project list, where N is a positive integer greater than 1.

[0079] Specifically, if the project deadline corresponding to the target IT R&D project in the enterprise IT R&D project list is incremented by 1 and the global optimum is re-solved, but the global optimum is still not solved, then the project deadline corresponding to the target IT R&D project in the enterprise IT R&D project list continues to be incremented by 1 and the global optimum is re-solved; if the project deadline corresponding to the target IT R&D project is incremented by N and the global optimum is still not solved, then the target IT R&D project is removed from the enterprise IT R&D project list to update the enterprise IT R&D project list.

[0080] Step S303. Taking the maximum IT R&D energy efficiency score as the goal, the particle swarm optimization algorithm is used to solve the global optimal solution under the premise that the sum of the R&D human resources of each IT R&D project in the updated enterprise IT R&D project list is less than or equal to the total amount of IT R&D human resources, and the IT R&D human resource allocation of each IT R&D project in the updated enterprise IT R&D project list is obtained.

[0081] After removing the target IT R&D project from the enterprise IT R&D project list to update the enterprise IT R&D project list, the maximum IT R&D energy efficiency score can be continued as the target, and the global optimal solution can be solved by the particle swarm optimization algorithm under the premise that the sum of the R&D human resources of each IT R&D project in the updated enterprise IT R&D project list is less than or equal to the total amount of IT R&D human resources, so as to obtain the IT R&D human resource allocation of each IT R&D project in the updated enterprise IT R&D project list. During this period, if the global optimal solution is still not solved, the above-mentioned execution step S302 can be repeated until the global optimal solution is solved.

[0082] To summarize, the IT R&D energy efficiency evaluation method based on comprehensive data analysis provided in the embodiment of the present application establishes an IT R&D energy efficiency scoring model related to the early completion benefits, labor costs and time costs of IT R&D projects based on the project development duration of each IT R&D project in the enterprise's IT R&D project list, the project deadline duration corresponding to each IT R&D project, and the total amount of IT R&D human resources that can be allocated by the enterprise; with the maximum IT R&D energy efficiency score as the goal, the particle swarm optimization algorithm is used to solve the global optimal solution on the premise that the sum of the R&D human resources of each IT R&D project in the enterprise's IT R&D project list is less than or equal to the total amount of IT R&D human resources, and the IT R&D human resource allocation amount of each IT R&D project in the enterprise's IT R&D project list is obtained; based on the IT R&D human resource allocation amount of each IT R&D project in the enterprise's IT R&D project list, IT R&D human resources are allocated to each IT R&D project. In this way, multiple IT R&D projects can be comprehensively considered from multiple perspectives such as the benefits of early completion of IT R&D projects, the labor costs of IT R&D projects, and the time costs of IT R&D projects, and the IT R&D human resource allocation for each IT R&D project can be determined when the IT R&D energy efficiency score is the largest, that is, when the comprehensive cost of the IT R&D project is the lowest. IT R&D human resources can be allocated to each IT R&D project, thereby reducing the development cost of IT R&D projects, achieving more refined project resource allocation, providing data support and guidance for project teams and decision-makers, and improving the IT R&D capabilities of enterprises, facilitating practical application and promotion. The data analysis and evaluation results provided can help project managers identify and solve potential problems in the IT project development process more quickly, improve project transparency and team communication efficiency. In addition, if the global optimal solution cannot be solved, the project deadlines corresponding to some low-priority IT R&D projects can be increased or some low-priority IT R&D projects can be removed. In this way, when it is impossible to ensure that all IT R&D projects can be completed smoothly on schedule, try to ensure that high-priority IT R&D projects can be completed on schedule.

[0083] See also Figure 2The second aspect of the embodiment of the present application provides an IT R&D energy efficiency evaluation system based on comprehensive data analysis, and the IT R&D energy efficiency evaluation system based on comprehensive data analysis includes:

[0084] Establish a unit for establishing an IT R&D efficiency scoring model related to the benefits of early completion, human cost, and time cost of IT R&D projects based on the project development time of each IT R&D project in the enterprise's IT R&D project list, the project deadline of each IT R&D project, and the total amount of IT R&D human resources that can be allocated by the enterprise;

[0085] A calculation unit is used to solve the global optimal solution by using a particle swarm optimization algorithm with the maximum IT R&D energy efficiency score as the goal, under the premise that the sum of the R&D human resources of each IT R&D project in the enterprise IT R&D project list is less than or equal to the total amount of IT R&D human resources, and obtain the IT R&D human resources allocation amount of each IT R&D project in the enterprise IT R&D project list;

[0086] The allocation unit is used to allocate IT R&D human resources to each IT R&D project based on the IT R&D human resources allocation amount of each IT R&D project in the enterprise IT R&D project list.

[0087] The working process, working details and technical effects of the IT R&D energy efficiency evaluation system based on comprehensive data analysis provided in the second aspect of this embodiment can be found in the first aspect of the embodiment and will not be described in detail here.

[0088] like Figure 3 As shown, the third aspect of an embodiment of the present application provides an electronic device, comprising a memory, a processor and a transceiver that are communicatively connected in sequence, wherein the memory is used to store computer programs, the transceiver is used to send and receive messages, and the processor is used to read the computer program to execute the IT R&D energy efficiency evaluation method based on comprehensive data analysis as described in the first aspect of the embodiment.

[0089] For specific examples, the memory may include but is not limited to random access memory (RAM), read-only memory (ROM), flash memory, first-in-first-out memory (FIFO) and / or first-in-last-out memory (FILO), etc.; the processor may be but is not limited to a microprocessor of the STM32F105 series, an ARM (Advanced RISC-Machines), an X86 or other architecture processor, or a processor with an integrated NPU (neural-network processing units); the transceiver may be but is not limited to a WiFi (Wireless Fidelity) wireless transceiver, a Bluetooth wireless transceiver, a General Packet Radio Service (GPRS) wireless transceiver, a ZigBee protocol (a low-power local area network protocol based on the IEEE802.15.4 standard, ZigBee) wireless transceiver, a 3G transceiver, a 4G transceiver and / or a 5G transceiver, etc.

[0090] The working process, working details and technical effects of the electronic device provided in the third aspect of this embodiment can be found in the first aspect of the embodiment and will not be described in detail here.

[0091] In a fourth aspect of this embodiment, there is provided a computer-readable storage medium storing instructions for the IT R&D energy efficiency evaluation method based on comprehensive data analysis as described in the first aspect of the embodiment, that is, the computer-readable storage medium stores instructions, and when the instructions are executed on a computer, the IT R&D energy efficiency evaluation method based on comprehensive data analysis as described in the first aspect is executed. The computer-readable storage medium refers to a carrier for storing data, which may include but is not limited to a floppy disk, an optical disk, a hard disk, a flash memory, a USB flash drive, and / or a memory stick, etc., and the computer may be a general-purpose computer, a special-purpose computer, a computer network, or other programmable devices.

[0092] The fifth aspect of this embodiment provides a computer program product comprising instructions, which, when executed on a computer, enables the computer to execute the IT R&D energy efficiency assessment method based on comprehensive data analysis as described in the first aspect of the embodiment, wherein the computer may be a general-purpose computer, a special-purpose computer, a computer network, or other programmable devices.

[0093] It should be understood that certain details are provided in the following description to facilitate a complete understanding of the example embodiments. However, it should be understood by those of ordinary skill in the art that the example embodiments can be implemented without these certain details. For example, the system can be shown in a block diagram to avoid obscuring the example with unnecessary details. In other examples, well-known processes, structures, and techniques may not be shown in unnecessary detail to avoid obscuring the example embodiments.

[0094] Finally, it should be noted that the above description is only a preferred embodiment of the present invention and is not intended to limit the protection scope of the present invention. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A method for evaluating IT R&D energy efficiency based on comprehensive data analysis, characterized in that: include: Based on the project development time of each IT R&D project in the enterprise's IT R&D project list, the project deadline of each IT R&D project, and the total amount of IT R&D human resources that can be allocated by the enterprise, an IT R&D energy efficiency scoring model related to the early completion benefits, human cost, and time cost of IT R&D projects is established; Taking the maximum IT R&D energy efficiency score as the goal, the particle swarm optimization algorithm is used to solve the global optimal solution under the premise that the sum of the R&D human resources of each IT R&D project in the enterprise IT R&D project list is less than or equal to the total amount of IT R&D human resources, and the IT R&D human resources allocation amount of each IT R&D project in the enterprise IT R&D project list is obtained; Allocate IT R&D human resources to each IT R&D project based on the IT R&D human resources allocation amount of each IT R&D project in the enterprise IT R&D project list; The IT R&D energy efficiency scoring model is: , where P represents the sum of IT R&D energy efficiency scores of all IT R&D projects, n represents the total number of IT R&D projects in the enterprise IT R&D project list, represents the energy efficiency score of the i-th IT R&D project, The duration of the project corresponding to the i IT R&D projects represented by represents the project development duration of the i-th IT R&D project, represents the IT R&D human resources allocation for the i-th IT R&D project, a, b and c are all known proportional coefficients, It indicates the total amount of IT R&D human resources that can be allocated by the enterprise; The method further comprises: Based on multiple historical IT R&D project lists that have not been overdue, the project development duration of historical IT R&D projects in each historical IT R&D project list, the project deadline duration corresponding to the historical IT R&D projects, and the total amount of IT R&D human resources that can be allocated by the enterprise corresponding to each historical IT R&D project list during the same period, the values ​​of the proportional coefficients a, b, and c in the IT R&D energy efficiency scoring model are solved when the IT R&D energy efficiency score is the maximum, and multiple arrays corresponding to multiple historical IT R&D project lists are obtained; Solving the values ​​of proportional coefficients a, b and c based on the multiple arrays; Solving the values ​​of the proportional coefficients a, b and c based on the multiple arrays includes: Performing bottom-up hierarchical clustering on the plurality of arrays; When there are two clusters left, the cluster with the most corresponding arrays is selected as the target cluster; Calculating the cluster center of the target cluster, and determining the values ​​of proportional coefficients a, b and c based on the values ​​corresponding to the cluster center; The method further comprises: If the global optimal solution is not found, the project duration corresponding to the target IT R&D project in the enterprise IT R&D project list is incremented by 1 and the global optimal solution is found again. The target IT R&D project is the IT R&D project with the lowest priority in the enterprise IT R&D project list. If the global optimal solution is still not found after adding N to the project deadline of the target IT R&D project, the target IT R&D project is removed from the enterprise IT R&D project list to update the enterprise IT R&D project list, where N is a positive integer greater than 1; Taking the maximum IT R&D energy efficiency score as the goal, the particle swarm optimization algorithm is used to solve the global optimal solution under the premise that the sum of the R&D human resources of each IT R&D project in the updated enterprise IT R&D project list is less than or equal to the total amount of IT R&D human resources, and the IT R&D human resource allocation of each IT R&D project in the updated enterprise IT R&D project list is obtained.

2. The IT R&D energy efficiency evaluation method based on comprehensive data analysis according to claim 1 is characterized in that: Taking the maximum IT R&D energy efficiency score as the goal, the particle swarm optimization algorithm is used to solve the global optimal solution under the premise that the sum of the R&D human resources of each IT R&D project in the enterprise IT R&D project list is less than or equal to the total amount of IT R&D human resources, including: Initializing a particle population, wherein the particle population includes IT R&D human resource allocations of each IT R&D project; Based on the IT R&D energy efficiency scoring model, the fitness function of the population example algorithm is determined. Based on the fitness function, the fitness value of each particle in the particle population is calculated, and the fitness value of each particle is used as the local optimal solution position. The position corresponding to the particle with the largest fitness value among all particles is used as the global optimal solution position. Update the particles in the particle population; Calculate the fitness value of each particle in the updated particle population, and update the local optimal solution position and the global optimal solution position of each particle based on the fitness value of each particle in the particle population; If the fitness value corresponding to the current global optimal solution position does not reach the preset threshold, the particles of the particle population are updated again to re-update the local optimal solution position and the global optimal solution position of each particle; If the fitness value corresponding to the latest global optimal solution position reaches a preset threshold or the number of iterations reaches a preset number, the update is stopped.

3. The IT R&D energy efficiency evaluation method based on comprehensive data analysis according to claim 1 is characterized in that: The amount of IT R&D human resources allocated to each IT R&D project is a positive integer.

4. An IT R&D energy efficiency evaluation system based on comprehensive data analysis, characterized in that: include: Establish a unit for establishing an IT R&D efficiency scoring model related to the benefits of early completion, human cost, and time cost of IT R&D projects based on the project development time of each IT R&D project in the enterprise's IT R&D project list, the project deadline of each IT R&D project, and the total amount of IT R&D human resources that can be allocated by the enterprise; A calculation unit is used to solve the global optimal solution by using a particle swarm optimization algorithm with the maximum IT R&D energy efficiency score as the goal, under the premise that the sum of the R&D human resources of each IT R&D project in the enterprise IT R&D project list is less than or equal to the total amount of IT R&D human resources, and obtain the IT R&D human resources allocation amount of each IT R&D project in the enterprise IT R&D project list; An allocation unit is used to allocate IT R&D human resources to each IT R&D project based on the IT R&D human resources allocation amount of each IT R&D project in the enterprise IT R&D project list; The IT R&D energy efficiency scoring model is: , where P represents the sum of IT R&D energy efficiency scores of all IT R&D projects, n represents the total number of IT R&D projects in the enterprise IT R&D project list, represents the energy efficiency score of the i-th IT R&D project, The duration of the project corresponding to the i IT R&D projects represented by represents the project development duration of the i-th IT R&D project, represents the IT R&D human resources allocation for the i-th IT R&D project, a, b and c are all known proportional coefficients, It indicates the total amount of IT R&D human resources that can be allocated by the enterprise; Based on the project development duration of the historical IT R&D projects in each historical IT R&D project list, the project deadline duration corresponding to the historical IT R&D projects, and the total IT R&D human resources that can be allocated by the enterprise corresponding to each historical IT R&D project list during the same period, in multiple historical IT R&D project lists that have not been overdue, solve the values ​​of the proportional coefficients a, b, and c in the IT R&D energy efficiency scoring model when the IT R&D energy efficiency score is maximized, and obtain multiple arrays corresponding to the multiple historical IT R&D project lists one by one; and Solving the values ​​of proportional coefficients a, b and c based on the multiple arrays; Solving the values ​​of the proportional coefficients a, b and c based on the multiple arrays includes: Performing bottom-up hierarchical clustering on the plurality of arrays; When there are two clusters left, the cluster with the most corresponding arrays is selected as the target cluster; Calculating the cluster center of the target cluster, and determining the values ​​of proportional coefficients a, b and c based on the values ​​corresponding to the cluster center; The calculation unit is further used to, if a global optimal solution is not found, then add 1 to the project deadline corresponding to the target IT R&D project in the enterprise IT R&D project list and then re-solve the global optimal solution, where the target IT R&D project is an IT R&D project with the lowest priority in the enterprise IT R&D project list; If the global optimal solution is still not found after adding N to the project deadline of the target IT R&D project, the target IT R&D project is removed from the enterprise IT R&D project list to update the enterprise IT R&D project list, where N is a positive integer greater than 1; and Taking the maximum IT R&D energy efficiency score as the goal, the particle swarm optimization algorithm is used to solve the global optimal solution under the premise that the sum of the R&D human resources of each IT R&D project in the updated enterprise IT R&D project list is less than or equal to the total amount of IT R&D human resources, and the IT R&D human resource allocation of each IT R&D project in the updated enterprise IT R&D project list is obtained.

5. An electronic device, characterized in that: It includes a memory, a processor and a transceiver which are communicatively connected in sequence, wherein the memory is used to store a computer program, the transceiver is used to send and receive messages, and the processor is used to read the computer program to execute the IT R&D energy efficiency evaluation method based on comprehensive data analysis as described in any one of claims 1 to 3.

6. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores instructions, and when the instructions are executed on a computer, the IT R&D energy efficiency evaluation method based on comprehensive data analysis as described in any one of claims 1 to 3 is executed.

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