An Instrument Service Unit Instrument Usage Performance Evaluation Method and System

Abstract

The present invention relates to a method and system for evaluating the instrument usage performance of an instrument service unit. The method includes: dividing a preset time length into unit time lengths; combining unit time periods with similar distributions of assessment index data; obtaining the assessment index data corresponding to each of multiple instrument service units in multiple combined time periods; and performing performance evaluation of the instrument service units by combining the assessment index data corresponding to each of multiple instrument service units in multiple combined time periods through the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) twice. The overall performance evaluation of the preset time length is divided into multiple unit time periods for separate evaluation, making the evaluation process more comparable; combining unit time periods with similar distribution information of assessment index data improves the performance evaluation efficiency; and by using the TOPSIS twice, on the basis of ensuring data comparability, the overall performance evaluation result within the preset time length is obtained.

Description

Technical Field

[0001] Multiple embodiments of this specification relate to the technical field of instrument management, and specifically to a method and system for evaluating the instrument usage performance of an instrument service unit. Background Art

[0002] In the context of the Internet of Things era, big data strongly supports resource sharing. Some resources such as scientific research instruments and experimental equipment can be shared. Usually, the unit that owns the experimental instruments is used as the instrument service unit, and the information of the experimental instruments it owns is entered into the shared instrument reservation platform. Users who do not own experimental instruments can then make reservations for experimental instruments on the shared instrument reservation platform. For example, the Chinese invention patent with the application number 202110166263.X discloses a management method and system for shared instruments. Users can use the online reservation method to make reservations for the use of shared instruments, with simple procedures and relatively easy processes.

[0003] For the shared instrument reservation platform, the instrument service unit needs to take on the responsibility of ensuring the efficient operation of the instruments. To improve the instrument usage efficiency and ensure the fairness and sustainability of resource sharing, it is necessary to conduct a reasonable performance evaluation of the instrument usage of the instrument service unit. Through performance evaluation, the operation status and service quality of the instruments can be comprehensively grasped, and then the resource allocation can be optimized and the service level can be improved. At the same time, a reasonable performance evaluation system can also motivate the instrument service unit to improve its management ability, ensure the effective utilization of shared resources, and promote the smooth progress of scientific research work. Summary of the Invention

[0004] Embodiments of this specification provide a method and system for evaluating the instrument usage performance of an instrument service unit, which can conduct a reasonable performance evaluation of the instrument usage situation of each instrument service unit.

[0005] The technical solution is as follows:

[0006] In a first aspect, embodiments of this specification provide a method for evaluating the instrument usage performance of an instrument service unit, including:

[0007] Dividing a preset time length based on a unit time length to obtain multiple unit time periods;

[0008] Obtaining a first set of evaluation index data corresponding to each instrument service unit, where the first set of evaluation index data includes the evaluation index data corresponding to each instrument service unit within multiple unit time periods;

[0009] Based on the first assessment index datasets corresponding to each instrument service unit, obtain the assessment index data distribution information corresponding to each of multiple unit time periods, which can reflect the overall distribution of the assessment index data of all instrument service units. And based on the assessment index data distribution information corresponding to each of the multiple unit time periods, combine the multiple unit time periods to obtain multiple combined time periods;

[0010] Based on the unit time period combination situations corresponding to each of the multiple combined time periods and the first assessment index datasets corresponding to each instrument service unit, obtain the second assessment index datasets corresponding to each instrument service unit. The second assessment index datasets include the assessment index data corresponding to each instrument service unit within the multiple combined time periods;

[0011] Based on the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) and the second assessment index datasets corresponding to each instrument service unit, obtain the performance assessment datasets corresponding to each instrument service unit. The performance assessment datasets include the performance data corresponding to each instrument service unit within the multiple combined time periods;

[0012] Based on the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) and the performance assessment datasets corresponding to each instrument service unit, obtain the performance evaluation results corresponding to each instrument service unit.

[0013] As a preferred solution, the assessment index data includes the assessment index values corresponding to multiple assessment categories. The multiple assessment categories include at least two of the instrument reservation quantity, instrument operation duration, charging amount, instrument external sharing score, and instrument maintenance expenditure;

[0014] Before obtaining the assessment index data distribution information corresponding to each of the multiple unit time periods, which can reflect the overall distribution of the assessment index data of all instrument service units, based on the first assessment index datasets corresponding to each instrument service unit, it further includes: obtaining multiple preset numerical ranges corresponding to the multiple assessment categories;

[0015] The step of obtaining the assessment index data distribution information corresponding to each of the multiple unit time periods, which can reflect the overall distribution of the assessment index data of all instrument service units, based on the first assessment index datasets corresponding to each instrument service unit, and combining the multiple unit time periods based on the assessment index data distribution information corresponding to each of the multiple unit time periods to obtain multiple combined time periods, includes:

[0016] Based on the first assessment index datasets corresponding to each instrument service unit and the multiple preset numerical ranges corresponding to the multiple assessment categories, obtain the assessment index data distribution information corresponding to each of the multiple unit time periods. The assessment index data distribution information includes the distribution quantities of the overall assessment index data of all instrument service units within the unit time period in different preset numerical ranges of each assessment category;

[0017] Based on the assessment index data distribution information corresponding to each of the multiple unit time periods, obtain the assessment index data distribution similarity between each unit time period;

[0018] Based on the assessment index data distribution similarity between each unit time period, combine the multiple unit time periods to obtain multiple combined time periods.

[0019] As an optimal solution, the obtaining of the performance assessment datasets corresponding to each instrument service unit based on the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) and the second assessment index datasets corresponding to each instrument service unit includes:

[0020] For each combined time period, perform a clustering operation on all instrument service units based on the assessment index data corresponding to each instrument service unit within the combined time period to obtain multiple instrument service unit clustering groups corresponding to the combined time period;

[0021] For each instrument service unit clustering group, obtain the index representative data corresponding to the instrument service unit clustering group based on the assessment index data corresponding to each instrument service unit within the combined time period corresponding to the instrument service unit clustering group;

[0022] For each combined time period, obtain the performance dataset corresponding to the combined time period based on the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) and the index representative data corresponding to the multiple instrument service unit clustering groups corresponding to the combined time period. The performance dataset corresponding to the combined time period includes the performance data corresponding to the multiple instrument service unit clustering groups corresponding to the combined time period;

[0023] Based on the performance datasets corresponding to each combined time period, obtain the performance assessment datasets corresponding to each instrument service unit.

[0024] As an optimal solution, for each instrument service unit clustering group, obtain the index representative data corresponding to the instrument service unit clustering group by taking the average based on the assessment index data corresponding to each instrument service unit within the combined time period corresponding to the instrument service unit clustering group.

[0025] As a preferred solution, based on the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) and the representative data of indicators corresponding to multiple instrument service unit clustering groups corresponding to the combined time period, a performance data set corresponding to the combined time period is obtained, including:

[0026] Based on the representative data of indicators corresponding to multiple instrument service unit clustering groups corresponding to the combined time period, obtain the positive ideal solution and negative ideal solution of the indicators corresponding to the combined time period;

[0027] Based on the representative data of indicators corresponding to multiple instrument service unit clustering groups corresponding to the combined time period, the positive ideal solution of the indicators corresponding to the combined time period, and the negative ideal solution of the indicators, obtain the performance data set corresponding to the combined time period.

[0028] As a preferred solution, the representative data of the indicators includes the indicator values corresponding to multiple assessment categories, and the positive ideal solution and negative ideal solution of the indicators also include the indicator values corresponding to multiple assessment categories;

[0029] In the process of obtaining the performance data set corresponding to the combined time period based on the representative data of indicators corresponding to multiple instrument service unit clustering groups corresponding to the combined time period, the positive ideal solution of the indicators corresponding to the combined time period, and the negative ideal solution of the indicators, the acquisition of the performance data of any instrument service unit clustering group in the combined time period includes:

[0030] Based on the indicator values corresponding to multiple assessment categories in the representative data of the indicator of the instrument service unit clustering group and the indicator values corresponding to multiple assessment categories in the positive ideal solution of the indicators, obtain the first positive distance;

[0031] Based on the indicator values corresponding to multiple assessment categories in the representative data of the indicator of the instrument service unit clustering group and the indicator values corresponding to multiple assessment categories in the negative ideal solution of the indicators, obtain the first negative distance;

[0032] Based on the first positive distance and the first negative distance, obtain the performance data of the instrument service unit clustering group.

[0033] As a preferred solution, the process of obtaining the performance evaluation results corresponding to each instrument service unit based on the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) and the performance assessment data set corresponding to each instrument service unit includes:

[0034] Based on the performance assessment data set corresponding to each instrument service unit, obtain the positive ideal solution and negative ideal solution of the performance corresponding to the preset time length;

[0035] Based on the performance assessment data set corresponding to each instrument service unit, the positive ideal solution of the performance corresponding to the preset time length, and the negative ideal solution of the performance, obtain the performance evaluation results corresponding to each instrument service unit.

[0036] As a preferred solution, both the positive ideal solution of performance and the negative ideal solution of performance include performance data corresponding to respective multiple combined time periods;

[0037] In the obtaining of the performance evaluation results corresponding to respective instrument service units based on the performance evaluation data sets corresponding to respective instrument service units, the positive ideal solution of performance corresponding to a preset time length, and the negative ideal solution of performance, the obtaining of the performance evaluation result for any instrument service unit includes:

[0038] Obtaining a second positive distance based on the performance data corresponding to respective multiple combined time periods of the instrument service unit and the performance data corresponding to respective multiple combined time periods in the positive ideal solution of performance;

[0039] Obtaining a second negative distance based on the performance data corresponding to respective multiple combined time periods of the instrument service unit and the performance data corresponding to respective multiple combined time periods in the negative ideal solution of performance;

[0040] Obtaining the performance data of the instrument service unit based on the second positive distance and the second negative distance.

[0041] As a preferred solution, after obtaining the performance evaluation data sets corresponding to respective instrument service units, it further includes:

[0042] Obtaining a graph that can respectively reflect the comparison of the performance data of each instrument service unit in different combined time periods based on the performance evaluation data sets corresponding to respective instrument service units.

[0043] In a second aspect, an instrument use performance evaluation system for an instrument service unit provided in an embodiment of this specification, based on the method for evaluating the instrument use performance of an instrument service unit in the first aspect of the above embodiment, includes:

[0044] A division module that divides a preset time length based on a unit time length as a division basis to obtain multiple unit time periods;

[0045] A first obtaining module that obtains the first evaluation index data sets corresponding to respective instrument service units, where the first evaluation index data sets include the evaluation index data corresponding to respective instrument service units in multiple unit time periods;

[0046] A combination module that obtains the evaluation index data distribution information that can reflect the overall distribution of the evaluation index data of all instrument service units corresponding to respective multiple unit time periods based on the first evaluation index data sets corresponding to respective instrument service units, and combines multiple unit time periods based on the evaluation index data distribution information corresponding to respective multiple unit time periods to obtain multiple combined time periods;

[0047] The second acquisition module obtains the second evaluation index data set corresponding to each instrument service unit based on the unit time period combination corresponding to each of the multiple combined time periods and the first evaluation index data set corresponding to each instrument service unit. The second evaluation index data set includes the evaluation index data corresponding to each instrument service unit within the multiple combined time periods.

[0048] The third acquisition module obtains the performance evaluation data set corresponding to each instrument service unit based on the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) and the second evaluation index data set corresponding to each instrument service unit. The performance evaluation data set includes the performance data corresponding to each instrument service unit within the multiple combined time periods.

[0049] The fourth acquisition module obtains the performance evaluation result corresponding to each instrument service unit based on the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) and the performance evaluation data set corresponding to each instrument service unit.

[0050] In a third aspect, an embodiment of the present specification provides an electronic device, including a processor and a memory; the processor is connected to the memory; the memory is used to store executable program code; the processor runs a program corresponding to the executable program code by reading the executable program code stored in the memory to execute the steps described in the first aspect of the above embodiment.

[0051] In a fourth aspect, an embodiment of the present specification provides a computer storage medium, which stores multiple instructions, and the instructions are suitable for being loaded and executed by a processor to execute the steps described in the first aspect of the above embodiment.

[0052] The beneficial effects brought by the technical solutions provided in some embodiments of the present specification at least include:

[0053] First, the preset time length is divided into unit time lengths, and further, the unit time periods with similar evaluation index data distribution are combined, and the evaluation index data corresponding to each of the multiple instrument service units within the multiple combined time periods is obtained. Subsequently, the performance evaluation of the instrument service units is carried out based on the evaluation index data corresponding to each of the multiple instrument service units within the multiple combined time periods. First, the overall performance evaluation of the preset time length is divided into multiple unit time periods for separate evaluation, making the evaluation process more comparable; second, since the unit time periods with similar evaluation index data distribution information are combined, and subsequently the performance evaluation of the instrument service units is carried out based on the evaluation index data corresponding to each of the multiple instrument service units within the multiple combined time periods, the performance evaluation efficiency is improved.

[0054] Through the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method, first, on the basis of ensuring data comparability, performance data corresponding to each of multiple instrument service units in multiple combined time periods is obtained; further, based on the performance assessment data sets corresponding to each instrument service unit, a performance assessment result representing the performance of each instrument service unit over the entire preset time length is obtained.

[0055] When obtaining the performance assessment data sets corresponding to each instrument service unit, for each combined time period, clustering of the instrument service units is performed based on the assessment index data of each instrument service unit in the combined time period to obtain multiple clusters of instrument service units, and further, index representative data corresponding to each of the multiple clusters of instrument service units is obtained. Subsequently, based on the TOPSIS method and the index representative data corresponding to each of the multiple clusters of instrument service units, performance data corresponding to each of the multiple clusters of instrument service units is obtained, and the performance assessment data of the instrument service units in the cluster of instrument service units is directly represented by the performance data corresponding to the cluster of instrument service units. That is, by clustering the instrument service units, the performance assessment efficiency is further improved. Description of the Drawings

[0056] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required for use in the description of the embodiments or the prior art. Obviously, the following drawings are only some embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0057] Figure 1 It is a flowchart showing the method for evaluating the instrument usage performance of an instrument service unit provided in an embodiment of this specification.

[0058] Figure 2 It is a structural diagram showing the instrument usage performance evaluation system of an instrument service unit provided in an embodiment of this specification.

[0059] Figure 3 It is a structural diagram showing an electronic device provided in an embodiment of this specification. Detailed Embodiments

[0060] The following will clearly and completely describe the technical solutions in the embodiments of this specification with reference to the drawings in the embodiments of this specification.

[0061] In the specification, claims, and the above-mentioned drawings of this specification, the terms "first", "second", "third", etc. are used to distinguish different objects, rather than to describe a specific order. In addition, the terms "comprising" and "having" and any variations thereof are intended to cover non-exclusive inclusion. For example, a process, method, system, product, or device that includes a series of steps or units is not limited to the listed steps or units, but optionally further includes steps or units not listed, or optionally further includes other steps or units inherent to these processes, methods, products, or devices.

[0062] The following description provides examples and does not limit the scope, applicability, or examples set forth in the claims. Changes can be made to the functions and arrangements of the described elements without departing from the scope of the content of this specification. Various processes or components can be appropriately omitted, substituted, or added to each example. For example, the described method can be executed in a different order than the described order, and various steps can be added, omitted, or combined. In addition, the features described in some examples can be combined into other examples.

[0063] Referring to Figure 1 as shown Figure 1 is a schematic flow diagram of a method for evaluating the instrument usage performance of an instrument service unit provided in an embodiment of this specification, and may at least include the following steps:

[0064] Step 102: Divide a preset time length based on the unit time length to obtain a plurality of unit time periods.

[0065] The unit time length described here can be divided according to the actual situation. For example, it can be divided by hour, by day, or by week.

[0066] Step 104: Obtain the first evaluation index data set corresponding to each instrument service unit, where the first evaluation index data set includes the evaluation index data corresponding to each instrument service unit in a plurality of unit time periods.

[0067] Step 106: Based on the first evaluation index data set corresponding to each instrument service unit, obtain the evaluation index data distribution information that can reflect the overall distribution of the evaluation index data of all instrument service units corresponding to each of the plurality of unit time periods, and based on the evaluation index data distribution information corresponding to each of the plurality of unit time periods, combine the plurality of unit time periods to obtain a plurality of combined time periods.

[0068] Step 108: Based on the combination of unit time periods corresponding to each of the multiple combined time periods and the first performance evaluation index datasets corresponding to each instrument service unit, obtain the second performance evaluation index datasets corresponding to each instrument service unit. The second performance evaluation index datasets include the performance evaluation index data corresponding to each instrument service unit within the multiple combined time periods.

[0069] Step 110: Based on the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) and the second performance evaluation index datasets corresponding to each instrument service unit, obtain the performance appraisal datasets corresponding to each instrument service unit. The performance appraisal datasets include the performance data corresponding to each instrument service unit within the multiple combined time periods.

[0070] Step 112: Based on the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) and the performance appraisal datasets corresponding to each instrument service unit, obtain the performance evaluation results corresponding to each instrument service unit.

[0071] Among them, the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) is a multi-attribute decision-making method used to select the best solution from multiple options. This method evaluates by calculating the distances between each solution and the ideal solution and the negative ideal solution, and arranges the priorities of the solutions based on these distances.

[0072] Therefore, when applying this method to the performance evaluation of multiple instrument service units, the optimal index data among the multiple instrument service units can be used as the ideal solution, and the worst index data can be used as the negative ideal solution. Subsequently, based on the index data, ideal solution, and negative ideal solution corresponding to each of the multiple instrument service units, the distance information between the index data corresponding to each of the multiple instrument service units and the ideal solution and the negative ideal solution can be obtained. Furthermore, based on the distance information corresponding to each of the multiple instrument service units, the performance appraisal of the multiple instrument service units can be carried out. The specific calculation method will be described in detail in the corresponding embodiments below.

[0073] It can be understood that currently, when conducting performance appraisals, it is usually directly based on various performance evaluation index values over a relatively long period. However, the various performance evaluation indexes over a relatively long period reflect the comprehensive performance of the evaluation object over a relatively long period and cannot reflect the performance of the evaluation object in different time periods within the relatively long period.

[0074] For example: It is unreasonable to compare the performance of instrument service unit A in the morning time period with the performance of instrument service unit B in the afternoon time period to determine which of the two instrument service units is better or worse. Therefore, when conducting performance appraisals based on the comprehensive performance over a relatively long period, the above problems are likely to occur.

[0075] Therefore, in the performance evaluation method provided in the embodiments of this specification, first, the preset time length is divided into unit time lengths, and further, the unit time periods with similar distributions of assessment index data are combined, and the assessment index data corresponding to each of multiple instrument service units in multiple combined time periods are obtained. Subsequently, for the performance evaluation of the instrument service units, it is based on the assessment index data corresponding to each of the multiple instrument service units in multiple combined time periods. First, the overall performance evaluation of the preset time length is divided into multiple unit time periods for individual evaluation to make the evaluation process more comparable; second, since the unit time periods with similar distribution information of assessment index data are combined, and subsequently, the performance evaluation of the instrument service units is based on the assessment index data corresponding to each of the multiple instrument service units in multiple combined time periods, the performance evaluation efficiency is improved.

[0076] In the performance evaluation method provided in the embodiments of this specification, through the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) twice, first, on the basis of ensuring data comparability, the performance data corresponding to each of multiple instrument service units in multiple combined time periods are obtained; further, based on the performance assessment data sets corresponding to each instrument service unit, the performance evaluation results that can represent the performance of each instrument service unit in the entire preset time length are obtained. The specific calculation method will be described in the corresponding embodiments below.

[0077] In some embodiments of this specification:

[0078] The assessment index data include the assessment index values corresponding to multiple assessment categories, and the multiple assessment categories include at least two of the instrument reservation quantity, instrument operation duration, charging amount, external sharing score of the instrument, and instrument maintenance expenditure. The external sharing score of the instrument is the experience score given by external instrument users after using the instrument.

[0079] Before obtaining the distribution information of the assessment index data corresponding to each of the multiple unit time periods, which can reflect the overall distribution of the assessment index data of all instrument service units, based on the first assessment index data set corresponding to each instrument service unit, it further includes: obtaining multiple preset numerical ranges corresponding to multiple assessment categories;

[0080] For example, for the instrument operation duration, three preset numerical ranges of 1 hour to 3 hours, 3 hours to 6 hours, and 6 hours to 9 hours are set; for the charging amount, three preset numerical ranges of 100 yuan to 300 yuan, 300 yuan to 600 yuan, and 600 yuan to 900 yuan are set, and specific settings can be made according to actual needs.

[0081] Based on the first evaluation index datasets corresponding to each instrument service unit, obtain the evaluation index data distribution information corresponding to each of multiple unit time periods, which can reflect the overall distribution of the evaluation index data of all instrument service units, and combine the multiple unit time periods based on the evaluation index data distribution information corresponding to each of the multiple unit time periods to obtain multiple combined time periods, including:

[0082] Step 1062: Based on the first evaluation index datasets corresponding to each instrument service unit and the multiple preset numerical ranges corresponding to multiple evaluation categories, obtain the evaluation index data distribution information corresponding to each of multiple unit time periods. The evaluation index data distribution information includes the distribution quantities of the overall evaluation index data of all instrument service units within different preset numerical ranges of each evaluation category during the unit time period;

[0083] Taking only instrument service unit A and instrument service unit B as an example for explanation:

[0084] Suppose:

[0085] The instrument operation duration of instrument service unit A in unit time period 1 is 4 hours, and the charging amount is 400 yuan;

[0086] The instrument operation duration of instrument service unit B in unit time period 1 is 5 hours, and the charging amount is 500 yuan;

[0087] Therefore, the quantity of the overall evaluation index data of all instrument service units within the range of 3 hours to 6 hours in the instrument operation duration evaluation category during time period 1 is 2; the quantity of the overall evaluation index data of all instrument service units within the range of 300 yuan to 600 yuan in the charging amount evaluation category during time period 1 is 2.

[0088] The instrument operation duration of instrument service unit A in unit time period 2 is 7 hours, and the charging amount is 700 yuan;

[0089] The instrument operation duration of instrument service unit B in unit time period 2 is 8 hours, and the charging amount is 800 yuan;

[0090] Therefore, the quantity of the overall evaluation index data of all instrument service units within the range of 6 hours to 9 hours in the instrument operation duration evaluation category during time period 2 is 2; the quantity of the overall evaluation index data of all instrument service units within the range of 600 yuan to 900 yuan in the charging amount evaluation category during time period 2 is 2.

[0091] The instrument operation duration of instrument service unit A in unit time period 3 is 5 hours, and the charging amount is 400 yuan;

[0092] Instrument service unit B has an instrument operation duration of 4 hours and a charging amount of 500 yuan in unit time period 3;

[0093] Therefore, in time period 3, the overall number of assessment index data of all instrument service units within the range of 3 hours to 6 hours in the instrument operation duration assessment category is 2; in time period 3, the overall number of assessment index data of all instrument service units within the range of 300 yuan to 600 yuan in the charging amount assessment category is 2.

[0094] Step 1064: Based on the distribution information of the assessment index data corresponding to each unit time period, obtain the similarity of the assessment index data distribution between each unit time period.

[0095] Here, no specific similarity calculation method is limited, but it can be understood that based on the assessment index data distribution information presented in the above example, the similarity between time period 1 and time period 3 is higher than the similarity between time period 1 and time period 2.

[0096] Step 1066: Combine multiple unit time periods based on the similarity of the assessment index data distribution between each unit time period to obtain multiple combined time periods.

[0097] It can be understood that time period 1 and time period 3 in the above example can be combined to obtain a new combined time period.

[0098] For step 108, it is also continued to be described based on the above example:

[0099] That is, within the combined time period obtained by combining time period 1 and time period 3, the assessment index data of instrument service unit A includes: the instrument operation duration is 4 hours + 5 hours = 9 hours, and the charging amount is 400 yuan + 400 yuan = 800 yuan;

[0100] Within the combined time period obtained by combining time period 1 and time period 3, the assessment index data of instrument service unit B includes: the instrument operation duration is 5 hours + 4 hours = 9 hours, and the charging amount is 500 yuan + 500 yuan = 1000 yuan.

[0101] In some embodiments of the present specification, the obtaining of the performance assessment data set corresponding to each instrument service unit based on the technique for order preference by similarity to ideal solution and the second assessment index data set corresponding to each instrument service unit includes:

[0102] Step 1102: For each combined time period, perform a clustering operation on all instrument service units based on the assessment index data corresponding to each instrument service unit within the combined time period to obtain multiple instrument service unit clustering groups corresponding to the combined time period.

[0103] For example:

[0104] Instrument service unit A has an instrument operation duration of 5 hours and a charging amount of 400 yuan in combined time period 1;

[0105] Instrument service unit B has an instrument operation duration of 4 hours and a charging amount of 500 yuan in combined time period 1;

[0106] Instrument service unit C has an instrument operation duration of 8 hours and a charging amount of 800 yuan in combined time period 1;

[0107] Instrument service unit D has an instrument operation duration of 8 hours and a charging amount of 900 yuan in combined time period 1;

[0108] Then, for combined time period 1, through clustering operations, instrument service unit A and instrument service unit B can be clustered to obtain instrument service unit cluster group 1, and instrument service unit C and instrument service unit D can be clustered to obtain instrument service unit cluster group 2.

[0109] Step 1104: For each instrument service unit cluster group, based on the respective corresponding assessment index data of each instrument service unit in the combined time period corresponding to this instrument service unit cluster group, obtain the index representative data corresponding to this instrument service unit cluster group.

[0110] Taking instrument service unit cluster group 1 as an example for illustration:

[0111] Instrument service unit A has an instrument operation duration of 5 hours and a charging amount of 400 yuan in combined time period 1;

[0112] Instrument service unit B has an instrument operation duration of 4 hours and a charging amount of 500 yuan in combined time period 1;

[0113] Then the index representative data of instrument service unit cluster group 1 includes operation duration representative data and charging amount representative data.

[0114] And for each instrument service unit cluster group, based on the respective corresponding assessment index data of each instrument service unit in the combined time period corresponding to this instrument service unit cluster group, obtain the index representative data corresponding to this instrument service unit cluster group by taking the average.

[0115] Therefore, the index representative data of instrument service unit cluster group 1 includes an operation duration index value of 4.5 hours and a charging amount index value of 450 yuan.

[0116] Step 1106: For each combined time period, based on the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) and the representative index data corresponding to each of the multiple instrument service unit clustering groups corresponding to the combined time period, obtain the performance data set corresponding to the combined time period. The performance data set corresponding to the combined time period includes the performance data corresponding to each of the multiple instrument service unit clustering groups corresponding to the combined time period.

[0117] Step 1108: Based on the performance data sets corresponding to each combined time period, obtain the performance appraisal data sets corresponding to each instrument service unit.

[0118] It can be understood that when obtaining the performance appraisal data sets corresponding to each instrument service unit, for each combined time period, the instrument service units are clustered based on the assessment index data of each instrument service unit in the combined time period to obtain multiple instrument service unit clustering groups, and further obtain the representative index data corresponding to each of the multiple instrument service unit clustering groups. Subsequently, based on the TOPSIS and the representative index data corresponding to each of the multiple instrument service unit clustering groups, obtain the performance data corresponding to each of the multiple instrument service unit clustering groups, and the performance appraisal data of the instrument service units in the instrument service unit clustering group are directly represented by the performance data corresponding to the instrument service unit clustering group. That is, by clustering the instrument service units, the performance evaluation efficiency is further improved.

[0119] In some embodiments of this specification, obtaining the performance data set corresponding to the combined time period based on the TOPSIS and the representative index data corresponding to each of the multiple instrument service unit clustering groups corresponding to the combined time period includes:

[0120] Step 11062: Based on the representative index data corresponding to each of the multiple instrument service unit clustering groups corresponding to the combined time period, obtain the positive ideal solution of the index and the negative ideal solution of the index corresponding to the combined time period.

[0121] Step 11064: Based on the representative index data corresponding to each of the multiple instrument service unit clustering groups corresponding to the combined time period, the positive ideal solution of the index and the negative ideal solution of the index corresponding to the combined time period, obtain the performance data set corresponding to the combined time period.

[0122] The representative index data includes the index values corresponding to each of the multiple assessment categories, and both the positive ideal solution of the index and the negative ideal solution of the index also include the index values corresponding to each of the multiple assessment categories;

[0123] As described above, based on the representative data of indicators corresponding to each of the multiple instrument service unit clustering groups corresponding to the combined time period, the positive ideal solution of indicators corresponding to the combined time period, and the negative ideal solution of indicators, obtaining the performance data set corresponding to the combined time period, and the acquisition of the performance data for any instrument service unit clustering group in the combined time period includes:

[0124] Based on the indicator values corresponding to each of the multiple assessment categories in the representative data of indicators of the instrument service unit clustering group and the indicator values corresponding to each of the multiple assessment categories in the positive ideal solution of indicators, obtain the first positive distance;

[0125] Based on the indicator values corresponding to each of the multiple assessment categories in the representative data of indicators of the instrument service unit clustering group and the indicator values corresponding to each of the multiple assessment categories in the negative ideal solution of indicators, obtain the first negative distance;

[0126] Based on the first positive distance and the first negative distance, obtain the performance data of the instrument service unit clustering group.

[0127] Therefore, the performance data set corresponding to the combined time period is:

[0128] ;

[0129] Among them, represents the performance data corresponding to the rd instrument service unit clustering group corresponding to the th combined time period, represents the total number of instrument service unit clustering groups corresponding to the th combined time period;

[0130] Among them, , represents the distance (i.e., the first negative distance) between the representative data of indicators corresponding to the th instrument service unit clustering group corresponding to the th combined time period and the negative ideal solution of indicators corresponding to the th combined time period, represents the distance (i.e., the first positive distance) between the representative data of indicators corresponding to the th instrument service unit clustering group corresponding to the th combined time period and the positive ideal solution of indicators corresponding to the th combined time period;

[0131] Among them, , represents the indicator value of the th assessment category in the representative data of indicators corresponding to the th instrument service unit clustering group corresponding to the th combined time period, Indicates the value of the th assessment category in the negative ideal solution of the indicators corresponding to the th combined time period, represents the performance calculation adjustment coefficient corresponding to the

[0132] th assessment category (Note: Since there are differences in the value ranges of different assessment categories, adjustment coefficients need to be set); , Indicates the value of the th assessment category in the positive ideal solution of the indicators corresponding to the

[0133] It can be understood that both the positive ideal solution of the indicators and the negative ideal solution of the indicators contain the indicator values corresponding to multiple assessment categories respectively. The following is an example for illustration:

[0134] Suppose that combined time period 1 corresponds to instrument service unit clustering group 1, instrument service unit clustering group 2, and instrument service unit clustering group 3.

[0135] Among them, the indicator representative data corresponding to instrument service unit clustering group 1 include an operation duration indicator value of 4 hours and a charging amount indicator value of 800 yuan;

[0136] The indicator representative data corresponding to instrument service unit clustering group 2 include an operation duration indicator value of 5 hours and a charging amount indicator value of 1000 yuan.

[0137] The indicator representative data corresponding to instrument service unit clustering group 3 include an operation duration indicator value of 6 hours and a charging amount indicator value of 1200 yuan.

[0138] At this time, both the positive ideal solution of the indicators and the negative ideal solution of the indicators should contain the indicator values corresponding to the operation duration assessment category and the charging amount assessment category respectively.

[0139] Moreover, for example, if a higher charging amount and a shorter operation duration are desired, then 1200 yuan is selected as the indicator value corresponding to the charging amount assessment category in the positive ideal solution of the indicators, and 4 hours is selected as the indicator value corresponding to the operation duration assessment category in the positive ideal solution of the indicators. The negative ideal solution of the indicators is the opposite of the positive ideal solution of the indicators, which will not be elaborated here.

[0140] In some embodiments of this specification, obtaining the performance evaluation results corresponding to each instrument service unit based on the method of distance from the ideal solution of superiority and inferiority and the performance evaluation data sets corresponding to each instrument service unit includes:

[0141] Step 1122, obtaining the positive ideal solution of performance and the negative ideal solution of performance corresponding to the preset time length based on the performance evaluation data sets corresponding to each instrument service unit.

[0142] For example, assume that the performance data of instrument service unit A in combined time period 1 is 70, in combined time period 2 is 80, and in combined time period 3 is 90;

[0143] The performance data of instrument service unit B in combined time period 1 is 60, in combined time period 2 is 70, and in combined time period 3 is 80;

[0144] The performance data of instrument service unit C in combined time period 1 is 50, in combined time period 2 is 60, and in combined time period 3 is 70;

[0145] Then, the performance positive ideal solution corresponding to the preset time length includes the performance data 70 corresponding to the first combined time period, the performance data 80 corresponding to the second combined time period, and the performance data 90 corresponding to the third combined time period.

[0146] The performance negative ideal solution corresponding to the preset time length includes the performance data 50 corresponding to the first combined time period, the performance data 60 corresponding to the second combined time period, and the performance data 70 corresponding to the third combined time period.

[0147] For the acquisition of the performance positive ideal solution and the performance negative ideal solution, the principle is similar to the acquisition of the above-mentioned index positive ideal solution and index negative ideal solution, and will not be elaborated here.

[0148] Step 1124: Based on the performance assessment data sets corresponding to each instrument service unit, the performance positive ideal solution corresponding to the preset time length, and the performance negative ideal solution, obtain the performance assessment results corresponding to each instrument service unit.

[0149] Both the performance positive ideal solution and the performance negative ideal solution include the performance data corresponding to each of the multiple combined time periods;

[0150] In the process of obtaining the performance assessment results corresponding to each instrument service unit based on the performance assessment data sets corresponding to each instrument service unit, the performance positive ideal solution corresponding to the preset time length, and the performance negative ideal solution, the acquisition of the performance assessment result for any instrument service unit includes:

[0151] Based on the performance data corresponding to each of the multiple combined time periods of the instrument service unit and the performance data corresponding to each of the multiple combined time periods in the performance positive ideal solution, obtain the second positive distance;

[0152] Based on the performance data corresponding to each of the multiple combined time periods of the instrument service unit and the performance data corresponding to each of the multiple combined time periods in the performance negative ideal solution, obtain the second negative distance;

[0153] Obtain the performance data of the instrument service unit based on the second positive distance and the second negative distance.

[0154] Among them, the calculation formula for the performance evaluation result of the instrument service unit is as follows:

[0155] ;

[0156] Among them, represents the performance evaluation result of the th instrument service unit, represents the distance between the performance assessment data set corresponding to the th instrument service unit and the negative ideal solution of performance (i.e., the second negative distance), represents the distance between the performance assessment data set corresponding to the th instrument service unit and the positive ideal solution of performance (i.e., the second positive distance);

[0157] ;

[0158] Among them, represents the performance data corresponding to the th combination time period in the performance assessment data set corresponding to the th instrument service unit, represents the total number of combination time periods, represents the performance data corresponding to the th combination time period in the negative ideal solution of performance, represents the performance evaluation weight corresponding to the th combination time period (note: since the importance of different time periods for performance evaluation varies, it is necessary to set evaluation weights);

[0159] ;

[0160] Among them, represents the performance data corresponding to the th combination time period in the positive ideal solution of performance.

[0161] In some embodiments of this specification, after obtaining the performance assessment data sets corresponding to each instrument service unit, it further includes:

[0162] Based on the performance assessment data sets corresponding to each instrument service unit, obtain a graph that can respectively reflect the performance data comparison of each instrument service unit in different combination time periods.

[0163] Combine the graph to display the performance comparison, such as a bar chart, a line chart, etc.

[0164] The above description is for specific embodiments of this specification. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recited in the claims can be performed in a different order than in the embodiments and still achieve the desired results. Additionally, the processes depicted in the drawings do not necessarily require the specific order or sequential order shown to achieve the desired results. In certain embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0165] Next, please refer to Figure 2 , Figure 2 which shows a schematic structural diagram of an instrument usage performance evaluation system for an instrument service unit provided by an embodiment of this specification.

[0166] This performance evaluation system can at least include:

[0167] A division module that divides a preset time length based on a unit time length to obtain multiple unit time periods;

[0168] A first acquisition module that acquires a first set of assessment index data corresponding to each instrument service unit, where the first set of assessment index data includes the assessment index data corresponding to each instrument service unit within multiple unit time periods;

[0169] A combination module that, based on the first set of assessment index data corresponding to each instrument service unit, acquires assessment index data distribution information that can reflect the overall distribution of the assessment index data of all instrument service units corresponding to multiple unit time periods, and based on the assessment index data distribution information corresponding to multiple unit time periods, combines multiple unit time periods to obtain multiple combined time periods;

[0170] A second acquisition module that, based on the unit time period combination situation corresponding to multiple combined time periods and the first set of assessment index data corresponding to each instrument service unit, acquires a second set of assessment index data corresponding to each instrument service unit, where the second set of assessment index data includes the assessment index data corresponding to each instrument service unit within multiple combined time periods;

[0171] A third acquisition module that, based on the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) and the second set of assessment index data corresponding to each instrument service unit, acquires a performance assessment data set corresponding to each instrument service unit, where the performance assessment data set includes the performance data corresponding to each instrument service unit within multiple combined time periods;

[0172] A fourth acquisition module that, based on the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) and the performance assessment data set corresponding to each instrument service unit, acquires a performance evaluation result corresponding to each instrument service unit.

[0173] Each embodiment in this specification is described in a progressive manner. For the parts that are the same or similar among the embodiments, reference can be made to each other. Each embodiment focuses on the differences from other embodiments. In particular, for the embodiment of the performance evaluation system, since it is basically similar to the embodiment of the performance evaluation method, the description is relatively simple, and for the relevant parts, reference can be made to the partial description of the embodiment of the performance evaluation method.

[0174] Please refer to Figure 3 the schematic structural diagram of an electronic device provided by the embodiment of this specification shown.

[0175] As Figure 3 shown, the electronic device 300 may include: at least one processor 301, at least one network interface 304, a user interface 303, a memory 305, and at least one communication bus 302.

[0176] Among them, the communication bus 302 can be used to realize the connection and communication of the above-mentioned various components.

[0177] Among them, the user interface 303 may include buttons, and the optional user interface may further include a standard wired interface and a wireless interface.

[0178] Among them, the network interface 304 may include, but is not limited to, a Bluetooth module, an NFC module, a Wi-Fi module, etc.

[0179] Among them, the processor 301 may include one or more processing cores. The processor 301 uses various interfaces and lines to connect various parts within the entire electronic device 300, and by running or executing instructions, programs, code sets, or instruction sets stored in the memory 305, and by calling the data stored in the memory 305, it executes various functions of the electronic device 300 and processes data. Optionally, the processor 301 may be implemented in at least one of the hardware forms of DSP, FPGA, and PLC. The processor 301 may integrate one or a combination of several of CPU, GPU, and modem, etc. Among them, the CPU mainly processes the operating system, user interface, and application programs, etc.; the GPU is responsible for the rendering and drawing of the content to be displayed on the display screen; the modem is used to process wireless communication. It can be understood that the above-mentioned modem may not be integrated into the processor 301 and may be implemented separately by a single chip.

[0180] Among them, the memory 305 may include RAM or ROM. Optionally, the memory 305 includes a non-transitory computer-readable medium. The memory 305 can be used to store instructions, programs, codes, code sets or instruction sets. The memory 305 may include a program storage area and a data storage area. Among them, the program storage area may store instructions for implementing an operating system, instructions for at least one function (such as a touch function, a sound playback function, an image playback function, etc.), instructions for implementing the above-mentioned method embodiments, etc.; the data storage area may store data involved in the above-mentioned method embodiments. Optionally, the memory 305 may also be at least one storage device located far from the aforementioned processor 301. The memory 305, as a computer storage medium, may include an operating system, a network communication module, a user interface module, and a performance evaluation application program. The processor 301 may be used to call the performance evaluation program stored in the memory 305 and execute the steps of the performance evaluation method mentioned in the foregoing embodiments.

[0181] An embodiment of this specification also provides a computer-readable storage medium. Instructions are stored in the computer-readable storage medium. When the instructions run on a computer or a processor, the computer or the processor is caused to execute one or more steps in the above-mentioned performance evaluation method embodiments. If the respective component modules of the above-mentioned electronic device are implemented in the form of software function units and sold or used as independent products, they can be stored in the computer-readable storage medium.

[0182] In the above embodiments, it can be implemented in whole or in part by software, hardware, firmware, or any combination thereof. When implemented using software, it can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, the processes or functions described in the embodiments of this specification are generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable devices. The computer instructions can be stored in a computer-readable storage medium or transmitted through the computer-readable storage medium. The computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center by wire (such as coaxial cable, optical fiber, Digital Subscriber Line (DSL)) or wirelessly (such as infrared, wireless, microwave, etc.). The computer-readable storage medium can be any available medium that can be accessed by a computer or a data storage device such as a server or data center that includes one or more integrated available media. The available medium can be a magnetic medium (e.g., floppy disk, hard disk, magnetic tape), an optical medium (e.g., Digital Versatile Disc (DVD)), or a semiconductor medium (e.g., Solid State Disk (SSD)), etc.

[0183] Those of ordinary skill in the art can understand that all or part of the processes in the above embodiments of the method can be completed by instructing relevant hardware through a computer program. The program can be stored in a computer-readable storage medium. When the program is executed, it can include the processes of the embodiments of the above methods. The foregoing storage medium includes various media that can store program codes, such as ROM, RAM, magnetic disk, or optical disc. Without conflict, the technical features in this embodiment and the implementation scheme can be combined arbitrarily.

[0184] The above-described embodiments are merely described in terms of the preferred embodiment modes of this specification, and do not limit the scope of this specification. Without departing from the design spirit of this specification, various deformations and improvements made by those of ordinary skill in the art to the technical solutions of this specification shall fall within the protection scope determined by the claims of this specification.

Claims

1. A method for evaluating the performance of instrument use in an instrument service unit, characterized in that: include: Dividing the preset time length based on the unit time length to obtain multiple unit time periods; Acquire a first assessment indicator data set corresponding to each instrument service unit, wherein the first assessment indicator data set includes assessment indicator data corresponding to each instrument service unit in multiple unit time periods; Based on the first assessment indicator data set corresponding to each instrument service unit, the assessment indicator data distribution information corresponding to each of the multiple unit time periods, which can reflect the overall distribution of the assessment indicator data of all the instrument service units, is obtained; and based on the assessment indicator data distribution information corresponding to each of the multiple unit time periods, the multiple unit time periods are combined to obtain multiple combined time periods; Based on the unit time period combination corresponding to each of the multiple combined time periods and the first assessment indicator data set corresponding to each of the instrument service units, a second assessment indicator data set corresponding to each of the instrument service units is obtained, wherein the second assessment indicator data set includes the assessment indicator data corresponding to each of the instrument service units in the multiple combined time periods; Based on the superior-inferior solution distance method and the second assessment indicator data set corresponding to each instrument service unit, a performance assessment data set corresponding to each instrument service unit is obtained, wherein the performance assessment data set includes performance data corresponding to each instrument service unit in multiple combined time periods; Based on the superior-inferior solution distance method and the performance evaluation data set corresponding to each instrument service unit, the performance evaluation results corresponding to each instrument service unit are obtained; The method of obtaining the performance evaluation data set corresponding to each instrument service unit based on the superior-inferior solution distance method and the second evaluation indicator data set corresponding to each instrument service unit includes: For each combined time period, all instrument service units are clustered based on the assessment index data corresponding to each instrument service unit in the combined time period to obtain multiple instrument service unit cluster groups corresponding to the combined time period; For each instrument service unit cluster group, based on the assessment index data corresponding to each instrument service unit in the instrument service unit cluster group within the combined time period corresponding to the instrument service unit cluster group, the index representative data corresponding to the instrument service unit cluster group is obtained; For each combined time period, based on the superior-inferior solution distance method and the indicator representative data corresponding to each of the multiple instrument service unit cluster groups corresponding to the combined time period, a performance data set corresponding to the combined time period is obtained, wherein the performance data set corresponding to the combined time period includes the performance data corresponding to each of the multiple instrument service unit cluster groups corresponding to the combined time period; Based on the performance data sets corresponding to each combined time period, the performance evaluation data sets corresponding to each instrument service unit are obtained.

2. The method for evaluating the performance of instrument use of an instrument service unit according to claim 1, characterized in that: The assessment index data includes assessment index values ​​corresponding to each of a plurality of assessment categories, wherein the plurality of assessment categories include at least two of the number of instrument reservations, instrument operation time, fee amount, instrument external sharing score, and instrument maintenance expenditure; Before obtaining the assessment indicator data distribution information corresponding to each of the plurality of unit time periods and reflecting the overall distribution of the assessment indicator data of all the instrument service units based on the first assessment indicator data set corresponding to each of the instrument service units, the method further includes: obtaining a plurality of preset value ranges corresponding to each of the plurality of assessment categories; The method comprises: obtaining, based on the first assessment indicator data set corresponding to each instrument service unit, assessment indicator data distribution information corresponding to each of the plurality of unit time periods, which can reflect the overall distribution of the assessment indicator data of all the instrument service units; and combining the plurality of unit time periods based on the assessment indicator data distribution information corresponding to each of the plurality of unit time periods to obtain a plurality of combined time periods, including: Based on the first assessment indicator data set corresponding to each instrument service unit and the multiple preset value ranges corresponding to the multiple assessment categories, the assessment indicator data distribution information corresponding to each of the multiple unit time periods is obtained, wherein the assessment indicator data distribution information includes the distribution quantity of the overall assessment indicator data of all instrument service units in the unit time period in different preset value ranges of each assessment category; Based on the assessment indicator data distribution information corresponding to each of the multiple unit time periods, the similarity of the assessment indicator data distribution between the unit time periods is obtained; Multiple unit time periods are combined based on the similarity of the distribution of the assessment indicator data between each unit time period to obtain multiple combined time periods.

3. The method for evaluating the performance of instrument use of an instrument service unit according to claim 1, characterized in that: For each instrument service unit cluster group, based on the assessment index data corresponding to each instrument service unit in the instrument service unit cluster group within the combined time period corresponding to the instrument service unit cluster group, the representative index data corresponding to the instrument service unit cluster group is obtained by averaging.

4. The method for evaluating the performance of instrument use of an instrument service unit according to claim 1, characterized in that: Based on the superior and inferior solution distance method and the representative indicator data corresponding to each of the multiple instrument service unit cluster groups corresponding to the combined time period, the performance data set corresponding to the combined time period is obtained, including: Based on the representative index data corresponding to each of the plurality of instrument service unit cluster groups corresponding to the combined time period, a positive ideal solution of the index and a negative ideal solution of the index corresponding to the combined time period are obtained; Based on the indicator representative data corresponding to each of the multiple instrument service unit cluster groups corresponding to the combined time period, the indicator positive ideal solution and the indicator negative ideal solution corresponding to the combined time period, a performance data set corresponding to the combined time period is obtained.

5. The method for evaluating the performance of instrument use of an instrument service unit according to claim 4, characterized in that: The indicator representative data includes indicator values ​​corresponding to each of the multiple assessment categories, and the indicator positive ideal solution and the indicator negative ideal solution also include indicator values ​​corresponding to each of the multiple assessment categories; The performance data set corresponding to the combined time period is obtained based on the indicator representative data corresponding to each of the multiple instrument service unit cluster groups corresponding to the combined time period, the indicator positive ideal solution and the indicator negative ideal solution corresponding to the combined time period. The performance data acquisition for any instrument service unit cluster group in the combined time period includes: Based on the indicator values ​​corresponding to the multiple assessment categories in the indicator representative data of the instrument service unit cluster group and the indicator values ​​corresponding to the multiple assessment categories in the indicator positive ideal solution, a first positive distance is obtained; Based on the indicator values ​​corresponding to each of the multiple assessment categories in the indicator representative data of the instrument service unit cluster group and the indicator values ​​corresponding to each of the multiple assessment categories in the negative ideal solution of the indicator, a first negative distance is obtained; Based on the first positive distance and the first negative distance, the performance data of the instrument service unit cluster group is obtained.

6. The method for evaluating the performance of instrument use in an instrument service unit according to claim 1, characterized in that: The performance evaluation results corresponding to each instrument service unit are obtained based on the superior-inferior solution distance method and the performance evaluation data set corresponding to each instrument service unit, including: Based on the performance evaluation data set corresponding to each instrument service unit, the positive ideal performance solution and the negative ideal performance solution corresponding to the preset time length are obtained; Based on the performance appraisal data set corresponding to each instrument service unit, the positive ideal performance solution corresponding to the preset time length, and the negative ideal performance solution, the performance evaluation result corresponding to each instrument service unit is obtained.

7. The method for evaluating the performance of instrument use of an instrument service unit according to claim 6, characterized in that: The positive ideal performance solution and the negative ideal performance solution both include performance data corresponding to multiple combined time periods; In the step of obtaining the performance evaluation results corresponding to each instrument service unit based on the performance appraisal data set corresponding to each instrument service unit, the positive ideal performance solution corresponding to the preset time length, and the negative ideal performance solution, the performance evaluation results for any instrument service unit are obtained including: Based on the performance data corresponding to each of the multiple combined time periods of the instrument service unit and the performance data corresponding to each of the multiple combined time periods in the performance positive ideal solution, a second positive distance is obtained; Based on the performance data corresponding to each of the multiple combined time periods of the instrument service unit and the performance data corresponding to each of the multiple combined time periods in the negative ideal performance solution, a second negative distance is obtained; Based on the second positive distance and the second negative distance, performance data of the instrument service unit is obtained.

8. The method for evaluating the performance of instrument use in an instrument service unit according to claim 1, characterized in that: After obtaining the performance evaluation data set corresponding to each instrument service unit, the method further includes: Based on the performance appraisal data set corresponding to each instrument service unit, a graph is obtained that can respectively reflect the performance data comparison of each instrument service unit in different combined time periods.

9. An instrument service unit instrument usage performance evaluation system, based on an instrument service unit instrument usage performance evaluation method according to any one of claims 1 to 8, characterized in that: include: A division module divides the preset time length based on the unit time length to obtain multiple unit time periods; A first acquisition module acquires a first assessment indicator data set corresponding to each instrument service unit, wherein the first assessment indicator data set includes assessment indicator data corresponding to each instrument service unit in multiple unit time periods; A combination module, based on the first assessment indicator data set corresponding to each instrument service unit, obtains assessment indicator data distribution information corresponding to each of the multiple unit time periods, which can reflect the overall distribution of the assessment indicator data of all instrument service units, and combines the multiple unit time periods based on the assessment indicator data distribution information corresponding to each of the multiple unit time periods to obtain multiple combined time periods; A second acquisition module acquires a second assessment indicator data set corresponding to each instrument service unit based on the unit time period combination corresponding to each of the multiple combined time periods and the first assessment indicator data set corresponding to each instrument service unit, wherein the second assessment indicator data set includes the assessment indicator data corresponding to each instrument service unit in the multiple combined time periods; A third acquisition module, based on the superior-inferior solution distance method and the second assessment indicator data set corresponding to each instrument service unit, acquires a performance assessment data set corresponding to each instrument service unit, wherein the performance assessment data set includes performance data corresponding to each instrument service unit in multiple combined time periods; The fourth acquisition module acquires the performance evaluation results corresponding to each instrument service unit based on the superior and inferior solution distance method and the performance evaluation data set corresponding to each instrument service unit.

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